Singapore Yield Curve closed down by -6.42% to 1.02 on 23 January 2021 and +-6.85% on a weekly basis. Singapore Yield Curve momentum was last calculated at +50.0/100 indicating positive momentum. Singapore Yield Curve trend is +25.0/100 indicating a positive trend. Singapore Yield Curve momentum exhaustion is 0.55749 indicating Singapore Yield Curve is oversold.Singapore Yield Curve RSI is 59.2503 .
Singapore Yield Curve Chart
stmk81449 var1=6606end
|
|
|
MacroVar offers Free access to our database of historical data for the largest economies and financial markets including economic indicators, stocks, bonds, commodities, currencies and credit default swaps.
Click the CSV button below to download the last 5 years of historical data.
MacroVar API for Python offers free access to last 5 years of historical data. click the Copy Button below and run code in your computer.
To get full historical data:
Singapore Yield Curve closed at 1.02 on 23 January 2021. Singapore Yield Curve trend was last calculated at +25.0/100 (range: -100 to +100) indicating a positive trend based on MacroVar models. Singapore Yield Curve momentum was last calculated at +50.0/100 (range: -100 to +100) indicating positive momentum. Singapore Yield Curve momentum exhaustion is 0.55749 (normal range: -2.5 to +2.5, overbought values: greater than 2.5, oversold values: less than 2.5) indicating Singapore Yield Curve is oversold and a possible reversal is imminent. Singapore Yield Curve RSI was last calculated at 59.2503. Singapore Yield Curve moving averages were last recorded as follows: 1-month moving average: 0.5805 in an uptrend , 1-quarter moving average: 0.61867 in a downtrend and 1-year moving average: 0.54188 in an uptrend. Singapore Yield Curve annual return was last recorded at None%, daily return was last recorded at -6.42%, and weekly return was last recorded at -6.85%. Singapore Yield Curve histrorical 20-day volatility was last recorded at 60.392%, Singapore Yield Curve alpha None, Singapore Yield Curve beta None and Singapore Yield Curve maximum drawdown was recorded at None%. MacroVar models monitor Singapore Yield Curve statistics based on historical data since 1970.
Example: S&P 500 current level of 4,400 = Forward earnings ($200) x P/E Multiple (22)
Price-to-earnings ratio (P/E): The price-to-earnings is the price investors are willing to pay for each $1 of earnings.
Forward earnings: Forward earnings are analysts forecasted earnings on a single stock or index
P/E multiples vs Interest Rates: All financial markets compete for investors depending on their expected returns and risk. As a result, the level and dynamics of interest rates affects corporate bond rates which in turn affects the earnings yield investors are willing to accept for taking the stock risk and the final stock valuation.
Expected Equity Yield: (Terminal Forward Price (calculated as Forward Earnings x P/E multiple) minus current price) divided by current price and multiplied by (number of days to full forward earning earnings divided by 365)
Example: P/E Multiples versus Interest Rates
Assume current US corporate yields are at 2.25%. Investors would require buying stocks with an expected equity yield of 4% to compensate for the elevated risk of holding equities which are much riskier than corporate debt which is safer.
If long-term rates rise given stable expected earnings, bond yields will also rise and as a result investors will require a higher equity yield to buy stocks.
This will lead to either lower future valuations if multiples reduced or forward earnings need to be expected to grow to take up that slack to retain current valuations.
Monitoring the yield curve is critical to predict P/E multiple growth. Market corrections are correlated with yield curve steepening which means higher yields.
MacroVar models monitors the S&P 500 current valuation versus the different scenarios of P/E multiples and earnings per share based on interest rate dynamics and forward earnings new releases.
test1
Optimize your investing & business strategy with MacroVar Data-Driven Financial Research
Use MacroVar to make your financial, investing decisions based on real-time analysis of financial and economic data using advanced models. MacroVar Research is also customized for Businesses.
Free
Monitor financial markets, news
and economic signals personalized to your financial profile and interests.
Basic
Get unlimited access to Financial & Macroeconomic Data
Plus
Get Access, monitor and get automatic notifications on Financial, Macroeconomic and Sector specific Data and Signals
generated using MacroVar models
Pro
Get Access to MacroVar premium multi-factor statistical models
and alternative data (Credit Default Swaps & Risk)
FREE
$300
/year
$500
/quarter
$900
/quarter
NewsFeed Monitor real-time Financial & Macroeconomic signals and newsflow personalized to your financial profile
Daily Newsletter Get up-to-date, in-depth expert analysis for the financial & economic developments personalized to your financial profile daily
Export Data Export data using MacroVar web interface
1 Free Series
Unlimited
Unlimited
Unlimited
Signals & Models Access Data & Signals generated from MacroVar models using web interface, Excel or Python API
Sectors & Industries Monitor Get in-depth analysis of 160+ Sectors & Industries in US, Europe and Asia. MacroVar bundles Financial, Macroeconomic indicators and real-time newsflow for each sector.
Premium Research Reports MacroVar generates research reports based on financial & macroeconomic signals and risk monitors suited for portfolio management and risk management
Systematic Investment Strategies Gain Access to MacroVar database of Algorithmic and Quantitative Trading Strategies
Excel & Python API Access MacroVar data & signals directly from Microsoft Excel and/or Python.
Premium Data & Models Get access to MacroVar premium models & data. MacroVar multi-factor models are used to analyze financial assets based on multiple factors including alternative data like Credit Default Swaps
Risk Management Tools Get access to MacroVar risk management models & data. MacroVar risk management models analyze risk across financial assets to help investors proactively adapt their portfolios.
Users & Data Distribution Multiple users can access MacroVar data using a single account. You can use MacroVar data to build your own applications and branding.
Portfolio Management
Professional investors follow a systematic investment process to achieve the following targets:
Protect their capital by controlling their portfolio’s risk (hedged portfolio)
Generate Consistent & Smooth compounded risk-adjusted returns irrespective of the general market trend
This is achieved by running a hedged portfolio of 15-25 uncorrelated positions, with a self-imposed position limited of 2% of assets under management (AUM).
In this guide MacroVar will provide guidance on how to structure such portfolios. Currently MacroVar models do not provide any tools for portfolio management.
Professional Portfolio Management
Professional traders manage a portfolio based on the following criteria:
Their portfolio consists of Long/Short positions with 1-3 months under normal market volatility conditions. Their trading ideas are formed using 70% fundamental analysis and 30% Price Dynamics models.
Their portfolio consists of 20-30 uncorrelated positions with position limits ranging from 1% to 3% size.
Their aim is to generate consistently high risk-adjusted returns. For example: Portfolio returns 15%, 10% annualized volatility and a maximum drawdown of maximum 10%.
Portfolio Management Stages
World View
The first step is to have a world view to position across equities, bonds, currencies, commodities and STIR. Once a World view is formed, you can move to analyze specific sectors and industries within sectors.
The most important element of portfolio management is to predict whether financial markets will be in a bull or bear market in the next 6-12 months.
Traders must continuously assess where market came from, where market is today and where market is going in the next 6-12 months. MacroVar continuously monitors Financial and macroeconomic data to help traders reassess conditions on a daily basis and generate trading ideas.
Financial Risk Monitoring
MacroVar risk management models, monitor financial conditions to identify risk-on or risk-off environments to help users position their portfolios accordingly.
Pricing Dynamics
MacroVar models analyze momentum, trends, and potential inflection points to time trading ideas correctly. Moreover, other factors like market flows through ETF Fund Flows, COT reports, Implied Volatility are also analyzed by MacroVar models.
Risk Management
Investors should always keep in mind the fundamental principle: In good times (that is when we make money from a trade) they should seek take more risk (let the profits run), while in bad times (when losing money) they should cut their losses short.
Humans seek certainty in profitable situations tending to take profits quickly and take more risks when losing money. Investors should do the opposite of being a human.
Stop Losses & Soft Targets
Investors should use hard stop losses based on the market’s realized or implied volatility to limit their losses. They should also use soft targets in order not to limit their upside by rolling their stop-losses.
Gross Exposure
Gross exposure is the absolute level of a fund’s investments. If an investors has $10 million in capital and deploys $3 million short positions and $7 million long positions he has a gross exposure of $10 million. His gross exposure as percentage of capital is 100%. If gross exposure exceeds 100%, it means that he is using leverage, borrowing money to amplify returns. A gross exposure below 100% indicates portfolio of portfolio is invested in cash.
Portfolio managers when starting to build a portfolio from zero should use 3-4X exposure. If their portfolios grow, they can increase their exposure accordingly to 4X and 5X.
Depending on market volatility adjust timeframes of portfolio (during elevated risk, move to cash or lower position sizes to protect portfolio)
Net Exposure Limits
Net exposure = Long Exposure – Short Exposure (if long = 70K, short = 30K, Net long exposure = 40%)
Portfolio managers should place a net exposure limit +/- 25%
Single Asset Position Limits
Portfolio managers should restrict the size of any position to maximum 10% of gross exposure limit.
Portfolio Stop loss
Investors should set a stop loss of 5-10% in their overall portfolio. If portfolio’s drawdown has reached 10% it means all positions are wrong costing 1% x 10.
Example:
Portfolio $100K exposure, each position is 10%, stop-loss 10%, 1% stop-loss of portfolio
Correlation analysis
Before placing a specific trade, investors should monitor the trade’s correlation to the rest of the positions of the portfolio. MacroVar calculates 60-day rolling correlation between financial assets to monitor correlations.
Beta hedging
Beta measures the systematic risk of a security or portfolio in comparison to the market. A portfolio beta of one indicates the portfolio moves with the market.
Any investment entails two kinds of risks. Unsystematic risks are unique to stocks and industries and these can be reduced by diversifying your portfolio across dissimilar stocks. But systematic risk stems from factors like inflation, interest rates, geopolitical risk, rupee weakness etc. Here you cannot diversify as it impacts all stocks almost in a systematic manner. That is where beta hedging comes in handy.
The beta of a specific security is how much the asset moves (daily return) given a 1-unit market (S&P 500 is the market benchmark).
To hedge out a long/short position investors should calculate and then hedge the beta of the long/short position.
Factor hedging
Portfolio managers sometimes also hedge their portfolios against other factors which are negatively correlated to generic beta.
Value, growth are the major factors to monitor but portfolio managers monitor their portfolio’s sensitivity to other major factors like oil or rates.
Check some of the factors to watch for.
Self-Assessment
Traders aim to maximize return over risk. Investors should frequently assess their trading performance by calculating their portfolio’s sharpe ratio and Kelly Criterion.
GROSS & NET EXPOSURE
CORRELATION ANALYSIS
HEDGING
POSITION LIMITS
PORTFOLIO PERFORMANCE
MacroVar Risk Management Models
MacroVar risk management models monitor global financial risk conditions and provide automatic signals when market risk has changed by analysing multiple financial markets using quantitative methods.
Checkout below details on how MacroVar Risk Management models monitor financial risk conditions. To get started, the window and select Risk from the main menu.
The models produce a composite index called MV Risk Index which represents current global financial risk conditions. This index is formed by analysing the following segments.
MV Risk Management Model Components Overview
Stock Risk monitor
Stock risk is monitored by analysing the implied volatility and shape of the term structure of the US, European and Emerging stock markets.
Credit Risk monitor
Credit risk is monitored by analysing the credit default swaps indices of the United States, European and Emerging Markets.
Bonds Risk
Bonds risk is monitored by analysing the implied volatility of the US treasury market.
Emerging markets risk
Emerging markets risk is monitored by analysing the credit default swaps of government bonds for major emerging countries.
Liquidity risk
Liquidity risk is monitored by analysing interbank rates in the US and Europe.
Currency risk
Currency risk is monitored by analysing the implied volatility of currencies.
Bank risk
Bank risk is gauged by monitoring credit risk of US, European, UK banks and insurance institutions through credit default swaps.
Country Risk
Country risk is gauged by monitoring the Credit Default Swaps dynamics of developed and emerging countries.
Our Risk management models are open-source and MacroVar displays these signals in the Risk Management section of the dashboard and will alert you through MacroVar Newsfeed and Daily newsletter automatically when new signals are generated. You can also access process these signals further and combine them with your research by downloading them from the MacroVar database using Excel, Python API or the Web.
Global Top-Down View
MacroVar’s aim is to provide you with the financial research, data analysis and statistical models to help you maximize your portfolio’s risk adjusted return.
Financial markets are affected by macroeconomic conditions. MacroVar models monitor Global Macro, Geopolitics, Price dynamics and factors affecting specific financial markets.
The most important factor in investing and trading having a view of whether the global macro and market environment is risk-on or risk-off.
During Risk-on environments stocks and commodities are the best asset class. This environment is carried by expanding corporate earnings, optimistic economic outlook, and accommodative central bank policies. During risk-off environments, bonds (under certain conditions) and cash are the best asset classes since there are widespread corporate earnings downgrades, contracting or slowing economic data and uncertain central bank policy. During risk-on periods:
Stocks: Global Stock Markets Up, US Breadth Up, Momentum & Trends Up
Sectors: Cyclical Sectors stronger than Defensive Sectors
Short Term Interest Rates (STIR) Futures markets down, Market expects central bank interest rate hikes in the future to slowdown the economy
Currencies US Dollar moderate, Currencies related to cyclical sectors and commodities up, Risk Off currencies moderate
Financial risk Stock Volatility Moderate to Low, Term Structure in Contango Corporate Bonds Spreads: Down
Global Business Confidence Macroeconomic indicators represented by Global Manufacturing & Services PMI strong – Momentum (YY) & Trends (12MA)
Risk Off assets JPY, Gold, CHF, Long-term bonds and VIX stable down
The trends described above are indicative and don’t always apply since specific financial markets are affected by factors specific to each market. Hence, it is important to monitor factors designed for each market. MacroVar models provide signals based on objective quantitative signals to allow you to identify trading and investing opportunities objectively for each market.
Investment Management Stages
Checkout below how MacroVar can help you in all stages of the Investment Management process.
Trading Ideas MacroVar follows a top-down approach to analyze financial markets using macroeconomic and financial factors
Price Dynamics MacroVar analyzes the price dynamics of each financial asset as well as statistically related factors with each market to help you time your trading ideas correctly and adjust your downside protection.
Risk Management MacroVar Risk management models analyze financial market risk conditions to help you adjust your portfolio’s exposures based on the current environment.
Portfolio Management This stage is not currently covered by MacroVar systems. You should manage your portfolio’s gross, net exposure, hedge your positions, perform correlation analysis between different positions, define position limits and periodically monitor your portfolio’s performance. Learn More in the MacroVar Portfolio Management section.
