Uses of Record Class
com.quantfinlib.alpha.FamaMacBeth.Result
Packages that use FamaMacBeth.Result
Package
Description
The alpha research pipeline — signal to evaluated, validated, cost-aware,
constructed, reported strategy, with each stage a separate, composable
step:
Signal generation —
Factors:
nine standard factors (MA crossover, contrarian RSI, MACD,
Bollinger reversion, mean reversion, 12-1 momentum, value, quality,
low volatility) producing raw cross-sectional scores over an
AlphaContext panel;
Evaluation — SignalEvaluator:
rank IC, IR, t-stat, hit rate, turnover, cross-factor exposure —
the cheap filter before any backtest;
Validation — AlphaValidation:
walk-forward selection with OOS efficiency, blocked k-fold
consistency, Monte Carlo permutation p-values, parameter
sensitivity — the overfitting defense;
Execution-aware backtest —
AlphaBacktester: commission, bid-ask
spread, slippage and square-root market impact
(microstructure.MarketImpactModel), with gross-vs-net cost
decomposition;
Portfolio construction —
PortfolioConstruction: z-score
sizing with caps, inverse-vol risk budgeting, sector and beta
neutralization, mean-variance tilt;
Reporting — AlphaReport:
alpha decay with half-life, OLS factor attribution, drawdown
curves, rolling Sharpe, and the shared ratio set from
backtest.PerformanceAnalytics.
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Uses of FamaMacBeth.Result in com.quantfinlib.alpha
Methods in com.quantfinlib.alpha that return FamaMacBeth.ResultModifier and TypeMethodDescriptionstatic FamaMacBeth.ResultFamaMacBeth.fit(double[][][] exposures, double[][] forwardReturns)