jaymd96-index-inclusion
Stock index inclusion probability prediction. Screens stocks against eligibility rules for 7 major indices (S&P 500, S&P 400, S&P 600, NASDAQ-100, FTSE 100, DJIA, Russell 3000), scores candidates with heuristic signals, and optionally refines predictions with ML.
Install
pip install jaymd96-index-inclusion
Quick Start
from index_inclusion import IndexInclusion
ii = IndexInclusion(fmp_api_key="your-key")
# Check a single stock
result = ii.check("PLTR", "SP500")
print(f"{result.ticker}: {result.probability:.1%} ({result.probability_label})")
# Find top candidates for an index
candidates = ii.candidates("SP500", top_n=10)
for c in candidates:
print(f"{c.ticker}: {c.probability:.1%}")
# Backtest prediction accuracy
report = ii.backtest("SP500", start=2016, end=2025)
print(f"Precision@3: {report.precision_at_3:.1%}")
# Train ML models
ii.train("SP500", start=2016, end=2023)
candidates = ii.candidates("SP500") # now uses ML calibration
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for jaymd96-index-inclusion 0.1.0
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Total release size: 75.9 kB
Release files / jaymd96_index_inclusion-0.1.0.tar.gz
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