Financial & Economic Indicators Database
Explore MacroVar Financial and Macroeconomic indicators database. Access historical data using MacroVar's web interface Excel or API.
Financial Data
| varnm | Symbol | Country | Type |
|---|---|---|---|
| POSCO | CDS.POSCO | South Korea | Corporate CDS |
| RIO TINTO LIMITED | CDS.RIO-TINTO | Australia | Corporate CDS |
| BHP BILLITON LIMITED | CDS.BHP-BILLITON | Australia | Corporate CDS |
| Hutchison Whampoa Limited | CDS.Hutchison-Whampoa | Hong Kong | Corporate CDS |
| MATALAN FINANCE PLC | CDS.MATALAN-FINANCE | United Kingdom | Corporate CDS |
| PEUGEOT SA | CDS.PEUGEOT | France | Corporate CDS |
| ACWI ETF | EWA | Global | CDS |
| ARDAGH PACKAGING FINANCE PUBLIC LIMITED COMPANY | CDS.Ardagh-Packaging-Finance | United Kingdom | Corporate CDS |
| CROWN EUROPEAN HOLDINGS | CDS.Crown-Holdings | France | Corporate CDS |
| CMA CGM | CDS.CMA-CGM | France | Corporate CDS |
Economic Indicators
| Economic Indicator | Symbol | Country | url |
|---|---|---|---|
| balance of trade | al.balanceoftrade | Albania | https://macrovar.com/albania/balance-of-trade |
| bank lending rate | al.banks.lendingrate | Albania | https://macrovar.com/albania/bank-lending-rate |
| banks balance sheet | al.banks.bs | Albania | https://macrovar.com/albania/banks-balance-sheet |
| building permits | al.buildingpermits | Albania | https://macrovar.com/albania/building-permits |
| business confidence | al.bizconfidence | Albania | https://macrovar.com/albania/business-confidence |
| central bank balance sheet | al.cb.assets | Albania | https://macrovar.com/albania/central-bank-balance-sheet |
| consumer confidence | al.consconfidence | Albania | https://macrovar.com/albania/consumer-confidence |
| consumer price index cpi | al.cpi | Albania | https://macrovar.com/albania/consumer-price-index-cpi |
| current account | al.currentaccount | Albania | https://macrovar.com/albania/current-account |
| current account to gdp | al.currentaccountgdp | Albania | https://macrovar.com/albania/current-account-to-gdp |
MacroVar API
Follow the Steps below to Access the MacroVar Database via the following API:
Step 1: Copy the following Code or click to download python file MacroVar Python API
Step 2: Search MacroVar financial securities and macroeconomic indicators database using the search options above Step 3:Insert your Query's criteria in d=am.load by specifying the variable name, start and end date
Alternatively, you can access MacroVar using MS Excel
# -*- coding: utf-8 -*-
"""
MacroVar API Python Script
Upgrade your Account to gain unlimited access https://macrovar.com/plans
Please find and search the full list of macroeconomic variables & financial variables at https://MacroVar.com/financial-database-variables
Instructions: 1. Insert your username, password 2. variable name, start date, end date 3. Run Script
"""
import http.client
from urllib.parse import quote
import pandas as pd
class MacroVar(object):
user_name, password, conn, headers, payload = None, None, None, None, None
def __init__(self, user_name, password):
self.auth(user_name, password)
self.conn = http.client.HTTPConnection("api.MacroVar.com:8080")
def auth(self, user_name, password):
self.user_name = user_name
self.password = password
self.headers = {'Authorization': '{};{}'.format(self.user_name, self.password)}
def get_vars(self):
self.conn.request(method="GET", url="/vars", headers=self.headers)
response = self.conn.getresponse()
data = response.read()
str_data = data.decode("utf-8")
return str_data.split(',')
def load_data(self, var_name, start_date=None, end_date=None):
v = self.get_vars()
if var_name not in v:
raise ValueError('Variable name not found, check the get_vars() result.')
params = 'name={}'.format(quote(var_name))
if start_date:
params += '&start_date={}'.format(start_date)
if end_date:
params += '&end_date={}'.format(end_date)
url = "/query?" + params
self.conn.request(method="GET", url=url, headers=self.headers)
response = self.conn.getresponse()
if response.status == 200:
data = response.read()
str_data = data.decode("utf-8")
data_rows = str_data.split('\r\n')
if len(data_rows) <= 1:
return data_rows
data_arr = []
for d in data_rows:
data_arr.append(d.split(','))
d = data_arr[:-1] # skip the last empty row
return pd.DataFrame(d[2:], columns=d[0])
else:
raise ValueError('Server error {} {}'.format(response.status, response.reason))
return None
if __name__ == '__main__':
am = MacroVar('MacroVartest', 'test')
v = am.get_vars()
d = am.load_data('US-1Y', '2010-01-03', '2019-02-01')
print (d)
"""
MacroVar API Python Script
Upgrade your Account to gain unlimited access https://macrovar.com/plans
Please find and search the full list of macroeconomic variables & financial variables at https://MacroVar.com/financial-database-variables
Instructions: 1. Insert your username, password 2. variable name, start date, end date 3. Run Script
"""
import http.client
from urllib.parse import quote
import pandas as pd
class MacroVar(object):
user_name, password, conn, headers, payload = None, None, None, None, None
def __init__(self, user_name, password):
self.auth(user_name, password)
self.conn = http.client.HTTPConnection("api.MacroVar.com:8080")
def auth(self, user_name, password):
self.user_name = user_name
self.password = password
self.headers = {'Authorization': '{};{}'.format(self.user_name, self.password)}
def get_vars(self):
self.conn.request(method="GET", url="/vars", headers=self.headers)
response = self.conn.getresponse()
data = response.read()
str_data = data.decode("utf-8")
return str_data.split(',')
def load_data(self, var_name, start_date=None, end_date=None):
v = self.get_vars()
if var_name not in v:
raise ValueError('Variable name not found, check the get_vars() result.')
params = 'name={}'.format(quote(var_name))
if start_date:
params += '&start_date={}'.format(start_date)
if end_date:
params += '&end_date={}'.format(end_date)
url = "/query?" + params
self.conn.request(method="GET", url=url, headers=self.headers)
response = self.conn.getresponse()
if response.status == 200:
data = response.read()
str_data = data.decode("utf-8")
data_rows = str_data.split('\r\n')
if len(data_rows) <= 1:
return data_rows
data_arr = []
for d in data_rows:
data_arr.append(d.split(','))
d = data_arr[:-1] # skip the last empty row
return pd.DataFrame(d[2:], columns=d[0])
else:
raise ValueError('Server error {} {}'.format(response.status, response.reason))
return None
if __name__ == '__main__':
am = MacroVar('MacroVartest', 'test')
v = am.get_vars()
d = am.load_data('US-1Y', '2010-01-03', '2019-02-01')
print (d)