Template Gallery
Pre-built strategy frameworks grounded in academic research. Each template ships with evidence tier ratings, capacity constraints, regime caveats, and default settings so you can calibrate expectations before running a backtest.
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Run immediately — all use price data the engine supports.
Trend Following
Price momentum with a trailing stop
Cross-Sectional Momentum
Rank a universe by return, rotate into top performers
ETF Rotation
Rotate across asset class ETFs by relative momentum
Commodity Carry
Roll yield proxy using front-month ETF returns
Cross-Sectional Momentum (12-1)
Each month, rank your universe by trailing 12-month return (skipping the most recent month) and hold the top quintile. The 12-1 specification is the most-replicated momentum variant across asset classes.
What it captures
Assets that have outperformed their peers over the past year tend to continue outperforming over the next 1–3 months. The 1-month skip prevents short-term reversal from contaminating the signal.
Time-Series Momentum / Trend
Hold each asset only when its own 12-month absolute return is positive; equal-weight all qualifying assets. Moves to cash when most assets are in downtrends — providing a built-in bear market hedge.
What it captures
Each asset's own trend — whether it is moving up or down on its own merits — predicts near-term returns. Unlike cross-sectional momentum, this strategy can hold 0% during broad bear markets.
Short-Term Reversal
Every week, rank your universe by 1-week return and buy the biggest losers. Short-term price pressure from liquidity-demanding sellers creates transient mispricings that revert as market makers are compensated.
What it captures
Liquidity providers absorbing temporary selling pressure earn a short-horizon premium. The strategy attempts to replicate this by systematically buying the recent losers who are most likely to bounce.
Pairs Trading (Long-Only)
Track the log-price spread between two correlated assets. Go long the cheaper asset when the z-score is 2+ standard deviations below its mean, exit when the spread normalises.
What it captures
Temporary deviations in the relative valuation of two economically linked assets tend to revert. The long-only variant captures the cheaper leg of classic statistical arbitrage.
Sector Rotation (SPDR)
Monthly, rank the 11 SPDR sector ETFs by trailing 3–6 month total return and hold the top 3. Rotate out of lagging sectors into the current economic cycle leaders.
What it captures
Different economic sectors lead and lag through the business cycle. By rotating into recent leaders, the strategy attempts to ride the dominant economic theme — technology in 2020–21, energy in 2022.
Dual Momentum
Gary Antonacci's Dual Momentum: first check absolute momentum (is SPY above cash?), then relative momentum (does SPY beat bonds?). Holds US equities, international equities, or bonds depending on signals.
What it captures
Combining absolute momentum (trend filter) with relative momentum (asset selection) reduces bear market drawdowns while capturing uptrends. The dual filter removes most of the large equity drawdowns historically.
Low Volatility
Monthly, rank your universe by trailing 63-day realised volatility and hold the lowest-volatility quintile equal-weight. Lower-risk stocks historically deliver superior Sharpe ratios — the 'low vol anomaly'.
What it captures
Low-volatility stocks outperform on a risk-adjusted basis because investors systematically overpay for high-volatility lottery-like stocks and underweight boring low-risk names due to leverage constraints and benchmark hugging.
Bollinger Mean Reversion
Enter long when price closes below the lower 2-sigma Bollinger Band (20-day MA). Exit when price crosses back above the middle band. A dynamic, volatility-scaled oversold signal.
What it captures
Short-term oversold conditions relative to recent price range tend to revert as buying interest returns. Bollinger Bands scale the entry threshold by the asset's own volatility, making the signal adaptive.
Coming Soon — Phase B
Fundamental and event-driven templates pending data pipeline support.
Coming Soon
Requires FCF yield, book-to-market, and EV/EBITDA data — coming in Phase B.
Value Composite
Rank stocks by a composite of FCF yield, book-to-market, and EV/EBITDA. Hold the cheapest decile monthly.
What it captures
Stocks trading at low prices relative to fundamentals tend to outperform as the market corrects mispricings over 12–36 month horizons.
Coming Soon
Requires annual financial statement data — coming in Phase B.
Quality — Piotroski F-Score
Long stocks with an F-Score of 8 or 9 — companies with strengthening profitability, leverage, and efficiency.
What it captures
Piotroski's 9 binary signals identify companies with improving fundamentals that the market is slow to reprice upward.
Coming Soon
Requires quarterly EPS and analyst estimate data — coming in Phase B.
Post-Earnings Drift (PEAD)
After a top-decile earnings surprise, hold the stock for 60 days to capture the gradual market revaluation.
What it captures
Markets under-react to large earnings surprises — positive shocks continue to generate abnormal returns for weeks after announcement.
Requires Additional Data
Shown for research planning.
Value + Momentum
Combine fundamental value signals with price momentum
News Sentiment Momentum
Rank stocks by rolling 30-day mean news sentiment score and go long the top decile. Combines NLP-derived sentiment signals with monthly rebalancing.
Insider Buying Cluster
Rank stocks by rolling 30-day net insider-purchase dollars (cluster buys) and hold the top 20. Insider purchases are weighted by dollar value, not count.
Multi-Factor Composite
Combine Value, Momentum, Quality, and Low-Volatility into a single equal-weighted composite score. Rank the top decile monthly. Each factor is cross-sectionally z-scored before blending.
Evidence tiers reflect peer-reviewed literature as of 2025. Past evidence ≠ future performance.
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