Harvesters Code Book
Harvesters subpackage is built to support Data Harvestering Ops from many varied data sources. this currently supports the Following Sources:
- AlphaVantage
- FRED
- GDELT
- Quandl
- Investpy
- YahooFinance
- IMF
The Usage of these sources can be found in the API Documentation Section.
These Harvesters need to be provided with some codes to fetch the data from. These codes are unique and represent a certain entity.
FRED
| Code | Description |
|---|---|
| T5YIFR | 5-Year, 5-Year Forward Inflation Expectation Rate |
| DGS30 | 30-Year Treasury Constant Maturity Rate |
| DGS10 | 10-Year Treasury Constant Maturity Rate |
| DFF | Effective Federal Funds Rate |
| DGS6MO | 6-Month Treasury Constant Maturity Rate |
| USD3MTD156N | 3-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar |
| DTB3 | 3-Month Treasury Bill: Secondary Market Rate |
| T10Y2Y | 10-Year Treasury Constant Maturity Minus 2-Year Treasury Constant Maturity |
| T10YIE | 10-Year Breakeven Inflation Rate |
| DAAA | Moody's Seasoned Aaa Corporate Bond Yield |
| TEDRATE | TED Spread |
| DBAA | Moody's Seasoned Baa Corporate Bond Yield |
| DGS1MO | 1-Month Treasury Constant Maturity Rate |
| DGS10 | 10-Year Treasury Constant Maturity Rate |
| DFEDTARU | Federal Funds Target Range - Upper Limit |
| VIXCLS | CBOE Volatility Index: VIX |
| GOLDAMGBD228NLBM | Gold Fixing Price 10:30 A.M. (London time) in London Bullion Market, based in U.S. Dollars |
| DPRIME | Bank Prime Loan Rate |
| DGS1MO | 1-Month Treasury Constant Maturity Rate |
| USRECD | NBER based Recession Indicators for the United States from the Period following the Peak through the Trough |
| DGS20 | 20-Year Treasury Constant Maturity Rate |
| USD6MTD156N | 6-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar |
| IOER | Interest Rate on Excess Reserves |
| DFEDTARL | Federal Funds Target Range - Lower Limit |
| USEPUINDXD | Economic Policy Uncertainty Index for United States |
| DPCREDIT | Primary Credit Rate |
| USD2MTD156N | 2-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar |
| USD1WKD156N | 1-Week London Interbank Offered Rate (LIBOR), based on U.S. Dollar |
| RRPONTSYD | Overnight Reverse Repurchase Agreements: Treasury Securities Sold by the Federal Reserve in the Temporary Open Market Operations |
Quandl
Codes for this harvester can be referenced from quandl website for the followings:
- Effective Exchange Rate
- Policy Rates
- US dollar exchange rate
- US dollar exchange rate
- Credit to the non-financial sector
- Debt service ratios for the private non-financial sector
- Global liquidity indicators
- Exchange-traded derivatives statistics
- OTC derivatives outstanding
Alpha Vantage
Functions(Allowed values)
1. TIME_SERIES
2. FX
3. DIGITAL_CURRENCY
symbol: Can be referenced from Google finance/ Yahoo finance.
Bond prices
WIP: https://investpy.readthedocs.io/index.html
Investing.com
Codes for this harvester are too many. But can be formalized as:
Country-Time-Period
The country along with the period can be referenced from here
Also, The submission format must follow: Country-Time-Period
GDELT
THE CAMEO CODES FROM 1-20 each have a significance on the geopolitical state of a country and its economic status it's upto us to determine which Cameo Codes will be useful based on the industry our asset is based upon
| Cameo Codes | Description |
|---|---|
| 01 | MAKE PUBLIC STATEMENT |
| 02 | APPEAL |
| 03 | EXPRESS INTENT TO COOPERATE |
| 04 | CONSULT |
| 05 | ENGAGE IN DIPLOMATIC COOPERATION |
| 06 | ENGAGE IN MATERIAL COOPERATION |
| 07 | PROVIDE AID |
| 08 | YIELD |
| 09 | INVESTIGATE |
| 10 | DEMAND |
| 11 | DISAPPROVE |
| 12 | REJECT |
| 13 | THREATEN |
| 14 | PROTEST |
| 15 | EXHIBIT MILITARY POSTURE |
| 16 | REDUCE RELATIONS |
| 17 | COERCE |
| 18 | ASSAULT |
| 19 | FIGHT |
| 20 | ENGAGE IN UNCONVENTIONAL MASS VIOLENCE |
main cameo codes will be 14 reflecting protests and 20 reflecting war but depends on the industry as Code 15 is important for arms manufacturing assets
Economic Policy Uncertainty
To measure policy-related economic uncertainty, EPU constructed an index from three types of underlying components. One component quantifies newspaper coverage of policy-related economic uncertainty. A second component reflects the number of federal tax code provisions set to expire in future years. The third component uses disagreement among economic forecasters as a proxy for uncertainty. Following countries data is available
| Country |
|---|
| India |
| Australia |
| Brazil |
| Canada |
| Chile |
| China |
| Colombia |
| France |
| Germany |
| Greece |
| India |
| Ireland |
| Italy |
| Japan |
| Korea |
| Netherlands |
| Russia |
| Spain |
| Singapore |
| UK |
| US |
| SCMP China |
| Mainland China |
| Sweden |
| Mexico |
Geopolitical Risk Index
To measure policy-related geopolitical risk index, The GPR index reflects automated text-search results of the electronic archives of 11 national and international newspapers: The Boston Globe, Chicago Tribune, The Daily Telegraph, Financial Times, The Globe and Mail, The Guardian, Los Angeles Times, The New York Times, The Times, The Wall Street Journal, and The Washington Post. Caldara and Iacoviello calculate the index by counting the number of articles related to geopolitical risk in each newspaper for each month (as a share of the total number of news articles). The index is then normalized to average a value of 100 in the 2000-2009 decade. Following countries data is available
| Country |
|---|
| TURKEY |
| MEXICO |
| KOREA |
| RUSSIA |
| INDIA |
| BRAZIL |
| CHINA |
| INDONESIA |
| SAUDI_ARABIA |
| SOUTH_AFRICA |
| ARGENTINA |
| COLOMBIA |
| VENEZUELA |
| THAILAND |
| UKRAINE |
| ISRAEL |
| MALAYSIA |
| PHILIPPINES |
| HONG_KONG |