MacroVar Stock Sectors Models
MacroVar analyzes sectors, industry groups, industries and sub-industries in US, Europe, Emerging Markets and Asia. Each segment is analyzed through its stock market dynamics, credit markets, news flow and industry specific quantitative and macroeconomic factors.
If you are new to Sector & Industry specific investing click here for an introduction to sectors & industries.
More specifically, stock market dynamics are analyzed based on S&P Dow Jones Indices indexes developed based on GICS (? For more), credit markets using individual Credit Default Swaps of specific companies and IBOXX corporate bond indices, news flow based on feeds from reliable finance news sources and industry specific factors based on MacroVar statistical Models and a broad range of sector specific related macroeconomic factors based on PMI & ESI Surveys and other factors like Building Permits. Lastly, MacroVar ranks sectors based on our quantitative models to identify Long / Short Investment themes.
Click here to get an overview of Sectors & Industries across the US, Europe and Asia.
Sector Specific Factor Analysis
Macrovar models analyze in real-time the following relative factors which will be explained briefly in the next sections of this article.
Stock Sectors vs Credit (Credit default swaps or Corporate bonds)
Stock Sectors vs Macroeconomics Surveys
News flow for corporations in each sector / industry
Moreover, MacroVar monitors the following families of factors specific to a sector:
Commodity related Stock Sectors vs Actual commodities For Example XLE representing energy companies’ vs crude oil
Banking related Stock Sectors vs Yield Curve For example Banking ETF (KBE) vs the US Yield Curve
Real estate stock sectors vs Macroeconomic Indicators For example Homebuilders ETF (ITB) vs Building Permits and 30-year Mortgage rates
Stock Sectors vs Macroeconomic leading Surveys ESI and ZEW sector specific reports
Stock sectors analysis of prices, momentum, trends, charts, and news.
Sectors & Industries investing introduction
Stock Sectors are categorized not cyclical sectors and defensive sectors. Cyclical stock sectors are sectors of stocks whose earnings are more sensitive to the business cycle and the economic growth. Defensive stock sectors are sectors of stocks whose earnings are less sensitive to the business cycle.
Cyclical stock sectors Overview
Materials The materials stock sector includes companies manufacturing construction materials, chemicals, glass, paper, forest products, minerals, mining, metals, and steel.
EnergyThe energy stock sector includes companies in the exploration, production, refining, storage, transportation and marketing of oil and gas, coal, and fuel.
Industrials The industrials stock sector includes companies engaged in the manufacturing and distribution of capital goods such as electrical equipment and machinery, aerospace, and defence. It also includes services providers such as construction and engineering, research and consulting services and transportation services.
FinancialsThe financials stock sector includes financial firms like banks and asset management companies offering financial services like consumer finance, asset management, investment banking, brokerage services and security underwriters.
Consumer DiscretionaryThe consumer discretionary stock sector covers companies involved in the manufacturing of consumer discretionary durable goods like automobiles, household goods, textiles, and apparel. The stock sector covers service providers of consumer discretionary services like hotels and restaurants.
Information TechnologyThe information technology stock sector covers companies which develop software, manufacture, and distribute technology hardware and equipment and offer IT consulting services. This stock sector excludes companies offering internet services.
Defensive stock sectors Overview
Consumer Staples The consumer staples stock sector covers businesses manufacturing and distributing of food, beverage, tobacco, personal products, and household goods. The stock sector also includes food and drug retailers.
Healthcare The healthcare stock sector covers businesses offering healthcare services, manufacture and distribute healthcare equipment and supplies. This stock sector includes pharmaceutical and biotechnology companies
Utilities The Utilities stock sector covers utility companies producing, distributing and trading electricity, gas and water.
Communication services The communication services stock sector covers companies that provide content like entertainment, news and social media through the internet and other networks.
cyclical vs defensive sectors
Sectors & Industries versus the Business Cycle
During different economic regimes, different sectors outperform others. For example, during recessions more defensive sectors like consumer staples outperform cyclical sectors like the industrials sector. Hence, an investor would want to scale back on the industrial sector and go long consumer staples.
Hence, after having a global view of the current economic environment, investors can choose their exposure either long, short or long/short across sectors.
The figure below shows which sectors tend to outperform and underperform during different economic cycles.
sectors and the business cycle
Sectors & Industries and the Value Chain
Investment themes are generated primarily from Macroeconomic factors and secondarily Microeconomic factors affecting the value chain in industries. Investors need to look for clues in the world, have views on the value chain and trade to invest with or against the trend.
value chain
Sectors Investing vs Top-Down process and Sector / Industry views
Investors can maximize returns while minimizing risks by investing Long and/or Short across sectors using the following steps:
Obtain view on the market using MacroVar macro view analysis
Obtain a view on a sector by analyzing fundamentals like the value chain and quantitative factors
Decide whether a specific sector will outperform on underperform the market
Decide whether they want to access Market Risk, Sector Risk and build a portfolio based on these criteria
MacroVar analyzes sectors, industry groups, industries and sub-industries in US, Europe, Emerging Markets and Asia. Each segment is analyzed through its stock market dynamics, credit markets, news flow and industry specific quantitative and macroeconomic factors.
If you are new to Sector & Industry specific investing click here for an introduction to sectors & industries.
More specifically, stock market dynamics are analyzed based on S&P Dow Jones Indices indexes developed based on GICS (? For more), credit markets using individual Credit Default Swaps of specific companies and IBOXX corporate bond indices, news flow based on feeds from reliable finance news sources and industry specific factors based on MacroVar statistical Models and a broad range of sector specific related macroeconomic factors based on PMI & ESI Surveys and other factors like Building Permits. Lastly, MacroVar ranks sectors based on our quantitative models to identify Long / Short Investment themes.
Click here to get an overview of Sectors & Industries across the US, Europe and Asia.
Sector Specific Factor Analysis
Macrovar models analyze in real-time the following relative factors which will be explained briefly in the next sections of this article.
Stock Sectors vs Credit (Credit default swaps or Corporate bonds)
Stock Sectors vs Macroeconomics Surveys
News flow for corporations in each sector / industry
Moreover, MacroVar monitors the following families of factors specific to a sector:
Commodity related Stock Sectors vs Actual commodities For Example XLE representing energy companies’ vs crude oil
Banking related Stock Sectors vs Yield Curve For example Banking ETF (KBE) vs the US Yield Curve
Real estate stock sectors vs Macroeconomic Indicators For example Homebuilders ETF (ITB) vs Building Permits and 30-year Mortgage rates
Stock Sectors vs Macroeconomic leading Surveys ESI and ZEW sector specific reports
Stock sectors analysis of prices, momentum, trends, charts, and news.
Sectors & Industries investing introduction
Stock Sectors are categorized not cyclical sectors and defensive sectors. Cyclical stock sectors are sectors of stocks whose earnings are more sensitive to the business cycle and the economic growth. Defensive stock sectors are sectors of stocks whose earnings are less sensitive to the business cycle.
Cyclical stock sectors Overview
Materials The materials stock sector includes companies manufacturing construction materials, chemicals, glass, paper, forest products, minerals, mining, metals, and steel.
EnergyThe energy stock sector includes companies in the exploration, production, refining, storage, transportation and marketing of oil and gas, coal, and fuel.
Industrials The industrials stock sector includes companies engaged in the manufacturing and distribution of capital goods such as electrical equipment and machinery, aerospace, and defence. It also includes services providers such as construction and engineering, research and consulting services and transportation services.
FinancialsThe financials stock sector includes financial firms like banks and asset management companies offering financial services like consumer finance, asset management, investment banking, brokerage services and security underwriters.
Consumer DiscretionaryThe consumer discretionary stock sector covers companies involved in the manufacturing of consumer discretionary durable goods like automobiles, household goods, textiles, and apparel. The stock sector covers service providers of consumer discretionary services like hotels and restaurants.
Information TechnologyThe information technology stock sector covers companies which develop software, manufacture, and distribute technology hardware and equipment and offer IT consulting services. This stock sector excludes companies offering internet services.
Defensive stock sectors Overview
Consumer Staples The consumer staples stock sector covers businesses manufacturing and distributing of food, beverage, tobacco, personal products, and household goods. The stock sector also includes food and drug retailers.
Healthcare The healthcare stock sector covers businesses offering healthcare services, manufacture and distribute healthcare equipment and supplies. This stock sector includes pharmaceutical and biotechnology companies
Utilities The Utilities stock sector covers utility companies producing, distributing and trading electricity, gas and water.
Communication services The communication services stock sector covers companies that provide content like entertainment, news and social media through the internet and other networks.
cyclical vs defensive sectors
Sectors & Industries versus the Business Cycle
During different economic regimes, different sectors outperform others. For example, during recessions more defensive sectors like consumer staples outperform cyclical sectors like the industrials sector. Hence, an investor would want to scale back on the industrial sector and go long consumer staples.
Hence, after having a global view of the current economic environment, investors can choose their exposure either long, short or long/short across sectors.
The figure below shows which sectors tend to outperform and underperform during different economic cycles.
sectors and the business cycle
Sectors & Industries and the Value Chain
Investment themes are generated primarily from Macroeconomic factors and secondarily Microeconomic factors affecting the value chain in industries. Investors need to look for clues in the world, have views on the value chain and trade to invest with or against the trend.
value chain
Sectors Investing vs Top-Down process and Sector / Industry views
Investors can maximize returns while minimizing risks by investing Long and/or Short across sectors using the following steps:
Obtain view on the market using MacroVar macro view analysis
Obtain a view on a sector by analyzing fundamentals like the value chain and quantitative factors
Decide whether a specific sector will outperform on underperform the market
Decide whether they want to access Market Risk, Sector Risk and build a portfolio based on these criteria
MacroVar Multi-factor models
MacroVar uses a series of quantitative models to identify:
Divergences between the financial markets analyzed and factors affecting them both Macroeconomic Indicators and other related financial markets
Trends
Momentum
Inflection points after extended trends
Extreme Sentiment Indicators based on Commitment of Traders report and other factors
MacroVar Models are open-source, transparent and MacroVar displays these signals in this dashboard, markets webpage and will alert you through MacroVar Newsfeed and Daily newsletter automatically when new signals are generated. You can also access raw data for each financial series including signals from these models by accessing MV database.
Single Factor models
MacroVar analyses macroeconomic and financial factors highly correlated with a specific financial asset. MacroVar models aim to identify divergences in the dynamics between indicators and financial markets which may lead to short-term trading opportunities.
Financial Markets versus Macroeconomic Factors
MacroVar a vast range of macroeconomic factors which are highly correlated with specific financial markets. Some of these factors can be grouped as follows: Stocks vs Manufacturing & Services PMI, Stocks vs ESI, Banking related Stock Sectors vs Yield Curve (KBE vs US 2s10s Yield Curve), Real estate stock sectors vs Macroeconomic Indicators like building permits and mortgage rate levels (ITB ETF vs Building Permits & 30-year mortgage rates), Stock Sectors vs ZEW & ESI sector specific reports
Financial Markets versus market Factors
MacroVar a vast range of financial factors which are highly correlated with specific financial markets. Financial Factors can be grouped as follows: Stocks versus Credit default swaps, Stock Sectors versus and corporate bonds, Stocks vs 10-Year Bond Yields, Commodity related Stock Sectors vs Actual commodities (For Example XLE representing energy companies’ vs crude oil)
Term Structures
MacroVar monitors the term structures of major financial assets used to gauge market expectations like VIX, VSTOXX, SOFR, SONIA, EURIBOR, 3-Month LIBOR, Fed Funds, Eurodollar futures.
The shape and dynamics of the implied curve is used for forecasting financial asset moves.
MacroVar uses quantitative models to monitor trends, momentum and possible inflection points for all financial assets monitored. Our Models are open-source, transparent and MacroVar displays these signals in this dashboard and will alert you through MacroVar Newsfeed and Daily newsletter automatically when new signals are generated. You can also access raw data for each financial series including signals from these models by accessing MV database.
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
Value currently 0 meaning that trend is flat.
Value is -25 meaning a strong -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum and long-term is currently present.
Value is -100 meaning a strong -ve momentum and long-term is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong +ve momentum and long-term is currently present.
Value is +100 meaning a strong +ve momentum and long-term is currently present.
Value is either +125 (when Momentum and Trend is +100) or -125 (when Momentum and Trend is -100) meaning that there is a moderate possibility of price reversal from the current trend.
Value is either +150 (when Momentum and Trend is +100) or -150 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Momentum Model (M)
Momentum trading is used to capture moves in shorter timeframes than trends. Momentum is the relative change occurring in markets. Relative change is different to a trend. A long-term trend can be up but the short-term momentum of a specific market can be 0.
If a market moves down and then moves up and then moves back down the net relative change in price is 0. That means momentum is 0. A short-term positive momentum, with a long-term downtrend results in markets with no momentum.
MacroVar momentum signal ranges from -100 to +100. The market trend signal is derived as the mean value from 4 calculations for each asset. The timeframes monitored are the following:
1 Day (1 trading day)
1 Week (5 trading days)
1 Month (20 trading days)
3 Months (60 trading days)
For each timeframe, the following calculations are performed:
Calculations of the return for the specific timeframe
If return calculated is higher than 0, signal value 1 else signal value -1
Finally, the 4 values are aggregated daily.
A technical rollover is identified when MacroVar momentum strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that momentum is flat.
Value is -25 meaning a weak -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum is currently present.
Value is -100 meaning a strong -ve momentum is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong -ve momentum is currently present.
Value is +100 meaning a strong -ve momentum is currently present.
MacroVar Trend model (T)
MacroVar Trend signal ranges from -100 to +100. The market trend signal is derived as the mean value from 8 calculations for each asset. The timeframes monitored are the following:
1-month (20 trading days)
3-months (60 trading days)
6-months (125 trading days)
1-year (250 trading days)
For each timeframe, the following calculations are performed:
Closing price vs moving average (MA): if price greater than MA value is +1, else -1
Moving average slope: if current MA is higher than previous MA, upward slope +1, else -1
MacroVar trend model can be used as a trend strength indicator. MacroVar trend strength values ranging between +75 and +100 or -75 and -100 show strong trend strength.
A technical rollover is identified when MacroVar trend strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that trend is flat.
Value is -25 meaning a weak -ve trend is currently present.
Value is -50 meaning a strong -ve trend is currently present.
Value is -75 meaning a strong -ve trend is currently present.
Value is -100 meaning a strong -ve trend is currently present.
Value is +25 meaning a strong +ve trend is currently present.
