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PCA Residual Statistical Arbitrage on Sector ETFs
trade the mean-reverting residual after hedging out common factors
Avellaneda-Lee-style residual stat-arb (PCA/ETF factor decomposition) reported strong Sharpe ratios on US equities 1997–2007, with PCA-based residuals outperforming ETF-based ones. The strategy isolates the idiosyncratic, mean-reverting component of each name after removing systematic factors — precisely the signal amplified by today's low-correlation regime.
Why it's relevant now
When market-wide correlation is near record lows, common factors explain less variance, so the residual (idiosyncratic) piece is larger and its mean-reversion signal is cleaner and more tradable.
Universe
Constituents of a handful of liquid sector ETFs (e.g. XLK, XLF, XLE holdings) or the sector ETFs themselves as the factor set. Free daily OHLCV; factor loadings estimated from returns, no fundamentals needed.
How it works
Estimate rolling factor loadings via PCA (or regression on sector ETFs), model each name's residual as an Ornstein-Uhlenbeck process, compute an s-score, go long residuals with s-score < -1.25 and short those > +1.25, exit near zero, daily rebalance.
Expected performance
Research-derived Sharpe estimate: 0.7–1.3. paper numbers are high/gross; apply the realism discount — costs and daily turnover bite hard).
Backtest this idea with SignalChain
This is a research lead — not a finished backtest. SignalChain takes an idea like this and runs the whole pipeline inside Claude Code: it researches the concept against academic and practitioner sources, sets benchmarks, writes and lints a VectorBT backtest, runs it, and grades the result PASS/FAIL. One command:
/signalchain PCA residual statistical arbitrage on sector-ETF constituents: hedge out common factors, model residual as Ornstein-Uhlenbeck, long residuals with s-score below -1.25 and short above +1.25.
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Research & sources
- arxiv.org — arxiv.org
- ar5iv.labs.arxiv.org — ar5iv.labs.arxiv.org
- stanford.edu — stanford.edu
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Not financial advice. This page describes a research idea, not a recommendation. Any performance figures are hypothetical, research-derived estimates and are not indicative of future results. SignalChain is a research and educational tool; you are solely responsible for any decisions you make.