Financial Research Data Services
Project description
FRDS - Financial Research Data Services
frds
aims to provide the simplest way to compute a collection of major academic measures used in the finance literature.
Getting started by checking out this notebook.
Example usage
Import
We start by importing relevant modules.
Specifically, we import the Funda
class from the frds.data.wrds.comp
library since the demo uses only the Fundamentals Annual dataset from Compustat via WRDS. We next import the setup
and load
functions from frds.io.wrds
, which are used to configure WRDS credentials and data management for WRDS datasets.
from frds.data.wrds.comp import Funda
from frds.io.wrds import setup, load
(Optional) Setup
Then, set WRDS credentials in case later we need to download from WRDS.
setup(username='username', password='password', save_credentials=True)
Load data
We now download the Funda
(Fundamentals Annual) dataset and assign it to the variable FUNDA
.
FUNDA = load(Funda, use_cache=True, obs=100)
Compute
Let's now compute a few metrics to showcase how easy it is.
import numpy as np
import pandas as pd
from frds.measures.corporate import roa
pd.DataFrame(
{
# We can calculate metrics on the go
"Fyear": FUNDA.FYEAR,
"Tangibility": FUNDA.PPENT / FUNDA.AT,
"Firm_Size": np.log(FUNDA.AT),
"MTB": FUNDA.PRCC_F * FUNDA.CSHO / FUNDA.CEQ,
# Or we can use the built-in measures available in FRDS:
"ROA_v1": roa(FUNDA),
"ROA_v2": roa(FUNDA, use_lagged_total_assets=True)
}
).dropna().head(10)
The result would be a nice pd.DataFrame
:
Fyear | Tangibility | Firm_Size | MTB | ROA_v1 | ROA_v2 | ||
---|---|---|---|---|---|---|---|
GVKEY | DATADATE | ||||||
001000 | 1970-12-31 | 1970 | 0.265351 | 3.510052 | 2.319803 | 0.056143 | 0.065408 |
1971-12-31 | 1971 | 0.260450 | 3.378611 | 2.054797 | 0.004705 | 0.004126 | |
1976-12-31 | 1976 | 0.426061 | 3.652890 | 0.899635 | 0.088996 | 0.947310 | |
001001 | 1984-12-31 | 1984 | 0.781644 | 2.789139 | 1.492970 | 0.069958 | 0.080441 |
1985-12-31 | 1985 | 0.567439 | 3.676174 | 3.102697 | 0.065223 | 0.158357 | |
001002 | 1970-12-31 | 1970 | 0.181825 | 2.619000 | 0.499715 | 0.035490 | 0.032331 |
1971-12-31 | 1971 | 0.207127 | 2.495104 | 0.827517 | 0.065660 | 0.058009 | |
1972-12-31 | 1972 | 0.166369 | 2.752131 | 0.561460 | 0.057285 | 0.074074 | |
001003 | 1983-12-31 | 1983 | 0.030015 | 2.143472 | 2.311034 | 0.123109 | 0.186435 |
1984-12-31 | 1984 | 0.051450 | 2.109122 | 1.138268 | 0.046960 | 0.138214 |
Built-in Measures
Check the built-in measures and documentation.
Note
This library is still under development and breaking changes may be expected.
Project details
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