Value is +50 meaning a strong +ve trend is currently present.
Value is +75 meaning a strong -ve trend is currently present.
Value is +100 meaning a strong -ve trend is currently present.
MacroVar Bubble model (B)
MacroVar bubble model monitors a financial asset’s price relative to its 252-day moving average to identify possible inflection point. Extreme moves often followed by price reversals have a high probability of occuring when MacroVar bubble indicator is greater than 2.5 or less than -2.5.
The MacroVar bubble model is calculated using the formula: Latest Price – (252-day Moving Average) / (252-day Standard Deviation). It represents a z-score and extreme values are greater than 2.5 and less than -2.5. Other thresholds include -3, +3.
Value is higher than +2.5 or lower than -2.5 meaning that there is a moderate possibility of price reversal from the current trend.
Value is higher than +3 (when Momentum and Trend is +100) or -3 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Stock Sectors Models
MacroVar analyzes sectors, industry groups, industries and sub-industries in US, Europe, Emerging Markets and Asia. Each segment is analyzed through its stock market dynamics, credit markets, news flow and industry specific quantitative and macroeconomic factors.
If you are new to Sector & Industry specific investing click here for an introduction to sectors & industries.
More specifically, stock market dynamics are analyzed based on S&P Dow Jones Indices indexes developed based on GICS (? For more), credit markets using individual Credit Default Swaps of specific companies and IBOXX corporate bond indices, news flow based on feeds from reliable finance news sources and industry specific factors based on MacroVar statistical Models and a broad range of sector specific related macroeconomic factors based on PMI & ESI Surveys and other factors like Building Permits. Lastly, MacroVar ranks sectors based on our quantitative models to identify Long / Short Investment themes.
Click here to get an overview of Sectors & Industries across the US, Europe and Asia.
Sector Specific Factor Analysis
Macrovar models analyze in real-time the following relative factors which will be explained briefly in the next sections of this article.
Stock Sectors vs Credit (Credit default swaps or Corporate bonds)
Stock Sectors vs Macroeconomics Surveys
News flow for corporations in each sector / industry
Moreover, MacroVar monitors the following families of factors specific to a sector:
Commodity related Stock Sectors vs Actual commodities For Example XLE representing energy companies’ vs crude oil
Banking related Stock Sectors vs Yield Curve For example Banking ETF (KBE) vs the US Yield Curve
Real estate stock sectors vs Macroeconomic Indicators For example Homebuilders ETF (ITB) vs Building Permits and 30-year Mortgage rates
Stock Sectors vs Macroeconomic leading Surveys ESI and ZEW sector specific reports
Stock sectors analysis of prices, momentum, trends, charts, and news.
Sectors & Industries investing introduction
Stock Sectors are categorized not cyclical sectors and defensive sectors. Cyclical stock sectors are sectors of stocks whose earnings are more sensitive to the business cycle and the economic growth. Defensive stock sectors are sectors of stocks whose earnings are less sensitive to the business cycle.
Cyclical stock sectors Overview
Materials The materials stock sector includes companies manufacturing construction materials, chemicals, glass, paper, forest products, minerals, mining, metals, and steel.
EnergyThe energy stock sector includes companies in the exploration, production, refining, storage, transportation and marketing of oil and gas, coal, and fuel.
Industrials The industrials stock sector includes companies engaged in the manufacturing and distribution of capital goods such as electrical equipment and machinery, aerospace, and defence. It also includes services providers such as construction and engineering, research and consulting services and transportation services.
FinancialsThe financials stock sector includes financial firms like banks and asset management companies offering financial services like consumer finance, asset management, investment banking, brokerage services and security underwriters.
Consumer DiscretionaryThe consumer discretionary stock sector covers companies involved in the manufacturing of consumer discretionary durable goods like automobiles, household goods, textiles, and apparel. The stock sector covers service providers of consumer discretionary services like hotels and restaurants.
Information TechnologyThe information technology stock sector covers companies which develop software, manufacture, and distribute technology hardware and equipment and offer IT consulting services. This stock sector excludes companies offering internet services.
Defensive stock sectors Overview
Consumer Staples The consumer staples stock sector covers businesses manufacturing and distributing of food, beverage, tobacco, personal products, and household goods. The stock sector also includes food and drug retailers.
Healthcare The healthcare stock sector covers businesses offering healthcare services, manufacture and distribute healthcare equipment and supplies. This stock sector includes pharmaceutical and biotechnology companies
Utilities The Utilities stock sector covers utility companies producing, distributing and trading electricity, gas and water.
Communication services The communication services stock sector covers companies that provide content like entertainment, news and social media through the internet and other networks.
cyclical vs defensive sectors
Sectors & Industries versus the Business Cycle
During different economic regimes, different sectors outperform others. For example, during recessions more defensive sectors like consumer staples outperform cyclical sectors like the industrials sector. Hence, an investor would want to scale back on the industrial sector and go long consumer staples.
Hence, after having a global view of the current economic environment, investors can choose their exposure either long, short or long/short across sectors.
The figure below shows which sectors tend to outperform and underperform during different economic cycles.
sectors and the business cycle
Sectors & Industries and the Value Chain
Investment themes are generated primarily from Macroeconomic factors and secondarily Microeconomic factors affecting the value chain in industries. Investors need to look for clues in the world, have views on the value chain and trade to invest with or against the trend.
value chain
Sectors Investing vs Top-Down process and Sector / Industry views
Investors can maximize returns while minimizing risks by investing Long and/or Short across sectors using the following steps:
Obtain view on the market using MacroVar macro view analysis
Obtain a view on a sector by analyzing fundamentals like the value chain and quantitative factors
Decide whether a specific sector will outperform on underperform the market
Decide whether they want to access Market Risk, Sector Risk and build a portfolio based on these criteria
MacroVar Commodities Market Models
One of the most important blocks of global macro strategies, is the analysis of commodities dynamics since they are original source in the value chain.
value chain
Checkout below details on how MacroVar models analyze Commodities. To get started, the window and select Markets from the main menu.
If you are new to Commodities investing heck our introduction.
Commodities and the Global Economy
Energy commodities and metal commodities used in manufacturing are cyclical and closely correlated with global economic growth. The most important commodities considered leading indicators of the global economy are crude oil and copper.
Crude oil demand depends on global trade hence it is intricately linked to global economic growth. Copper is the main metal used in most sectors of the economy from construction to electronics and power generation and transmission. Shipping is a commodity related sector which is also affected by global economic growth.
MacroVar monitors both commodities prices dynamics closely versus the Global Manufacturing PMI which is a leading indicator of global economic growth. Large divergences between commodities and Global PMI momentum measured by year over year return may signify commodity trading opportunities.
Commodities versus the US Dollar
Since commodities are priced in US dollars, when the value of the dollar rises, the price of commodities measured in other currencies rise. When raw material prices rise, demand tends to fall. A long-term bear market in the dollar began in 2002 and corresponded with a secular bull market in commodity prices.
Commodities and Global Risk
Precious metals are considered low-risk safe assets during increased global market risk. Funds flow to precious metals in anticipation of fiscal and monetary policy stimuli programs which normally bring inflationary conditions and currency depreciations or devaluations. Gold is the most important safe asset followed by silver platinum and palladium. Silver, platinum and palladium are considered precious metals but since they are also used as basic metals in manufacturing, they are also affected by the global economy.
Commodities Seasonality
Some commodities are heavily affected by seasonality. MacroVar monitors seasonality for the following commodities: Crude Oil, Natural Gas, Gold, Lumber, Sugar, Corn, Baltic Dry Index, Copper, Silver, Palladium, Cotton. Check our guide on how MacroVar monitors seasonality for financial markets.
Demand / Supply Dynamics
Commodity prices are determined by demand and supply dynamics. Commodities supply shocks like the Vale dam disaster or extreme weather conditions like floods often lead to supply disruptions and sudden spikes in commodity prices. Some commodities are affected by political crisis in commodity producing countries.
Crude Oil
The main sources for monitoring the physical demand and supply of the crude oil market are OPEC, and IEA reports and actions.
Platinum & Palladium
John Matthey produces detailed reports for the demand / supply dynamics of the physical market for platinum and palladium.
Weather
Agriculture commodities are affected by weather conditions. Extreme weather phenomena like spring floods have historically caused commodities prices spikes due to supply shocks mainly for food commodities like corn, wheat, rice, soybeans, and coffee.
Weather forecasts are particularly useful in monitoring when trading food commodities. US weather forecasts are provided by NOAA.
Aura commodities provides live monitoring of global weather conditions and detailed reports for demand and supply dynamics for the following food commodities: corn, soybeans, wheat, cocoa, coffee, cotton, sugar, and palm oil.
Commodities and Commitment of Traders Report
The COT report is used by MacroVar to analyze the sentiment of financial institutions and hedge funds about commodities monitored. Check our guide on how to analyze the cot report.
Commodities Markets vs ETF Instruments
ETFs comprised of commodities producing companies are closely correlated with the spot price of these commodities. MacroVar monitors the correlations of those pairs looking for divergence investment opportunities.
Commodities Markets vs commodity producing countries currencies
The economies and currencies of commodity producing countries for a specific commodity are leading indicators of specific commodities. MacroVar monitors correlations between commodity prices and currencies of these countries. For example, MacroVar monitors the correlation between crude oil and the Russian Rubble since Russian economy is heavily exposed in the production of crude oil.
Commodities Markets analyzed
MacroVar analyzes the following commodities grouped by type:
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
Value currently 0 meaning that trend is flat.
Value is -25 meaning a strong -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum and long-term is currently present.
Value is -100 meaning a strong -ve momentum and long-term is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong +ve momentum and long-term is currently present.
Value is +100 meaning a strong +ve momentum and long-term is currently present.
Value is either +125 (when Momentum and Trend is +100) or -125 (when Momentum and Trend is -100) meaning that there is a moderate possibility of price reversal from the current trend.
Value is either +150 (when Momentum and Trend is +100) or -150 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Momentum Model (M)
Momentum trading is used to capture moves in shorter timeframes than trends. Momentum is the relative change occurring in markets. Relative change is different to a trend. A long-term trend can be up but the short-term momentum of a specific market can be 0.
If a market moves down and then moves up and then moves back down the net relative change in price is 0. That means momentum is 0. A short-term positive momentum, with a long-term downtrend results in markets with no momentum.
MacroVar momentum signal ranges from -100 to +100. The market trend signal is derived as the mean value from 4 calculations for each asset. The timeframes monitored are the following:
1 Day (1 trading day)
1 Week (5 trading days)
1 Month (20 trading days)
3 Months (60 trading days)
For each timeframe, the following calculations are performed:
Calculations of the return for the specific timeframe
If return calculated is higher than 0, signal value 1 else signal value -1
Finally, the 4 values are aggregated daily.
A technical rollover is identified when MacroVar momentum strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that momentum is flat.
Value is -25 meaning a weak -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum is currently present.
Value is -100 meaning a strong -ve momentum is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong -ve momentum is currently present.
Value is +100 meaning a strong -ve momentum is currently present.
MacroVar Trend model (T)
MacroVar Trend signal ranges from -100 to +100. The market trend signal is derived as the mean value from 8 calculations for each asset. The timeframes monitored are the following:
1-month (20 trading days)
3-months (60 trading days)
6-months (125 trading days)
1-year (250 trading days)
For each timeframe, the following calculations are performed:
Closing price vs moving average (MA): if price greater than MA value is +1, else -1
Moving average slope: if current MA is higher than previous MA, upward slope +1, else -1
MacroVar trend model can be used as a trend strength indicator. MacroVar trend strength values ranging between +75 and +100 or -75 and -100 show strong trend strength.
A technical rollover is identified when MacroVar trend strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that trend is flat.
Value is -25 meaning a weak -ve trend is currently present.
Value is -50 meaning a strong -ve trend is currently present.
Value is -75 meaning a strong -ve trend is currently present.
Value is -100 meaning a strong -ve trend is currently present.
Value is +25 meaning a strong +ve trend is currently present.
Value is +50 meaning a strong +ve trend is currently present.
Value is +75 meaning a strong -ve trend is currently present.
Value is +100 meaning a strong -ve trend is currently present.
MacroVar Bubble model (B)
MacroVar bubble model monitors a financial asset’s price relative to its 252-day moving average to identify possible inflection point. Extreme moves often followed by price reversals have a high probability of occuring when MacroVar bubble indicator is greater than 2.5 or less than -2.5.
The MacroVar bubble model is calculated using the formula: Latest Price – (252-day Moving Average) / (252-day Standard Deviation). It represents a z-score and extreme values are greater than 2.5 and less than -2.5. Other thresholds include -3, +3.
Value is higher than +2.5 or lower than -2.5 meaning that there is a moderate possibility of price reversal from the current trend.
Value is higher than +3 (when Momentum and Trend is +100) or -3 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Currencies Market Models
Investing in currencies requires analysis of global and local economic growth dynamics, liquidity, market risk as well factors specific to an individual nation’s economy.
If you are new to Currencies and Forex Trading check our introduction.
MacroVar uses several factors that allow traders to analyze and trade the currency market.
Checkout below details on how MacroVar models analyze Currencies. To get started, the window and select Markets from the main menu.
MacroVar Currency models Overview
MacroVar monitors the following economic and financial market factors affecting currencies.
Currencies versus Yield Differential
Most importantly, currencies are affected by relative differences in monetary policies between 2 countries and their currencies which is depicted in the yield differential between short-end bonds (2-year bonds) or by the long-term inflation outlook or country risk premium between countries represented by the 10-year bond yield differentials.
For example, let us examine the USDGBP in an environment where the US economy is stronger than the UK economy. During a strong US economy, the Fed raises short-term rates to keep the economy strong while controlling inflation. This causes the US 2-year bond rates to rise. At the same time, the BOE keeps short-term interest rates low to help a weak UK economy strengthen. This causes UK 2-year bond rates to stay low. Since US 2-year bond rates yield more than UK 2-year bond rates, capital flows out of GBP into the US Dollar causing the USDGBP to appreciate.
Currencies versus 10Y, CDS, 2Y
When credit risk in a country rises, it’s currency weakens and vice-versa. MacroVar monitors the dynamics of the country’s 5-year CDS (Credit default swaps) vs each currency.
Currencies and the Economy
Currencies are highly correlated to the country’s economy. The country’s economy is compared with the currency’s performance using manufacturing PMI.
Currencies and Monetary Policy
When a country’s economy weakens, the government and central bank use fiscal policy and monetary policy tools to inject or withdraw liquidity from the country’s financial system to support the economy.
