wehub-resource-sync
84 lines
3.4 KiB
Markdown
84 lines
3.4 KiB
Markdown
# Macroeconomic Indicators (FRED)
|
|
|
|
~40 macroeconomic and financial-condition time series from the Federal
|
|
Reserve Economic Data (FRED) service. Used across the book for regime
|
|
detection, macro factor engineering, and control variables in causal
|
|
analyses. All series are stored in a single wide-format parquet.
|
|
|
|
## Dataset
|
|
|
|
- **Source**: FRED (Federal Reserve Bank of St. Louis) via the public
|
|
FRED REST API.
|
|
- **Coverage**: 2000-01-01 → present; mixed frequency (daily, weekly,
|
|
monthly — daily-aligned in the loader output).
|
|
- **Series**: ~40 (treasury yields, credit spreads, volatility indices,
|
|
real-economy indicators, financial-conditions indices).
|
|
- **Size on disk**: under 1 MB (primary parquet + metadata + dictionary).
|
|
- **Runtime**: under 2 minutes for a full refresh (FRED API is fast).
|
|
- **API key**: `FRED_API_KEY` required — free at https://fred.stlouisfed.org/docs/api/api_key.html.
|
|
- **License / attribution**: FRED data is public domain; the service
|
|
requests attribution when series are redisplayed. See
|
|
https://fred.stlouisfed.org/legal/.
|
|
|
|
## Key Series
|
|
|
|
| Group | Series |
|
|
| -------------------- | ------------------------------------------------------- |
|
|
| Treasury yields | DGS1MO, DGS3MO, DGS6MO, DGS1, DGS2, DGS5, DGS10, DGS30 |
|
|
| Spreads | T10Y2Y, T10Y3M, BAMLH0A0HYM2, TEDRATE |
|
|
| Volatility | VIXCLS, MOVE |
|
|
| Economic | UNRATE, INDPRO, CPIAUCSL, PCEPI, GDP |
|
|
| Financial conditions | NFCI, STLFSI4 |
|
|
|
|
Full list + descriptions: `config.yaml` and `fred_macro_metadata.parquet`
|
|
(load via `load_macro_metadata()`).
|
|
|
|
## Download
|
|
|
|
```bash
|
|
uv run python data/macro/download.py # full refresh
|
|
uv run python data/macro/download.py --dry-run # plan only
|
|
```
|
|
|
|
Output layout under `$ML4T_DATA_PATH/macro/`:
|
|
|
|
```
|
|
fred_macro.parquet # primary wide-format series (loader target)
|
|
fred_macro_metadata.parquet # per-series metadata (name, group, description, source id)
|
|
fred_macro_dictionary.parquet # code-book for series names
|
|
fred_macro_profile.json # summary statistics
|
|
fred_macro_raw.parquet # raw unprocessed pull (reserve)
|
|
fred_macro_raw_dictionary.parquet
|
|
fred_macro_raw_profile.json
|
|
```
|
|
|
|
## Loading
|
|
|
|
```python
|
|
from data import load_macro, load_macro_metadata
|
|
|
|
df = load_macro() # all series, wide format
|
|
df = load_macro(series=["DGS10", "DGS2", "VIXCLS"])
|
|
df = load_macro(start_date="2015-01-01", end_date="2023-12-31")
|
|
|
|
meta = load_macro_metadata() # series metadata table
|
|
```
|
|
|
|
Schema (loader output, canonical):
|
|
|
|
| Column | Type | Description |
|
|
| ------------ | -------- | ------------------------------- |
|
|
| `timestamp` | Date | Observation date |
|
|
| `{SERIES}` | Float | Series value (one col per code) |
|
|
|
|
The on-disk parquet uses `date`; `load_macro()` renames it to `timestamp`
|
|
to match the book's canonical schema.
|
|
|
|
## Consumers
|
|
|
|
- **Ch4**: `06_fred_macro_eda.py`, `07_macro_data_alignment.py`.
|
|
- **Ch7**: `08_causal_sanity_checks.py`.
|
|
- **Ch8**: `04_fundamentals_macro_calendar.py`.
|
|
- **Ch16**: `01_backtest_first_principles.py`, `06_framework_parity.py`.
|
|
- **Ch18**: `02_spread_estimation.py`, `03_market_impact_calibration.py`.
|