Poland balance of trade

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.

If you are new to investing check our introduction on trends and momentum.

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:

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.

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.

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.

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, click here to close 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:

• Commodities Indices: Energy, Industrial Metals, Precious Metals, Agriculture
• Energy: Crude Oil, Natural Gas, Heating Oil, Uranium
• Metals: Copper, Iron Ore, Aluminum, Nickel
• Precious Metals: Gold, Silver, Platinum, Palladium
• Soft commodities: Rubber, Lumber, Cotton, Platinum, Coffee, Cocoa, Sugar, Orange Juice
• Food commodities: Corn, Wheat, Oat, Rice, Soybeans, Soybean Oil, Soybean meal, Feeder Cattle
• Shipping: Baltic Dry Index, Baltic Capesize Index, Baltic Panamax Index, Baltic Supramax Index, Baltic Handysize Index, Baltic Dirty Tanker Index, Baltic Clean Tanker Index, China Bulk Freight Index, China Container freight index

MacroVar Quantitative Signals

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:

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.

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.

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.

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, click here to close 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, click here to close 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 monitors sovereign bonds, corporate bonds, credit default swaps, global yield curves, STIR (short-term interest rates), Interest Rate Swaps, US/EU/GB 3-month LIBOR futures, SOFR, SONIA and fed funds Futures, Eurodollar futures.

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, click here to close 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:

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.

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.

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.

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, click here to close 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:

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.

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.

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.

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 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.

If you are new to investing check our introduction on trends and momentum.

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:

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.

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.

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.

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, click here to close 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:

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:

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.

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.

Your can find full analysis of Global Macroeconomic models.

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, click here to close the window and select Risk Management 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

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.

Your can find full analysis of MacroVar risk Management models.