Central banks use monetary policy tools to inject liquidity. The tools used are the expansion of their balance sheets, reduction of the required reserve ratio and cutting short-term rates. Expansion monetary tools cause the country’s currency to weaken versus other countries.
Currencies and Fiscal Policy
Countries’ policymakers use fiscal policy tools to strengthen a weakening economy. Fiscal policies may include reduction in taxes and increase in government spending through infrastructure spending. Fiscal and Monetary policy stimuli weaken the country’s currency.
Currencies and Commodity producing countries
The currencies of countries which depend on heavily on producing commodities are closely correlated with the price of commodities.
Crude Oil related Currencies
The Russian Rubble, Norwegian Krona, Canadian dollar depend on the price of crude oil because these countries are major crude oil producers.
Currencies linked to industrial metals
The Australian Dollar is dependent on industrial metals because Australia is a major metal exporter mainly to China. Chile is a major producer and exporter of copper, hence the Chilean Peso is closely correlated with the spot price of copper.
South Africa is major producer and exporter of Gold and Platinum. Gold and Platinum are respectively 20% and 7.5% of South Africa’s exports. Hence, the South African Rand (ZARUSD) is closely correlated with the spot price of these commodities.
Examples
Australia is highly dependent on exporting commodities to China. When China slows down, its demand for iron ore, coal and metal exports from Australia falls. Australia’s economy as a result weakens and it’s central bank (RBA) injects liquidity by lowering short-term interest rates. This causes Australia 2-year bond yields to weaken versus those of the United States.
Currencies versus CESI (Citi Economic Surprise Index)
The Citi Economic Surprise Index (CESI) measures whether data releases from an economy have beaten or missed expectations in the past 90 calendar days. A positive index means releases have been better than expected and vice-versa. The index is measured in basis points of aggregated and decay-adjusted standard deviations of surprises and has no natural bounds.
CESI is a coincident indicator, oscillating fast and is used for short-term Forex trading.
Currencies Quantitative models
MacroVar models monitor different quantitative values for all currencies. The most important currencies price indicators are: 1. MacroVar Trend Indicator, 2. MacroVar Momentum Indicator, 3. Year on Year momentum, 4. 3m, 5. 1m, 6. 1w
MacroVar currencies trend indicator is compiled from signals compiles from different timeframes. Currencies trend indicator ranges from -100 to +100. A currency technical rollover is identified when MacroVar trend strength indicator moves from positive to negative. MacroVar currencies momentum indicator monitors price action for different timeframes of commodities. Momentum indicator ranges from -100 to +100.
Geopolitics
Trade tensions between countries cause global economic slowdowns which lead to rising market risk and capital flows to low-risk countries and financial assets like the US Dollar. Moreover, sanctions or tariffs imposed by major importing countries like the United States to other countries leads to depreciation of those currencies. For example, in June of 2019 the United States increased tariffs in Mexico causing the Mexican peso to depreciate a lot.
Currency Implied Volatility
MacroVar monitors implied volatility of major currencies. Implied volatility is used as a leading indicator of the currency’s risk. Currency implied volatility indicates how much the market expects a currency pair to fluctuate. Currency implied volatility is considered a measure of market risk.
Currency 3-month Risk Reversal
One of the most useful indicators for sentiments is looking at call-put skew on 3-month risk reversals. If someone is long EUR and needs to maintain a long bias, they could buy out-of-the-money puts when their view turns bearish and finance the hedge by selling out-of-the money calls.
If this happens to a large extent, implied volatility of puts will rise relative to that of the calls. This relationship would be negative for EUR, implying EUR weakness.
Currencies vs Commitment of Traders report
The COT report is published weekly (available every Friday) and provides analysis of holdings of different market participants for all major currencies monitored.
The COT report is used to monitor capital flows of currencies and detect trend continuations or reversals. A specific currency tends to reverse when the currency is overbought or oversold. COT report data are especially useful in detecting overbought and oversold market conditions.
COT Report versus US Dollar
The COT report is used by MacroVar to monitor the market’s US Dollar net positioning by calculating the average position of total Open Interest of large speculators for the following assets: EUR, GBP, CHF, JPY, CAD, AUD, NZD, MXN, RUB, BRL. Net long positioning in this indicator is interpreted as net long in the US Dollar.
COT Report and Safe Currencies
MacroVar also monitors net positions in low-risk currencies like the JPY and CHF. During high market risk environments capital flows to these currencies reporting increasing net long positions. Other safe financial assets related to the JPY, CHF are the US 10-year bond, Gold and VIX.
MacroVar Credit Market Models
Credit is the market of corporate bonds which is very important for all major economies. Corporate bonds are closely correlated with stocks and since bond investors are more diligent in analyzing credit risk, their decisions represented by credit spreads are often leading indicators for stocks.
MacroVar statistical models analyze the dynamics between stock indices, stock sectors versus credit default swaps and corporate bond indices to identify investing opportunities when divergences between the different markets occur.
MacroVar monitors credit default swaps of more than 500 individual companies and indexes as well as IBOXX corporate bond indices for 80 sectors and industries of the United States and 50 sectors and industries of the European corporate bond market.
If you are new to the credit market click here for an introduction.
Checkout below details on how MacroVar models analyze Credit Markets. To get started, the window and select Markets from the main menu.
MacroVar Credit Related Factors
MacroVar uses a top-down approach for analyzing the credit market. The models used are regression models between the momentum of stock markets and the corresponding credit markets in order to identify potential divergences and investment opportunities in the stock market.
Credit Risk versus Stocks Overview
The major credit indicators analyzed versus the corresponding stock market indices are:
US Credit Risk vs Stocks Models compares Stock Indices (S&P 500) versus CDS (Credit Default Swaps) Indexes (CDX IG / CDX HY)
EU Credit Risk vs Stocks Models compares Stock Indices (STOXX 600) versus CDS (Credit Default Swaps) Indexes (ITRAXX Indexes)
Emerging Markets credit Risk vs Stocks Models compares Stock Indices (EEM) versus CDS (Credit Default Swaps) Indexes (CDX Indexes)
CDX indices are a family of tradable credit default swap (CDS) indices covering North America and the emerging markets.
iTraxx indices are a family of European, Asian and emerging market tradable credit default swap indices.
Credit Risk versus Stock Sectors Analysis
MacroVar models use the same regression models to analyze specific stock sectors to their IBOXX credit risk indexes for the US and European stock markets.
Credit Risk versus Volatility Risk
MacroVar monitors the relationship between credit risk and implied stock volatility to identify investment opportunities with the following strategies:
Take advantage of compressed volatility when complacency in the market exists (monitor -1 standard deviation levels)
Take advantage of temporarily spiked volatility if the credit risk levels are stable (monitor levels of +2 standard deviations)
The markets monitored are CDX vs VIX and ITRAXX vs VSTOXX.
Countries Credit Risk versus Currencies
MacroVar models monitor all countries CDS to identify turning points in countries’ credit risk which in turn will affect their bonds, stocks and FX.
CDS Database
MacroVar keeps a database of 5-year credit default swaps indices for 1,000 corporations categorized by sector and region. Click here to access the database.
MacroVar Fixed Income Models
The fixed income market is one of the main pillars for managing an investment portfolio and understanding the functioning of global markets and macroeconomics. Bank credit and debt capital markets are the lifeblood of the financial system.
MacroVar uses several factors that allow traders to analyze and trade different sectors of the fixed income market.
Checkout below analysis of how MacroVar models analyze Fixed Income Markets. To get started, the window and select Markets from the main menu of the dashboard page.
If you are new to Bond Markets / Fixed Income, click here for an introduction to bonds.
Fixed Income Factor Analysis
Government Bonds
MacroVar financial models monitor short-term (2-year), medium-term (5-year) and long-term (10-year) government bonds and the dynamics of the yield curves for the largest 30 economies in the world.
The short-term (2-year) bond is driven by the market expectations of the central bank’s decisions while the 10-year bond is driven by inflation / growth market expectations.
Moreover, MacroVar analyzes the following financial and macroeconomic factors using statistical models:
Macroeconomic Surveys Dynamics vs Government bonds
Inflation Index Dynamics vs Government bonds
Exchange Rate Dynamics vs Government bonds
Stock Market Dynamics vs Government bonds
Inflation Protected Bonds Dynamics
Government bonds are closely correlated with the levels and dynamics of inflation. However, CPI which is the standard macroeconomic indicator to track inflation is a coincident indicator. In order to track inflationary expectations 1-3 months in the future, MacroVar analyzes price dynamics from manufacturing and services surveys like the ISM, NMI, PMI and ESI.
Corporate bonds
Corporate bonds are bonds issued by large corporations, to finance projects or their business activity.
Corporate bonds are closely correlated with stocks and since bond investors are more diligent in analyzing credit risk, their decisions represented by credit spreads are often leading indicators for stocks.
MacroVar statistical models analyze the dynamics between stock indices, stock sectors versus credit default swaps and corporate bond indices to identify investing opportunities when divergences between the different markets occur.
credit cycle
MacroVar monitors credit default swaps of more than 500 individual companies and indexes as well as IBOXX corporate bond indices for 80 sectors and industries of the United States and 50 sectors and industries of the European corporate bond market.
Get an overview view of credit default swaps and corporate credit markets.
Fixed Income Logic
Investors trade government bonds based on their expectations of future economic growth and inflation.
The most important criteria to categorize government bonds are:
Government Bond maturity (Short-term bonds: 1 to 4-year maturity, Long-Term bonds: 10-year to 30-year maturity)
Government Bond Credit risk based on the country’s credit profile
Government bonds are highly correlated with the factors presented below. However, during extreme economic downturns, central banks use extraordinary measures to combat recessions like extensive quantitative easing programs (money printing) with which they purchase government bonds of all maturities hence distorting price discovery.
The factors affecting government bonds are summarized with the case studies below:
Low-Risk Government bonds like the US and Germany 10-year bonds rally on global slowdown conditions during low inflation environments.
Government bonds are closely correlated with the country’s economy expectations. When leading economic indicators show economic slowdown government bonds rise. Leading indicators used to gauge the country’s economic expectations are the following:
All economies: Manufacturing PMI, Housing activity, Domestic Banks exposure.
Commodity dependent economies: Commodity trends and momentum
Export oriented economies: e.g. Germany exports to China, Australian exports to China
Geopolitical Events: Brexit, Political Crisis (Italy), Trade wars, Tariffs
Central Bank Expected Interventions: e.g. Front-running ECB Quantitative Easing programs for Italian Bonds
Emerging market Bonds: During rising global risk conditions, capital moves out of emerging market bonds into low-risk assets like US 10-year treasuries and German Bunds
Government infrastructure programs: New debt issuance to finance new projects lead to a fall in both short-term and long-term bonds.
Government Bonds and Credit Risk
The government bonds considered the low-risk investments and used for capital protection during recessions and downturns are the US 10-year Treasury note bond and the German 10-year bond.
The government bonds which considered high risk are the bonds of emerging market countries like Turkey and Hungary, and countries of southern Europe namely Spain, Italy, Portugal, and Greece.
Government Bonds and the factors affecting them
MacroVar monitors government bonds of 2-year, 5-year and 10-year maturities for the 25 biggest economies in the world.
Short-term government bonds (the 2-year government bond is the benchmark for short-term bonds) is driven by the market’s expectation of the central bank future moves. The long-term government bonds (the 10-year government bond is used as the benchmark of long-term bonds) is driven by the market’s expectations of inflation and economic growth.
Inflation Expectations
Inflation is the most critical factor affecting government bonds. A government bond’s coupon rate is fixed for the bond’s life. Hence during inflationary conditions, the price of government bonds tends to drop, because the bond may not be paying enough interest to stay ahead of inflation.
Long-term government bonds offer higher interest rates than short-term government bonds to account for the increased probability of inflation rising at some point during the bond’s life.
Financial health of Country
The financial health of the country issuing the government bonds affects the coupon rate the bond is issued with. Countries with low credit risk issue bonds with lower interest rates, while those countries with higher credit risk like some emerging market countries will have to offer higher rates to incentivize investors.
Government Bonds and the Economy
Real economic growth expectations and the inflation outlook of the global economy drive all financial assets. There are 4 economic environments based on economic growth and inflationary conditions.
Inflation boom: Accelerating Economic growth with Rising inflation
Stagflation: Slowing Economic Growth with Rising Inflation
Disinflation boom: Accelerating Economic growth with Slowing Inflation
Deflation Bust: Slowing Economic Growth with Falling Inflation
During an inflationary boom with strong economic growth and inflation, high yield bonds are well performing investment vehicles while government bonds are the worst performing financial assets.
During stagflation which is an economic environment of falling inflation and slowing economic growth government bonds are the best performing financial assets while high yield bonds are one fo the worst performing financial assets.
During disinflationary boom, with strong economic growth and falling inflation, government bonds are the best performing assets and high yield bonds are also good performing assets.
Deflationary busts are economic environments with falling economic growth and falling inflation. During this environment safe government bonds like US treasuries and German bunds are the best performing assets while high yield bonds are one of the worst performing assets.
Long-term government bonds are the best financial assets during periods of environments of deflation and disinflation. Government bonds are the worst financial assets during periods of inflationary booms with rising inflation and stagflation.
Bond Types versus the Economy
The following bond types outperform and underperform during different phases of the global economy.
bond types
Government Bonds and Market Risk
During global economic expansions when inflation expectations are positive, capital flows out of low-risk assets such as US treasuries and German bunds into higher risk financial assets such as stocks. Inside the bond market, during healthy economic conditions capital flows from safe German bunds to riskier bonds of the Eurozone periphery like Italian government bonds and Spanish government bonds and from low-risk US treasuries to other emerging market bonds in search of additional yield.
During economic slowdowns where the market expectation is disinflation funds flow from risky assets like emerging market bonds and stocks to low-risk financial assets like US treasuries and German bunds.
Government long-term bonds perform well during a weak economic environment with low inflation expectations and no economic growth expectations. Moreover, a global bond rally may indicate a rotation from risky assets like stocks to low risk assets like bonds.
Low economic growth can arise from a global slowdown affecting a specific economy, low commodity prices affecting commodity export oriented economies like Canada / Russia, geopolitical events affecting adversely economies like Brexit, a domestic economic slowdown, falling exports for export oriented economies like that of Germany, QE intervention or market front running of QE intervention.
Fiscal interventions like government infrastructure spending projects adversely affect government bonds (both short-term government bonds and long-term government bonds) since they sense increased projected inflation expectations.
