japan-finance-factors 0.1.1

Quantitative factor calculation for Japanese equities with PIT safety

japan-finance-factors

Quantitative factor calculation for Japanese equities with point-in-time (PIT) safety.

Features

• 10 quantitative factors across 4 categories (value, momentum, quality, risk)
• PIT-safe: All calculations respect point-in-time constraints to prevent lookahead bias
• Lightweight: Only depends on pydantic; data source integrations are optional
• Optional integrations: Convenience wrappers for edinet-mcp and stockprice-mcp

Installation

pip install japan-finance-factors

# With optional data source integrations
pip install japan-finance-factors[all]

Quick Start

from datetime import datetime
from japan_finance_factors import compute_factors, FinancialData, PriceData

# Prepare financial data (JPY units)
fd = FinancialData(
    ticker="7203",
    revenue=45_000_000_000_000,
    net_income=2_800_000_000_000,
    operating_income=3_500_000_000_000,
    total_assets=90_000_000_000_000,
    total_equity=35_000_000_000_000,
    operating_cf=4_500_000_000_000,
    capex=-1_800_000_000_000,
    market_cap=50_000_000_000_000,
    published_at=datetime(2025, 6, 25),
)

# Compute all factors
result = compute_factors(
    financial_data=fd,
    as_of=datetime(2025, 7, 1),
)

print(result.to_dict())
# {'ev_ebitda': 12.77, 'fcf_yield': 0.054, 'earnings_yield': 0.056, ...}

Factors

Category	Factor	Description
Value	ev_ebitda	Enterprise Value / EBITDA
Value	fcf_yield	Free Cash Flow / Market Cap
Value	earnings_yield	Net Income / Market Cap
Value	book_to_market	Book Value / Market Cap
Momentum	mom_3m	3-month price return
Momentum	mom_12m	12-month price return (12-1 convention)
Quality	piotroski_f_score	Piotroski F-Score (0-9)
Quality	accruals_ratio	(Net Income - Operating CF) / Total Assets
Risk	realized_vol_60d	60-day annualized volatility
Risk	max_drawdown_252d	Maximum drawdown over 252 trading days

License

Apache-2.0