Emerging countries are often vulnerable to capital outflows for various reasons. Capital outflows cause heavy losses in emerging countries government bonds. If you want to learn about emerging countries risks and opportunities click our guide on emerging economies.
MacroVar Price Dynamics Models
MacroVar uses quantitative models to monitor trends, momentum and possible inflection points for all bonds monitored. Our Models are open-source, transparent and MacroVar displays these signals in this dashboard and will alert you through MacroVar Newsfeed and Daily newsletter automatically when new signals are generated. You can also access raw data for each financial series including signals from these models by accessing MV database.
MacroVar index (MV)
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
Value currently 0 meaning that trend is flat.
Value is -25 meaning a strong -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum and long-term is currently present.
Value is -100 meaning a strong -ve momentum and long-term is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong +ve momentum and long-term is currently present.
Value is +100 meaning a strong +ve momentum and long-term is currently present.
Value is either +125 (when Momentum and Trend is +100) or -125 (when Momentum and Trend is -100) meaning that there is a moderate possibility of price reversal from the current trend.
Value is either +150 (when Momentum and Trend is +100) or -150 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Momentum Model (M)
Momentum trading is used to capture moves in shorter timeframes than trends. Momentum is the relative change occurring in markets. Relative change is different to a trend. A long-term trend can be up but the short-term momentum of a specific market can be 0.
If a market moves down and then moves up and then moves back down the net relative change in price is 0. That means momentum is 0. A short-term positive momentum, with a long-term downtrend results in markets with no momentum.
MacroVar momentum signal ranges from -100 to +100. The market trend signal is derived as the mean value from 4 calculations for each asset. The timeframes monitored are the following:
1 Day (1 trading day)
1 Week (5 trading days)
1 Month (20 trading days)
3 Months (60 trading days)
For each timeframe, the following calculations are performed:
Calculations of the return for the specific timeframe
If return calculated is higher than 0, signal value 1 else signal value -1
Finally, the 4 values are aggregated daily.
A technical rollover is identified when MacroVar momentum strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that momentum is flat.
Value is -25 meaning a weak -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum is currently present.
Value is -100 meaning a strong -ve momentum is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong -ve momentum is currently present.
Value is +100 meaning a strong -ve momentum is currently present.
MacroVar Trend model (T)
MacroVar Trend signal ranges from -100 to +100. The market trend signal is derived as the mean value from 8 calculations for each asset. The timeframes monitored are the following:
1-month (20 trading days)
3-months (60 trading days)
6-months (125 trading days)
1-year (250 trading days)
For each timeframe, the following calculations are performed:
Closing price vs moving average (MA): if price greater than MA value is +1, else -1
Moving average slope: if current MA is higher than previous MA, upward slope +1, else -1
MacroVar trend model can be used as a trend strength indicator. MacroVar trend strength values ranging between +75 and +100 or -75 and -100 show strong trend strength.
A technical rollover is identified when MacroVar trend strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that trend is flat.
Value is -25 meaning a weak -ve trend is currently present.
Value is -50 meaning a strong -ve trend is currently present.
Value is -75 meaning a strong -ve trend is currently present.
Value is -100 meaning a strong -ve trend is currently present.
Value is +25 meaning a strong +ve trend is currently present.
Value is +50 meaning a strong +ve trend is currently present.
Value is +75 meaning a strong -ve trend is currently present.
Value is +100 meaning a strong -ve trend is currently present.
MacroVar Bubble model (B)
MacroVar bubble model monitors a financial asset’s price relative to its 252-day moving average to identify possible inflection point. Extreme moves often followed by price reversals have a high probability of occuring when MacroVar bubble indicator is greater than 2.5 or less than -2.5.
The MacroVar bubble model is calculated using the formula: Latest Price – (252-day Moving Average) / (252-day Standard Deviation). It represents a z-score and extreme values are greater than 2.5 and less than -2.5. Other thresholds include -3, +3.
Value is higher than +2.5 or lower than -2.5 meaning that there is a moderate possibility of price reversal from the current trend.
Value is higher than +3 (when Momentum and Trend is +100) or -3 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Stocks Dynamics Models
MacroVar models analyze global stock markets by analyzing multiple macroeconomic and financial factors affecting a specific stock market.
Individual stock analysis is currently outside MacroVar’s scope. However, individual stocks are highly correlated to general stock market performance. Hence, investors should follow a top-down approach when structuring a stock portfolio by first analyzing Global macroeconomic and market dynamics and then focusing on specific sectors and stocks.
Checkout below analysis of how MacroVar models analyze Stock Markets. To get started, the window and select Stocks from the main menu of the dashboard page.
If you are new to stocks, click here for an introduction to stocks.
Top-Down Stock Analysis
MacroVar approach in analyzing stock markets starts from the global macroeconomic view, moving on to individual countries and then to individual sectors inside the stock markets.
The dynamics of each stock market is monitored in conjunction with the global market dynamics, and other markets.
MacroVar Stocks Factor Analysis
Stock Markets versus related markets
Macrovar models analyze in real-time the following relative factors which will be explained briefly in the next sections of this article.
Stocks versus Bond Markets
Stocks versus Credit Markets (CDS and corporate bonds)
Stocks versus Macroeconomic PMI & ESI Surveys
Stocks versus Credit Markets (CDS and corporate bonds)
Moreover, MacroVar monitors at least 200 factors specific to specific sectors. Some Examples are displayed below:
Commodity related Stock Sectors versus commodities (E.g. Energy ETF sector (XLE) versus crude oil price)
Banking related Stock Sectors vs Yield Curve dynamics (E.g. Bank ETF sector (KBE) vs US 2s10 Yield Curve)
Real estate stock sectors vs Macroeconomic Indicators (E.g. HomeBuilders ETF sector (ITB) vs Building Permits & 30-Year US Mortage Rates)
Stock Sectors versus Macroeconomic Surveys for specific sectors (Sources: Eurostat ESI, ZEW Institute, IFO)
Stock Seasonality
Other Factors MacroVar monitors closely are:
Style: Growth, Value, Momentum, Small Cap, low Volatility, High Dividend Yield
Size versus Value: Large-Cap Value vs Growth, Mid-Cap Value vs Growth, Small-Cap Value vs Growth
Stocks Price Dynamics??
Long / Short Stock Analysis
MacroVar models also analyze stock sectors from a long-short perspective. Long-short equity is an investing strategy seeks to minimize market exposure while profiting from stock gains in the long positions, along with price declines in the short positions.
MacroVar models can be used to generate long/short trading ideas by using related Long / Short analysis of Country Stock Indices, Sector Indices and Macroeconomic Reports like the ESI & ISM Manufacturing and Services PMI reports. Other methods to identify long/short ideas is to compare P/E across different sectors and individual stocks.
table with sections??
Stocks Versus Market Risk
Investors need to monitor Global Market risk before deciding whether to be long, short or market neutral in a specific stock market, sector and specific stock. Moreover, Global market risk is important in defining a portfolio’s gross and net exposure The sections below briefly analyze what MacroVar models monitor to gauge Risk related to the stock market. You can monitor Global market risk conditions in the Risk Management section.
Equity Risk
MacroVar models monitor the most important indicators to gauge risk implied stock market volatility across US & European markets. The volatility index (VIX) monitors the implied volatility of the S&P 500 while the VSTOXX tracks the implied volatility of Euro Stoxx 50 stock index.
During low-risk environments, VIX, VSTOXX are low and their respective VIX futures curve are in contango. However, other factors are closely monitored to identify periods of market complacency which are often followed by market corrections. You can monitor MacroVar Volatility models in detail in the Risk Management section.
Credit Risk
Stocks are closely correlated with corporate bonds. Bond investors are often more sophisticated than stock investors. As a result, corporate bonds performance often decouples from stocks which very often predicts a correction period for stocks.
MacroVar monitors an extensive series of Credit Default Swaps and Corporate Bond indices however the most important ones to monitor are the Markit CDX IG and HY indexes for the US, the ITRAXX IG and HY for Europe and the CDX EM for Emerging Markets.
During low-risk environments the indicators mentioned above are low. It is important to monitor the momentum of the CDS indices vs S&P 500 and the VIX components.
You can monitor MacroVar Credit models in detail in the Credit Markets and Stock Market Risk monitors and quantitative models.
Stocks versus Global & Country Economic Growth Dynamics
Manufacturing and Services PMI for all countries combined with ESI surveys for European countries only are surveys based on corporations’ expectations on how the economy is performing.
They are leading indicators of how the individual economies are performing and hence are closely correlated with stocks.
However, sometimes there is divergence between the performance of PMIs and Stock Markets, which often lead to Stock Market corrections or recoveries.
MacroVar models closely monitor the dynamics between stocks markets and these macroeconomic indicators to identify divergences. You can find these in the Stock Markets section.
MacroVar Price Dynamics Models
Stock Market Breadth
MacroVar analysis monitors global flows into stock markets as a whole. Hence, MacroVar monitors the Stock Market Breadth across the 35 biggest stock markets in the world as well Stock Market Breadth of the US Stock markets.
MacroVar index (MV)
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
Value currently 0 meaning that trend is flat.
Value is -25 meaning a strong -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum and long-term is currently present.
Value is -100 meaning a strong -ve momentum and long-term is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong +ve momentum and long-term is currently present.
Value is +100 meaning a strong +ve momentum and long-term is currently present.
Value is either +125 (when Momentum and Trend is +100) or -125 (when Momentum and Trend is -100) meaning that there is a moderate possibility of price reversal from the current trend.
Value is either +150 (when Momentum and Trend is +100) or -150 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Momentum Model (M)
Momentum trading is used to capture moves in shorter timeframes than trends. Momentum is the relative change occurring in markets. Relative change is different to a trend. A long-term trend can be up but the short-term momentum of a specific market can be 0.
If a market moves down and then moves up and then moves back down the net relative change in price is 0. That means momentum is 0. A short-term positive momentum, with a long-term downtrend results in markets with no momentum.
MacroVar momentum signal ranges from -100 to +100. The market trend signal is derived as the mean value from 4 calculations for each asset. The timeframes monitored are the following:
1 Day (1 trading day)
1 Week (5 trading days)
1 Month (20 trading days)
3 Months (60 trading days)
For each timeframe, the following calculations are performed:
Calculations of the return for the specific timeframe
If return calculated is higher than 0, signal value 1 else signal value -1
Finally, the 4 values are aggregated daily.
A technical rollover is identified when MacroVar momentum strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that momentum is flat.
Value is -25 meaning a weak -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum is currently present.
Value is -100 meaning a strong -ve momentum is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong -ve momentum is currently present.
Value is +100 meaning a strong -ve momentum is currently present.
MacroVar Trend model (T)
MacroVar Trend signal ranges from -100 to +100. The market trend signal is derived as the mean value from 8 calculations for each asset. The timeframes monitored are the following:
1-month (20 trading days)
3-months (60 trading days)
6-months (125 trading days)
1-year (250 trading days)
For each timeframe, the following calculations are performed:
Closing price vs moving average (MA): if price greater than MA value is +1, else -1
Moving average slope: if current MA is higher than previous MA, upward slope +1, else -1
MacroVar trend model can be used as a trend strength indicator. MacroVar trend strength values ranging between +75 and +100 or -75 and -100 show strong trend strength.
A technical rollover is identified when MacroVar trend strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that trend is flat.
Value is -25 meaning a weak -ve trend is currently present.
Value is -50 meaning a strong -ve trend is currently present.
Value is -75 meaning a strong -ve trend is currently present.
Value is -100 meaning a strong -ve trend is currently present.
Value is +25 meaning a strong +ve trend is currently present.
Value is +50 meaning a strong +ve trend is currently present.
Value is +75 meaning a strong -ve trend is currently present.
Value is +100 meaning a strong -ve trend is currently present.
MacroVar Bubble model (B)
MacroVar bubble model monitors a financial asset’s price relative to its 252-day moving average to identify possible inflection point. Extreme moves often followed by price reversals have a high probability of occuring when MacroVar bubble indicator is greater than 2.5 or less than -2.5.
The MacroVar bubble model is calculated using the formula: Latest Price – (252-day Moving Average) / (252-day Standard Deviation). It represents a z-score and extreme values are greater than 2.5 and less than -2.5. Other thresholds include -3, +3.
Value is higher than +2.5 or lower than -2.5 meaning that there is a moderate possibility of price reversal from the current trend.
Value is higher than +3 (when Momentum and Trend is +100) or -3 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
Momentum vs Trend
A trend can last for day(s), weeks and even months and doesn’t necessarily need momentum to continue moving. Trend is a sustained directional movement over a time. Momentum typically refers to the building of energy in a particular direction. For example, as part of an overall trend up, the market might be experiencing a lot of momentum to the upside, whereas the market may be in an overall trend up, but lacking any current momentum to push prices up and thus moving sideways but still in an uptrend. You can have a trend without momentum, and have momentum without a trend.
Stock Investing Strategies
Investing in stocks can take many forms, from value investing to event-driven trading to long/short strategies. Different trading strategies can be applied to different timeframes.
The most common form of investing in stocks is investing with a timeframe of 1-3 months during low volatility periods when it has been historically proven that stocks experience momentum.
Momentum investing is short-term investing, as traders are merely looking to capture part of the price movement in a trend. It involves long and short trading.
Value investing on the other hand, is long-term investing where traders are looking to buy undervalued stocks or assets in general in speculating that stocks will revert to their fair values.
Fundamental Analysis
Equity valuation depends on 2 variables:
Price / Earnings (P/E)
Stocks’ Forward earnings
Example: S&P 500 current level of 4,400 = Forward earnings ($200) x P/E Multiple (22)
Price-to-earnings ratio (P/E): The price-to-earnings is the price investors are willing to pay for each $1 of earnings.
Forward earnings: Forward earnings are analysts forecasted earnings on a single stock or index
P/E multiples vs Interest Rates: All financial markets compete for investors depending on their expected returns and risk. As a result, the level and dynamics of interest rates affects corporate bond rates which in turn affects the earnings yield investors are willing to accept for taking the stock risk and the final stock valuation.
Expected Equity Yield: (Terminal Forward Price (calculated as Forward Earnings x P/E multiple) minus current price) divided by current price and multiplied by (number of days to full forward earning earnings divided by 365)
Example: P/E Multiples versus Interest Rates
Assume current US corporate yields are at 2.25%. Investors would require buying stocks with an expected equity yield of 4% to compensate for the elevated risk of holding equities which are much riskier than corporate debt which is safer.
If long-term rates rise given stable expected earnings, bond yields will also rise and as a result investors will require a higher equity yield to buy stocks.
This will lead to either lower future valuations if multiples reduced or forward earnings need to be expected to grow to take up that slack to retain current valuations.
Monitoring the yield curve is critical to predict P/E multiple growth. Market corrections are correlated with yield curve steepening which means higher yields.
MacroVar models monitors the S&P 500 current valuation versus the different scenarios of P/E multiples and earnings per share based on interest rate dynamics and forward earnings new releases.
Check in the table above an example of the range of S&P 500 valuations based on different combinations of P/E multiples and earnings per share forecasts.
MacroVar Quantitative Models
MacroVar index (MV)
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
Value currently 0 meaning that trend is flat.
Value is -25 meaning a strong -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum and long-term is currently present.
Value is -100 meaning a strong -ve momentum and long-term is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong +ve momentum and long-term is currently present.
Value is +100 meaning a strong +ve momentum and long-term is currently present.
Value is either +125 (when Momentum and Trend is +100) or -125 (when Momentum and Trend is -100) meaning that there is a moderate possibility of price reversal from the current trend.
Value is either +150 (when Momentum and Trend is +100) or -150 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Momentum Model (M)
Momentum trading is used to capture moves in shorter timeframes than trends. Momentum is the relative change occurring in markets. Relative change is different to a trend. A long-term trend can be up but the short-term momentum of a specific market can be 0.
If a market moves down and then moves up and then moves back down the net relative change in price is 0. That means momentum is 0. A short-term positive momentum, with a long-term downtrend results in markets with no momentum.
MacroVar momentum signal ranges from -100 to +100. The market trend signal is derived as the mean value from 4 calculations for each asset. The timeframes monitored are the following:
1 Day (1 trading day)
1 Week (5 trading days)
1 Month (20 trading days)
3 Months (60 trading days)
For each timeframe, the following calculations are performed:
Calculations of the return for the specific timeframe
If return calculated is higher than 0, signal value 1 else signal value -1
Finally, the 4 values are aggregated daily.
A technical rollover is identified when MacroVar momentum strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that momentum is flat.
Value is -25 meaning a weak -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum is currently present.
Value is -100 meaning a strong -ve momentum is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong -ve momentum is currently present.
Value is +100 meaning a strong -ve momentum is currently present.
MacroVar Trend model (T)
MacroVar Trend signal ranges from -100 to +100. The market trend signal is derived as the mean value from 8 calculations for each asset. The timeframes monitored are the following:
1-month (20 trading days)
3-months (60 trading days)
6-months (125 trading days)
1-year (250 trading days)
For each timeframe, the following calculations are performed:
Closing price vs moving average (MA): if price greater than MA value is +1, else -1
Moving average slope: if current MA is higher than previous MA, upward slope +1, else -1
MacroVar trend model can be used as a trend strength indicator. MacroVar trend strength values ranging between +75 and +100 or -75 and -100 show strong trend strength.
A technical rollover is identified when MacroVar trend strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that trend is flat.
Value is -25 meaning a weak -ve trend is currently present.
Value is -50 meaning a strong -ve trend is currently present.
Value is -75 meaning a strong -ve trend is currently present.
Value is -100 meaning a strong -ve trend is currently present.
Value is +25 meaning a strong +ve trend is currently present.
Value is +50 meaning a strong +ve trend is currently present.
Value is +75 meaning a strong -ve trend is currently present.
Value is +100 meaning a strong -ve trend is currently present.
MacroVar Bubble model (B)
MacroVar bubble model monitors a financial asset’s price relative to its 252-day moving average to identify possible inflection point. Extreme moves often followed by price reversals have a high probability of occuring when MacroVar bubble indicator is greater than 2.5 or less than -2.5.
The MacroVar bubble model is calculated using the formula: Latest Price – (252-day Moving Average) / (252-day Standard Deviation). It represents a z-score and extreme values are greater than 2.5 and less than -2.5. Other thresholds include -3, +3.
Value is higher than +2.5 or lower than -2.5 meaning that there is a moderate possibility of price reversal from the current trend.
Value is higher than +3 (when Momentum and Trend is +100) or -3 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
Momentum vs Trend
A trend can last for day(s), weeks and even months and doesn’t necessarily need momentum to continue moving. Trend is a sustained directional movement over a time. Momentum typically refers to the building of energy in a particular direction. For example, as part of an overall trend up, the market might be experiencing a lot of momentum to the upside, whereas the market may be in an overall trend up, but lacking any current momentum to push prices up and thus moving sideways but still in an uptrend. You can have a trend without momentum, and have momentum without a trend.
Term Structures
MacroVar monitors the term structures of major financial assets used to gauge market expectations like VIX, VSTOXX, SOFR, SONIA, EURIBOR, 3-Month LIBOR, Fed Funds, Eurodollar futures.
The shape and dynamics of the implied curve is used for forecasting financial asset moves.
Implied Volatility
MacroVar monitors implied volatility and their curves for all major financial assets. The main reasons are that firstly asset volatility often is a leading indicator of a market’s performance and secondly risk is easier to forecast than return.
For example, US stock returns data from 1927 to 2018, the correlation in volatility from one month to the next is +69%.
Momentum Oscillator
The RSI provides technical traders with signals about bullish and bearish price momentum. RSI is an oscillator and it is used primarily in financial markets where there is a normal trending market.
In a normal behavioural oscillating down-trend an RSI of 50-60 of a financial market becomes “overbought” before resuming its downtrend while in an up-trend an RSI of 40-50 becomes already “oversold” before resuming uptrend.
The RSI creator explains how to use the RSI index: First move to overbought or oversold is a warning. The signal to pay attention is second move by oscillator to danger zone. If second move fails to confirm price move into new highs or new lows (forming double top or bottom on oscillator), divergence exists. If oscillator moves in opposite direction, breaking previous high or low, divergence or failure swing is confirmed.
Sentiment – COT
MacroVar analyses the commitment of traders (COT) report for many financial assets to identify potential overbought or oversold positioning by financial institutions and hedge funds.
The weekly COT report represents to what extend and whether financial institutions are long or short a specific financial asset.
MacroVar calculates the 5-year z-score and 5-year percentile for each financial asset for both large speculators (financial institutions and hedge funds) and commercials (producers).
MacroVar monitors closely extreme positions (<10% and >90% percentile) for turning points as well flip signals from L/S.
MacroVar Price Dynamics Models
MacroVar uses quantitative models to monitor trends, momentum and possible inflection points for all financial assets monitored. Our Models are open-source, transparent and MacroVar displays these signals in this dashboard and will alert you through MacroVar Newsfeed and Daily newsletter automatically when new signals are generated. You can also access raw data for each financial series including signals from these models by accessing MV database.
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
The MacroVar index is a synthetic variable derived by a combination of the Momentum, Trend and Bubble models described below. It ranges between -150 and +150. MacroVar displays signals schematically as follows:
Value currently 0 meaning that trend is flat.
Value is -25 meaning a strong -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum and long-term is currently present.
Value is -100 meaning a strong -ve momentum and long-term is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong +ve momentum and long-term is currently present.
Value is +100 meaning a strong +ve momentum and long-term is currently present.
Value is either +125 (when Momentum and Trend is +100) or -125 (when Momentum and Trend is -100) meaning that there is a moderate possibility of price reversal from the current trend.
Value is either +150 (when Momentum and Trend is +100) or -150 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
MacroVar Momentum Model (M)
Momentum trading is used to capture moves in shorter timeframes than trends. Momentum is the relative change occurring in markets. Relative change is different to a trend. A long-term trend can be up but the short-term momentum of a specific market can be 0.
If a market moves down and then moves up and then moves back down the net relative change in price is 0. That means momentum is 0. A short-term positive momentum, with a long-term downtrend results in markets with no momentum.
MacroVar momentum signal ranges from -100 to +100. The market trend signal is derived as the mean value from 4 calculations for each asset. The timeframes monitored are the following:
1 Day (1 trading day)
1 Week (5 trading days)
1 Month (20 trading days)
3 Months (60 trading days)
For each timeframe, the following calculations are performed:
Calculations of the return for the specific timeframe
If return calculated is higher than 0, signal value 1 else signal value -1
Finally, the 4 values are aggregated daily.
A technical rollover is identified when MacroVar momentum strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that momentum is flat.
Value is -25 meaning a weak -ve momentum is currently present.
Value is -50 meaning a strong -ve momentum is currently present.
Value is -75 meaning a strong -ve momentum is currently present.
Value is -100 meaning a strong -ve momentum is currently present.
Value is +25 meaning a strong +ve momentum is currently present.
Value is +50 meaning a strong +ve momentum is currently present.
Value is +75 meaning a strong -ve momentum is currently present.
Value is +100 meaning a strong -ve momentum is currently present.
MacroVar Trend model (T)
MacroVar Trend signal ranges from -100 to +100. The market trend signal is derived as the mean value from 8 calculations for each asset. The timeframes monitored are the following:
1-month (20 trading days)
3-months (60 trading days)
6-months (125 trading days)
1-year (250 trading days)
For each timeframe, the following calculations are performed:
Closing price vs moving average (MA): if price greater than MA value is +1, else -1
Moving average slope: if current MA is higher than previous MA, upward slope +1, else -1
MacroVar trend model can be used as a trend strength indicator. MacroVar trend strength values ranging between +75 and +100 or -75 and -100 show strong trend strength.
A technical rollover is identified when MacroVar trend strength indicator moves from positive to negative value or vice-versa.
Value currently 0 meaning that trend is flat.
Value is -25 meaning a weak -ve trend is currently present.
Value is -50 meaning a strong -ve trend is currently present.
Value is -75 meaning a strong -ve trend is currently present.
Value is -100 meaning a strong -ve trend is currently present.
Value is +25 meaning a strong +ve trend is currently present.
Value is +50 meaning a strong +ve trend is currently present.
Value is +75 meaning a strong -ve trend is currently present.
Value is +100 meaning a strong -ve trend is currently present.
MacroVar Bubble model (B)
MacroVar bubble model monitors a financial asset’s price relative to its 252-day moving average to identify possible inflection point. Extreme moves often followed by price reversals have a high probability of occuring when MacroVar bubble indicator is greater than 2.5 or less than -2.5.
The MacroVar bubble model is calculated using the formula: Latest Price – (252-day Moving Average) / (252-day Standard Deviation). It represents a z-score and extreme values are greater than 2.5 and less than -2.5. Other thresholds include -3, +3.
Value is higher than +2.5 or lower than -2.5 meaning that there is a moderate possibility of price reversal from the current trend.
Value is higher than +3 (when Momentum and Trend is +100) or -3 (when Momentum and Trend is -100) meaning that there is a very high probability of price reversal from the current trend.
Momentum vs Trend
A trend can last for day(s), weeks and even months and doesn’t necessarily need momentum to continue moving. Trend is a sustained directional movement over a time. Momentum typically refers to the building of energy in a particular direction. For example, as part of an overall trend up, the market might be experiencing a lot of momentum to the upside, whereas the market may be in an overall trend up, but lacking any current momentum to push prices up and thus moving sideways but still in an uptrend. You can have a trend without momentum, and have momentum without a trend.
MacroVar Global Macroeconomic Analysis
MacroVar analyzes more than 10,000+ macroeconomic indicators of the largest 35 countries in the world. You can use MacroVar Newsfeed to get real-time updated on the latest Macroeconomic releases. Moreover, you can personalize your feed to select for which countries you want to get notified.
Checkout below details on how MacroVar models analyze Global Macroeconomic Conditions. To get started, the window and select Economies from the main menu.
Top-down Analysis of Global Macroeconomic factors
MacroVar top-down approach of macroeconomic conditions seeks to focus first on analyzing the most important leading macroeconomic indicators which are predictive of economic growth and inflation 3-12 months in advanced. These leading indicators drive the global economy which in turn drive all financial markets.
Moreover, MacroVar statistical models compare financial markets momentum with the momentum of these indicators to identify potential investment themes arising from divergences or new trend formations. Click here to see how Macroeconomic indicators as used as factors in MacroVar models.
The major components of MacroVar Global Macro top-down approach are the following:
Economic Growth Dynamics
Inflation Outlook
Liquidity Conditions
Global Economic Growth Dynamics
The most important factor to monitor is global economic growth trends and momentum. Individual country economic growth expectations are gauged using principally each country’s Manufacturing PMI and other business and consumer confidence indicators. Global growth is gauged by calculating MacroVar Global PMI based on each country’s weighting to Global GDP of the 35 largest economies monitored and Manufacturing PMI. Special attention is given to the top four largest economies (United States, Eurozone, China, Japan) comprising more than 50% of global GDP. We also monitor divergences between developed and emerging economies. Lastly, global macroeconomic growth breadth is monitored. MacroVar uses the following indicators to analyze Macroeconomic trends.
The Global Economy section presents the current global macroeconomic conditions using different statistics. The largest four economies in the world closely monitored are the US, Eurozone, China and Japan economies comprising more than 50% of Global GDP. MacroVar also monitors the relative performance of Developed and Emerging economies.
Global Inflation Outlook
MacroVar monitors the CPI Y/Y rates for the largest 35 economies in the world, segmented by region and developed vs emerging economies.
Since CPI Y/Y is a coincident economic indicator, the following leading indicators which often predict the future inflation outlook are used as well:
US: ISM Manufacturing Prices
Eurozone, Europe and Individual European Countries: ESI Retail Prices
China: Official Manufacturing PMI prices
Global Liquidity Conditions
Global liquidity is a major factor affecting all financial markets. It is of paramount importance to monitor Global Liquidity of the four major central banks in the world namely the Federal Reserve (US), ECB (Eurozone), PBoC (China) and BOJ (China).
MacroVar monitors central banks actions by closely monitoring published statistics and news flow.
The Central Banks section presents quantitative data and news flow for the four major central banks and secondarily to the rest of the 31 countries monitored.
MacroVar Growth/Inflation model
MacroVar models analyze the relationship between economic growth and inflation by using the MV Growth/Inflation model. Leading indicators primarily based on Manufacturing PMI / ESI and the respective price indexes are used to present an outlook of what to expect in the next 3-12 months. Moreover, financial assets expected risk/returns are calculated based on the dynamics of the Growth/inflation model.
Click here to check the theory behind this MV Growth/Inflation model.
Macroeconomic Factors
MacroVar monitors various macroeconomic and financial factors affecting each financial market. A brief list is provided below. From click on a specific financial market in the World Markets or Sectors sections of MacroVar to examine the related factors.
Global Manufacturing PMI vs Global Stock Market, US Dollar, Emerging Markets, US 10 year treasury
Global Manufacturing PMI vs Cyclical Commodities (Metals, Energy, Shipping)
Country Stock Market vs Yield Curve, Manufacturing PMI, 10-year Bond, ZEW
Country Bonds vs Manufacturing PMI, ESI, Inflation, ZEW, Inflation Expectations (ISM, ESI)
Country Currency vs 10-year Bond, Stock Market, Central Bank B/S, 10-Year bond yield differential, 2-year bond yield differential, Manufacturing PMI, ZEW
Country ETF vs Manufacturing PMI, ESI, Country Currency, 10-year Bond, CDS, ESI
US & EU Stock Market vs Credit Index (YoY) – Index and Sector Analysis
Construction ETF vs Building Permits
Bank Sector ETF vs Yield Curve
ISM Manufacturing Prices vs US 10-year Bond yield
Our Global Macroeconomic models are open-source and MacroVar displays these signals in the Ecoonomies section of the dashboard and will alert you through MacroVar Newsfeed and Daily newsletter automatically when new signals are generated. You can also access process these signals further and combine them with your research by downloading them from the MacroVar database using Excel, Python API or the Web.
Every financial market is linked (correlated) with economic growth expectations and other related markets.
Hence, analyzing a financial market requires monitoring the asset’s price dynamics (trend & momentum) and how the financial market reacts against economic indicators affecting it and other related markets.
For example, a specific stock is affected by the company’s fundamentals, it’s sector performance which in turn depends on the country and world economic growth. Moreover, the stock price must be analyzed in combination with the company’s bond price since both markets are closely linked and often a divergence between them may signal an trading opportunity.
MacroVar monitors various macroeconomic and financial factors affecting each financial market. A brief list is provided below. From click on a specific financial market in the World Markets or Sectors sections of MacroVar to examine the related factors.
Global Manufacturing PMI vs Global Stock Market, US Dollar, Emerging Markets, US 10 year treasury
Emerging Markets vs US 10 year treasury, US Dollar
Global Manufacturing PMI vs Cyclical Commodities (Metals, Energy, Shipping)
Country Stock Market vs Yield Curve, Manufacturing PMI, 10-year Bond, ZEW
Country Bonds vs Manufacturing PMI, ESI, Inflation, ZEW, Inflation Expectations (ISM, ESI)
Country Currency vs 10-year Bond, Stock Market, Central Bank B/S, 10-Year bond yield differential, 2-year bond yield differential, Manufacturing PMI, ZEW
Country ETF vs Manufacturing PMI, ESI, Country Currency, 10-year Bond, CDS, ESI
US & EU Stock Market vs Credit Index (YoY) – Index and Sector Analysis
Commodity related currencies vs Metals, Energy
Gold vs Bonds
Construction ETF vs Building Permits
Commodities ETF vs Commodity Futures
Bank Sector ETF vs Yield Curve
Equity vs Credit Volatility Indices
Every financial market is linked (correlated) with economic growth expectations and other related markets.
Hence, analyzing a financial market requires monitoring the asset’s price dynamics (trend & momentum) and how the financial market reacts against economic indicators affecting it and other related markets.
For example, a specific stock is affected by the company’s fundamentals, it’s sector performance which in turn depends on the country and world economic growth. Moreover, the stock price must be analyzed in combination with the company’s bond price since both markets are closely linked and often a divergence between them may signal an trading opportunity.
MacroVar monitors various macroeconomic and financial factors affecting each financial market. A brief list is provided below. From click on a specific financial market in the World Markets or Sectors sections of MacroVar to examine the related factors.
Global Manufacturing PMI vs Global Stock Market, US Dollar, Emerging Markets, US 10 year treasury
Emerging Markets vs US 10 year treasury, US Dollar
Global Manufacturing PMI vs Cyclical Commodities (Metals, Energy, Shipping)
Country Stock Market vs Yield Curve, Manufacturing PMI, 10-year Bond, ZEW
Country Bonds vs Manufacturing PMI, ESI, Inflation, ZEW, Inflation Expectations (ISM, ESI)
Country Currency vs 10-year Bond, Stock Market, Central Bank B/S, 10-Year bond yield differential, 2-year bond yield differential, Manufacturing PMI, ZEW
Country ETF vs Manufacturing PMI, ESI, Country Currency, 10-year Bond, CDS, ESI
US & EU Stock Market vs Credit Index (YoY) – Index and Sector Analysis
Commodity related currencies vs Metals, Energy
Gold vs Bonds
Construction ETF vs Building Permits
Commodities ETF vs Commodity Futures
Bank Sector ETF vs Yield Curve
Equity vs Credit Volatility Indices
Every financial market is linked (correlated) with economic growth expectations and other related markets.
Hence, analyzing a financial market requires monitoring the asset’s price dynamics (trend & momentum) and how the financial market reacts against economic indicators affecting it and other related markets.
For example, a specific stock is affected by the company’s fundamentals, it’s sector performance which in turn depends on the country and world economic growth. Moreover, the stock price must be analyzed in combination with the company’s bond price since both markets are closely linked and often a divergence between them may signal an trading opportunity.
MacroVar monitors various macroeconomic and financial factors affecting each financial market. A brief list is provided below. From click on a specific financial market in the World Markets or Sectors sections of MacroVar to examine the related factors.
Global Manufacturing PMI vs Global Stock Market, US Dollar, Emerging Markets, US 10 year treasury
Emerging Markets vs US 10 year treasury, US Dollar
Global Manufacturing PMI vs Cyclical Commodities (Metals, Energy, Shipping)
Country Stock Market vs Yield Curve, Manufacturing PMI, 10-year Bond, ZEW
Country Bonds vs Manufacturing PMI, ESI, Inflation, ZEW, Inflation Expectations (ISM, ESI)
Country Currency vs 10-year Bond, Stock Market, Central Bank B/S, 10-Year bond yield differential, 2-year bond yield differential, Manufacturing PMI, ZEW
Country ETF vs Manufacturing PMI, ESI, Country Currency, 10-year Bond, CDS, ESI
US & EU Stock Market vs Credit Index (YoY) – Index and Sector Analysis
Commodity related currencies vs Metals, Energy
Gold vs Bonds
Construction ETF vs Building Permits
Commodities ETF vs Commodity Futures
Bank Sector ETF vs Yield Curve
Equity vs Credit Volatility Indices
MacroVar analyzes financial markets and economies using a top down approach. MacroVar’s aim is to monitor markets and economies in order to predict the performance of every sector under investigation in the next 6-12 months.
The most important factors which affect economic conditions and financial markets are:
Global economic growth expectations
Global Inflation outlook
Global Liquidity conditions
Global Risk environment
Financial Markets
Global Economic Growth Expectations
Global economic growth is the most important factor affecting individual economies, sectors, industries, and all financial assets (stocks, bonds, currencies, and commodities).
The most important indicator to monitor Global growth is MacroVarGlobal PMI which is a weighted average of Manufacturing PMI of the 35 largest economies.
PMI is a leading economic indicator published for each country monthly derived from surveys of private sector companies. The PMI summarizes whether market conditions are expanding, staying the same, or contracting as viewed by managers of the companies surveyed. PMI provides information about current and future business conditions.
Special attention is given to the top four largest economies (United States, Eurozone, China, Japan) comprising more than 50% of global GDP.
Interpreting Global PMI: Readings above 50 indicator economic expansion, while readings below 50 indicate economic contraction.
Global Liquidity
Global liquidity is the availability of credit in global financial markets. Global liquidity is controlled by central banks using various instruments to inject or remove money from the system. An expansion of global liquidity leads to debt growth which is favorable for financial assets and economic growth and vice versa.
Global Liquidity Snapshot: Global Liquidity is gauged by monitoring the 1. Level of interest rates, 2. balance sheet and 3. Money Supply M2 of the four major central banks of the world namely Federal Reserve (US), ECB (Eurozone), PBoC (China) and BOJ (China).
Country View
Country Economic, Financial & Risk Snapshot
To get a snapshot of your country’s economic health, the most important macroeconomic and financial indicators are the country’s 1. Manufacturing and Services PMI and 2. The performance of the stock market, bonds and currency.
A country’s full macroeconomic analysis involved the indicators below.
Get a snapshot of a country’s economy using:
Economic Growth variables
United States: use ISM Manufacturing New Orders
Europe: use ESI Manufacturing New Orders
Other Countries: use Manufacturing, Services and Composite PMI
Inflation variables
United States: use ISM Manufacturing prices
Europe: use ESI Manufacturing Prices
Other Countries: CPI & PPI
To further analyze a country’s macroeconomy, the following parameters must be closely monitored:
Business Confidence: UMSCI, Manufacturing PMI, Services PMI, Construction PMI, Permits, Employment (ESR), ESI, Consumer Confidence, Real Estate Index
Inflation Conditions: Leading: ISM Prices, ESI Prices – Coincident: CPI, CPI Core, PPI, PPI
Trade: CA (BOP): Trade surplus = exports > imports, FX demand
Fiscal Policy:
Current Surplus/Deficit: rising deficit, injection > inflationary > debt rising
Debt/GDP: growth dependent on public spending, rising Debt/GDP (more spending injections) > must keep rates low / raise MS (interest bill kept low), else default or deflate (not desirable)
Interest bill: interest bill % GDP
Liquidity Cover: government ability to pay its interest bill (tax revenues # Interest bill)
Monetary Policy:
MP1: M2, Interest rates, Reserve Requirement
MP2: Central Bank Balance sheet
News flow: Politics
Four Macroeconomic Environments versus financial markets
There are four macroeconomic environments based on economic growth and inflationary conditions. MacroVar uses this model to monitor macroeconomic conditions for the largest 35 countries in the world.
Inflation boom: Accelerating Economic growth with rising inflation
During these macroeconomic conditions economic growth is strong, capacity utilization is high and hence rising inflation is experienced. Policy makers use monetary policy and fiscal policy tools to slowdown the economy and bring inflation down.
High global growth with rising inflation expectations lifts commodities. Many emerging economies growth is linked to commodities. When commodities rise emerging market stocks, currencies and real estate rise as well.
During this environment, global growth is strong and global risk is low. Capital flows out of safe developed low growth countries like the US into emerging markets.
The best performing financial assets are emerging market stocks, international real estate, emerging countries’ currencies, commodities, and IL bonds (inflation linked bonds).
The worst performing financial assets are US treasury bonds and cash since they are adversely affected by rising inflation.
Stagflation: Slowing Economic Growth with Rising Inflation
Click to check the Best & Worst Assets during Stagflation
The best asset performers protecting investors from inflation are Gold, Cash, Treasury Inflation Protected Securities, and the US Dollar.
The worst performers are long-duration treasury bonds adversely affected by rising inflation.
Disinflation boom: Accelerating Economic growth with Slowing Inflation
The best performers are developed markets stocks, developed Real estate and US Treasury bonds.
Low inflation with moderate growth is a good environment for bonds and stocks and bad for the worst performs which are commodities and commodity related sectors.
Deflation Bust: Slowing Economic Growth with Falling Inflation
During this environment the best asset performers are Long-Duration Treasuries and Cash. Everything else experiences big volatility and often large losses.
MacroVar risk management model overview
Successful investing requires managing a portfolio of assets to protect the capital of investors and generate steady returns in both rising and falling markets. This requires investing in growth assets (stocks, commodities, currencies) when global financial risk is low while shifting the portfolio to safe investments (bonds, cash) or neutralizing a portfolio’s market risk when financial risk exceeds certain levels.
Risk management analysis
Financial markets and the real economy have historically experienced a series of severe crises. During these financial crisis, catastrophic investment and economic losses where experienced. It is critical for any investment or business strategy to understand financial risk conditions and adapt strategies based on these conditions.
Analyzing the Global Economy and Financial risk
The global economy and financial markets experience long-term growth. When financial risk is low, financial markets operate smoothly providing ample liquidity to financial markets and the economy. During these periods high growth assets like stocks experience high returns and are priced efficiently based on their fundamental drivers. On the contrary, when financial risk is rising, market liquidity deteriorates because of a loss of confidence in banks, funding institutions or governments which causes a feedback loop of surging funding costs, increased price volatility and asset fire sales.
MacroVar risk management model overview
MacroVar risk management is a quantitative model which monitors critical financial markets and warns investors when financial risk is rising quickly. The risk management model monitors stocks, bonds, credit markets, currencies and global liquidity daily. MacroVar risk management model is comprised of the following segments:
Stock Risk monitor: Stock risk is monitored by analyzing the implied volatility and shape of the term sturcture of the S&P 500 and Eurostoxx 50 stock markets.
Credit Risk monitor: Credit risk is monitored by analyzing the credit default swaps indices of the United States and European markets.
Bond Risk: Bond risk is monitored by analyzing the implied volatility of the US treasury market.
Emerging markets risk: Emerging markets risk is monitored by analyzing the credit default swaps of government bonds for major emerging countries.
Liquidity risk: Liquidity risk is monitored by analyzing the LIBOR-OIS spread.
Currency risk: Currency risk is monitored by analyzing the implied volatility of low-risk currencies and gold.
Banking risk: US, European and UK banks credibility plays an important role in monitoring global liquidity risk. When Banks risk is rising, global market liquidity risk is rising and therefore global financial risk is rising. MacroVar monitors Global Bank risk by monitoring credit default swaps levels of the following major global systemic banks.
Sovereign risk: Sovereign credit risk plays an important in gauging global financial risk. MacroVar monitors Sovereign Risk by monitoring Credit Default Swaps Levels for the following developed countries
Learn more in the respective section of MacroVar Risk Management model section.
Monitor global financial markets and economies using MacroVar financial data analytics. Get access by creating your free account using your Email, Google or Facebook.
MacroVar Free Database provides historical data for Financial and Macroeconomic Variables. Get access by creating your free account using your Email, Google or Facebook.
MacroVar Investing & Trading Guide
This guide was created by MacroVar’s team of professional fund managers and economists to enable you understand the principles of trading and investing.
Macrovar uses a top down framework to analyse markets and economies and multi-factor models to identify trading opportunities across 1,400 financial assets.
Top-Down Analysis of Markets & Economies
Fund managers use a top down framework to analyze the major components driving the global economy which in turn drive all financial markets.
The major factors monitored and analysed are:
Global Economic Growth Expectations
The most important factor to predict from a fundamental point is view is global economic growth trend for the next one to three months. This is accomplished by monitoring leading macroeconomic indicators for each country like manufacturing, services PMI and other business and consumer confidence indicators. Global economic growth is monitored by calculating MacroVar Global PMI based on each country’s manufacturing PMI and it’s relative weight to Global GDP of the 35 largest economies. Special attention is given to the top four largest economies (United States, Eurozone, China, Japan) comprising more than 50% of global GDP. Global macroeconomic growth breadth is monitored. The trend and momentum for each macroeconomic indicator is calculated using the following metrics.
Check the major macroeconomic indicators of the largest 35 economies in the world in MacroVar’s Global Economy section.
Global Liquidity conditions
Global liquidity is a major factor affecting all financial markets. The most important liquidity factors are related to the four largest central banks in the world namely the Federal Reserve (US), ECB (Eurozone), PBoC (China) and BOJ (China). MacroVar monitors each central bank’s interest rates, Money Supply (M2) and Balance Sheet dynamics on a year to year basis.
Global Financial Risk levels
Global financial risk conditions are especially important since they affect all financial assets. MacroVar risk index is composed of various financial risk factors to provide an overview of global market risk conditions. The risk index is used for adjusting portfolio risk. MacroVar risk management provides free current risk analysis.
Global Financial Markets Overview
MacroVar uses a top down framework to analyse financial markets as well. The major financial markets which affect the rest of the other financial assets are: Stocks
Global Stocks: MSCI All Country World Index
US Stocks: S&P 500 Index
European Stocks: Eurostoxx 600 Index
Bonds
US 10-year Treasury
German 10-year Bund
US Short-Term Yield Curve (2s5s)
US Long-Term Yield Curve (2s10s)
Currencies
US Dollar: DXY Index
Risk Off Currencies: USDJPY, USDCHF
Emerging Market Currencies: CEW Index
Commodities
Crude Oil
Copper
Gold
Equity Risk
US Stock implied volatility: VIX Index, VIX term structure
EU Stock implied volatility: VSTOXX Index, VSTOXX term structure
Emerging Markets Stock implied volatility: VXEEM Index
Credit Risk
US Corporate risk: CDX IG, CDX HY
EU Corporate risk: ITRAXX EU
Emerging Corporate risk: CDX EEM
Global Macroeconomic Overview
Global Manufacturing PMI
Global Services PMI
Developed Economies Manufacturing PMI
Emerging Economies Manufacturing PMI
How Financial Markets Work
The basic logic on how financial assets behaves during different economic conditions is provided below. There are periods where correlations between financial assets breakdown and where economic data are disconnected from financial markets but the core market logic is described below.
There are two market environments: Risk On periods during which funds flow from safe assets to risky assets and Risk Off periods where funds flow from risky assets to low-risk assets. Risk Assets (Risk-On): Stocks, Cyclical Commodities, Cyclical Sectors / Industries, High Yield Bonds, Cyclical Currencies, Emerging Markets (Capital flows to emerging markets in search for higher yields, higher growth rates and hence profits) Safe Assets (Risk-Off): US Treasuries, German Bunds, Defensive Sectors / Industries, US Dollar DXY, Swiss Franc, Japanese Yen, Gold
The most important asset correlation is between the US stocks and US Bonds. During risk on periods US stocks rise while US bonds are sold and vice-versa. Since equities are closely linked with credit, MacroVar monitors closely the performance of corporate bonds for each sector in US and EU markets.
During Risk on Periods the markets behave as follows: Global Risk
Equity Risk: US VIX & Europe VSTOXX falling
Credit Risk: US CDX IG, Europe ITRAXX IG, US BofA High Yield credit spreads falling
Volatility Term Structures: US VIX & Europe VSTOXX term structures in steep Contango
MacroVar Risk index: falling
Stocks
Global Stocks: rising (ideally this should occur with global bond market weakness)
US Stocks Breadth: rising
Global Stock Breadth: rising
Emerging Market Stocks: rising (often outperforming developed markets like US & EU)
Stock Sectors
Cyclical vs Defensive sectors: Cyclical sectors outperform Defensive sectors
Sector Breadth rising
Bonds (MacroVar monitors 2-year, 5-year and 10-year bonds)
Low Risk Bonds: US Treasuries & German Bunds falling (yields rising)
High Risk Bonds: US High Yield Bonds, Europe Club Med Bonds, Emerging Market bonds rising (yields falling)
Bond interest rates breadth: Rising – Funds move out of bonds into stocks hence yield rates rise
Yield Curve dynamics
Yield Curve: Bear steepening (on the contrary a Yield Curve bull re-steepening signifies Risk Off environment)
Global Yield Curve Steepening breadth: rising
Fed Funds futures: steep Contango
Eurodollar futures: Rising
Currencies
US Dollar (DXY): Rising
Low Risk Currencies (JPY, CHF): Falling
High Risk Currencies (AUD, NZD, CAD): Rising
Currencies Breadth (vs the US Dollar): Rising
Commodities
Energy (Crude Oil): Rising
Metals (Copper): Rising
Low Risk Commodities (Gold): Falling
Cyclical Commodities : Rising
Macroeconomic Conditions
Global Manufacturing & Services trend and momentum: Rising
Global Manufacturing & Services breadth trend and momentum: Rising
Factors of a specific financial asset
Financial assets like stocks, bonds, currencies and commodities are linked with other
related financial markets. MacroVar monitors a broad list of macroeconomic and financial factors affecting every financial market. Check a representative list of factors monitored below:
Global Manufacturing PMI vs Global Stock Index, US Dollar, Emerging Markets, US 10-year treasury
Stocks markets, sectors and industries versus their respective credit indices
A specific country’s stock market vs its yield curve, Manufacturing & Services PMI, 10-year bond, Yield Curve
Commodity Futures vs Commodities ETF
Country Macroeconomic Overview
MacroVar analyses the economic and financial conditions of the largest 35 economies in the world by monitoring 40 economic and financial indicators for each country. Economic Aim
A nation’s economy is healthy when it experiences stable economic growth with low inflation and low unemployment. Economic growth is measured by Real GDP and inflation by CPI, PPI. An economy is affected by its individual performance and its economic performance relative to the rest of the World (RoW).
Policymakers (government & central bank) use fiscal and monetary policy to inject liquidity (print & spend money) during slowdowns (to solve weak economic growth) and withdraw liquidity (buy back money & stop spending money) from an overheating economy (to solve high inflation).
Excessive intervention in the economy may lead to loss of confidence in the country and a financial crisis. The degree of intervention depends on the country’s fundamentals. Read how to analyze a country’s economic in depth. The four economic environments
Financial markets are affected by economic growth and inflation expectations. The performance of each financial asset for each economic environment is explained below.
The four economic environments:
Inflation boom: Accelerating Economic growth with Rising inflation
Stagflation: Slowing Economic Growth with Rising Inflation
Disinflation boom: Accelerating Economic growth with Slowing Inflation
Deflation Bust: Slowing Economic Growth with Falling Inflation
MacroVar uses leading economic indicators for each country to predict economic and inflation expectations. More specifically for each country the Price Expectations and New Orders expectations components of the PMI, ISM and ESI indicators are used for structuring the models.
Country Macroeconomic Analysis
This analysis is based on the work of Ray Dalio and more specifically how the economic machine works.
Introduction: An economy is the sum of the transactions that make it up. A country’s economy is comprised of the public and private sector. The private sector is comprised of businesses and consumers.
Economic activity is driven by 1. Productivity growth (GDP growth 2% per year due knowledge increase), 2. the Long-term debt cycle (50-75 years), 3. the business cycle (5-8 years). Credit (promise to pay) is driven by the debt cycle. If credit is used to purchase productive resources, it helps economic growth and income. If credit is used for consumption it has no added value
Money and Credit: Economic transactions are filled with either money or credit (promise to pay). The availability of credit is determined by the country’s central bank. Credit used to purchase productive resources generating sufficient income to service the debt, helps economic growth and income.
Country versus Rest of the World: A country’s finances consist of a simple income statement (revenue–expenses) and a balance sheet (assets–liabilities). Exports are imports are the main revenue and expense for countries. Uncompetitive economies have negative net income (imports higher than exports), which is financed by either savings (FX & Gold reserves) or rising debt (owed to exporters).
Debt: A nation’s debt is categorized as local currency debt and FX debt. Local debt is manageable since a country’s central bank can print money and repay it. FX debt is controlled by foreign central banks hence it is difficult to be repaid. For example. Turkey has US dollar denominated debt. Only the US central bank (the Federal Reserve), can print US dollars hence FX debt is out of Turkey’s control.
A country can control its debt by either: 1. Inflate it away, 2. Restructure, 3. Default. The US aims to keep nominal GDP growth above interest rates (kept low) to gradually reduce its debt.
Injections & Withdrawals
The government and central bank use fiscal and monetary policies to inject liquidity during slowdowns to boost growth and withdraw liquidity from an overheating economy to control rising inflation. The available policies and tools used during recessions are the following:
Monetary Policies (MP)
Reduce short-term interest rates > Boost Economic growth by 1. Raising Credit, Easing Debt service
Print money > purchase financial assets > force investors to take more risk & create wealth effect
Print Money > purchase new debt issued to finance Gov. deficits when no local or foreign investors
Fiscal Policies (FP)
Expansionary FP is when government spends more than tax received to boost economic growth. This is financed by issuing new debt financed by 1. domestic or foreign investors or 2. CB money printing
Currency vs Injections & Withdrawals and inflation
The degree of economic intervention depends on the country’s economic fundamentals, its currency status and credibility. Countries with reserve currencies or strong fundamentals are allowed by markets to intervene. However, when nations with weak economic fundamentals intervene heavily, confidence is lost, causing a capital flight out of the country, spiking inflation and interest rates which lead to a severe recession, political and social crisis.
Reserve vs Non-reserve currencies: Reserve currencies are used by countries and corporations to borrow funds, store wealth and for international transactions (buy commodities). They are considered low risk. The US dollar is the world’s largest reserve currency. The main advantage of reserve currency nations is their ability to borrow (issue debt) on their own currency. These countries have increased power to conduct monetary and fiscal policies to boost their economies. However, prolonged expansionary fiscal and monetary policies eventually lead to loss of confidence in these currencies as a store of value and potential inflationary crisis.
Non-reserve currency countries: Conversely, developing nations are not considered low risk hence their ability to borrow in their own currencies is limited. Their economic growth is dependent on foreign capital inflows denominated in foreign currencies like the US dollar. During periods of global economic growth, capital flows from developed markets into developing nations looking for higher returns. These economies and their corporations’ issue foreign debt to grow. However, during periods of weak global economic growth or financial stress, foreign capital flows (also called capital flight) back to developed countries causing an inability of countries and companies to repay their debt. Central banks gather foreign exchange reserves during growth periods to create a cushion against capital outflows.
A nation’s economy is vulnerable to economic weakness or financial stress when it experiences:
Current account deficit: a current account deficit indicates an uncompetitive economy which relies on foreign capital to sustain its spending. Hence, is vulnerable to capital outflows
Government deficit: a big government deficit indicates an economy relying or rising debt to finance its operations
Debt/GDP: a high Debt/GDP pushes a nation to borrow large amounts to finance its debt, print money or default. Historically, Debt/GDP higher than 100% is a red warning for economies.
Low or no foreign exchange reserves: Developing economies are vulnerable to capital flight since foreign exchange reserves provide a cushion against capital outflows
High external debt: Nations are vulnerable to high external debts which may be caused by a sudden depreciation of their currency or rising foreign interest rates (due to foreign growth)
Negative real interest rates: Lower interest rates than inflation, are not compensating lenders for holding a nation’s debt hence making nation’s currency vulnerable to capital outflows.
A history of high inflation and negative total returns:: Nations with bad history have lack of trust in value of their currency and debt
Trend & Momentum indicators
Momentum trading is used to capture moves in shorter timeframes than trends. Momentum is the relative change occurring in markets. Relative change is different to a trend. A long-term trend can be up but the short-term momentum of a specific market can be 0.
If a market moves down and then moves up and then moves back down the net relative change in price is 0. That means momentum is 0.
A short-term positive momentum, with a long-term downtrend results in markets with no momentum. MacroVar Momentum model for Financial Markets
MacroVar Trend signal ranges from -100 to +100. The market trend signal is derived as the mean value from 4 calculations for each asset. The timeframes monitored are the following: 1 Day (1 trading day), 1 Week (5 trading days), 1 Month (20 trading days), 3 Months (60 trading days)
For each timeframe, the following calculations are performed: 1. Calculations of the return for the specific timeframe, 2. If return calculated is higher than 0, signal value 1 else signal value -1. Finally, the 4 values are aggregated daily.
MacroVar Trend model for Financial Markets The most important trend indicator
The 52-week simple moving average and its slope are the most important indicators defining a market’s trend. An uptrend is characterized by price above the 52-week moving average followed by an upward slope. If fundamentals of the market have not changed and the moving average slope is still in uptrend, a price drop signifies a market correction and not a change of trend. Traders should watch oscillators like MacroVar oscillator and RSI to buy the dip and still follow the trend. The moving average slope turn signifies a change of trend. MacroVar Trend model for financial markets
MacroVar Trend signal ranges from -100 to +100. The market trend signal is derived as the mean value from 8 calculations for each asset. The timeframes monitored are the following: 1-month (20 trading days), 3-months (60 trading days), 6-months (125 trading days), 1-year (250 trading days)
For each timeframe, the following calculations are performed: 1. Closing price vs moving average (MA): if price greater than MA value is +1, else -1, 2. Moving average slope: if current MA is higher than previous MA, upward slope +1, else -1
MacroVar trend model can be used as a trend strength indicator. MacroVar trend strength values ranging between +75 and +100 or -75 and -100 show strong trend strength.
A technical rollover is identified when MacroVar trend strength indicator moves from positive to negative value or vice-versa.
MacroVar Trend model for Macroeconomic Indicators
A macroeconomic indicator is in an uptrend when last value is higher than its twelve month moving average and its twelve month moving average slope is positive (last twelve month moving average is higher than the previous month’s twelve month moving average)
Lastly, MacroVar calculates the number of months the current value has recorded highs or lows. Trend change is assumed when a specific indicator has recorded a 3-month high / low or more. MacroVar Momentum model for Macroeconomic Indicators
A macroeconomic indicator’s momentum is monitored by calculating its long-term year over year (Y/Y) return and its short-term month on month (M/M) return.
MacroVar is a free financial and economic analysis platform designed to help you make the right trading, investment and business decisions based on data analysis of global financial and economic conditions.
Sign up Free to MacroVar Financial & Economic analytics
MacroVar Financial and economic data driven models will help you outsmart your competition, identify new opportunities, and avoid risks by predicting how economcic and financial markets conditions will affect your business.
