Does this signal
survive reality?
Testing whether systematic alpha signals survive costs, out-of-sample validation, and market stress. Each of 5 signals is treated as a research case and carried through one validation sequence.
- 01Thesis
- 02Cost-aware evidence
- 03Out-of-sample
- 04Walk-forward
- 05Robustness
- 06Classification
Five signals under review
Each row is a research case carried through the same validation sequence. Select one to open its file; the sections that follow update to the selected signal.
| Signal & thesis | Classification | Key evidence | Principal weakness | ||
|---|---|---|---|---|---|
| 01 | Time-Series Momentum Assets in a sustained year-long uptrend tend to continue; the strategy holds those with positive medium-term trend. | Survived | Sharpe 0.57 · DD -15% CAGR 5.7% net | Performance is uneven across market regimes. | Viewing |
| 02 | Cross-Sectional Momentum The strongest-trending assets relative to the universe tend to keep leading; the strategy holds only the relative leaders. | Survived | Sharpe 0.62 · DD -18% CAGR 8.8% net | Performance is uneven across market regimes. | Open |
| 03 | Short-Term Reversal Assets with a sharp multi-day sell-off tend to partially recover; the strategy holds the most oversold names. | Rejected | Sharpe 0.44 · DD -29% CAGR 5.1% net | High turnover (12.8x/yr) makes it execution-sensitive. | Open |
| 04 | Volatility-Scaled Momentum Trend-following with position sizes scaled down as volatility rises, holding portfolio risk closer to a fixed target. | Conditional | Sharpe 0.57 · DD -12% CAGR 4.3% net | Performance is uneven across market regimes. | Open |
| 05 | Equal-Weight Signal Ensemble Combine the four signals' standardized scores and hold the assets the blend rates positively, reducing reliance on any single signal. | Survived | Sharpe 0.59 · DD -22% CAGR 7.8% net | Performance is uneven across market regimes. | Open |
Time-Series Momentum
Assets in a sustained year-long uptrend tend to continue; the strategy holds those with positive medium-term trend.
Assets with positive medium-term trends tend to keep performing, because capital moves slowly, investors underreact, and macro regimes persist.
12-month return, skipping the last month.
momentum_12_1[t] = adj_close[t-21] / adj_close[t-252] - 1Hold every asset with positive 12-1 momentum, equal-weighted; park the rest in cash.
- Works in persistent trend regimes
- Avoids prolonged drawdowns by stepping aside
- Rotates across asset classes
- Lags sharp reversals
- Underperforms in choppy markets
- Misses V-shaped recoveries
Performance, gross and net of costs
Growth of an index of 100 over the backtest sample (from 2007-02-28), against a selectable benchmark. The strategy is shown gross and net of 5 bps transaction costs.
| In-sample, 2006 to 2016 | 5.3% | 0.66 |
| Out-of-sample · 2017→ | 6.1% | 0.47 |
| CAGR | Sharpe |
Response to moving assumptions
Each module re-runs the signal under a different perturbation (cost, parameter, rebalance frequency, market regime, and crisis window) to test whether the result holds when the assumptions move.
Time-Series Momentum holds up: net Sharpe 0.57, -15.3% max drawdown, and out-of-sample Sharpe 0.47. It survives realistic costs and parameter variation.
Classification ledger
The committee classification for each signal, grouped by verdict and backed by the same evidence inspected above. Select any row to reopen its file.
Of five signals examined, three survived validation as documented research overlays, one is conditional, and one is rejected on this evidence.
| Signal | Primary evidence | Principal weakness | Research note |
|---|---|---|---|
Survived3 signals Useful net-of-cost performance, controlled drawdowns, and credible out-of-sample evidence that does not depend on a single parameter choice. | |||
Time-Series Momentum Net Sharpe 0.57, max drawdown -15%, 5.7% CAGR net of 5 bps. Use as a long-only de-risking trend overlay that controls drawdowns, not as a standalone return-maximizing strategy. | Net Sharpe 0.57 at 5 bps with -15.3% max drawdown (SPY drew down -55.2%). | Performance is uneven across market regimes. | Time-Series Momentum holds up: net Sharpe 0.57, -15.3% max drawdown, and out-of-sample Sharpe 0.47. It survives realistic costs and parameter variation. |
Cross-Sectional Momentum Net Sharpe 0.62, max drawdown -18%, 8.8% CAGR net of 5 bps. Use as a relative-strength allocation sleeve within a diversified book, not as proof of standalone alpha. | Net Sharpe 0.62 at 5 bps with -18.4% max drawdown (SPY drew down -55.2%). | Performance is uneven across market regimes. | Cross-Sectional Momentum holds up: net Sharpe 0.62, -18.4% max drawdown, and out-of-sample Sharpe 0.72. It survives realistic costs and parameter variation. |
Equal-Weight Signal Ensemble Net Sharpe 0.59, max drawdown -22%, 7.8% CAGR net of 5 bps. Use as a diversified, lower-variance core blend, not as a single-signal bet or proof of alpha. | Net Sharpe 0.59 at 5 bps with -21.8% max drawdown (SPY drew down -55.2%). | Performance is uneven across market regimes. | Equal-Weight Signal Ensemble holds up: net Sharpe 0.59, -21.8% max drawdown, and out-of-sample Sharpe 0.59. It survives realistic costs and parameter variation. |
Conditional1 signal Adds value under specific regimes or cost levels, or as a risk-control overlay. Useful, but not standalone alpha. | |||
Volatility-Scaled Momentum Net Sharpe 0.57, max drawdown -12%, 4.3% CAGR net of 5 bps. Use as a volatility-control overlay when drawdown control matters more than raw return, not as a return maximizer. | Net Sharpe 0.57 at 5 bps with -11.8% max drawdown (SPY drew down -55.2%). | Performance is uneven across market regimes. | Volatility-Scaled Momentum is conditional: it adds value mainly through risk control (net Sharpe 0.57, -11.8% max drawdown) rather than raw return, and depends on costs or regime. |
Rejected1 signal Costs, turnover, benchmark-relative weakness, or instability undo the signal. A documented negative result. | |||
Short-Term Reversal Net Sharpe 0.44, max drawdown -29%, 5.1% CAGR net of 5 bps. Not recommended as a standalone allocation on this evidence; at most a low-cost tactical input, never a return-maximizing strategy. | Net Sharpe 0.44 at 5 bps with -29.1% max drawdown (SPY drew down -55.2%). | High turnover (12.8x/yr) makes it execution-sensitive. | Short-Term Reversal is rejected on this evidence: it does not clear simple benchmarks; net Sharpe 0.44, out-of-sample Sharpe 0.32. |
Data, construction, and validation record
ETF prices from Yahoo Finance (dividend- and split-adjusted close). Macro series from Yahoo Finance (VIX, 10-year and 13-week Treasury yields) and FRED (CPI). NBER recession dates and fixed crisis windows are used only for retrospective regime labeling. Portfolio returns use adjusted close as a total-return approximation. Every figure on this page is produced by the Python research engine and read from generated JSON; none is entered by hand.
- 15 liquid ETFs · 9 asset groups
- Price panel 2006-01-03 → 2026-08-14
- Backtest calendar from 2007-02-28
- Returns: dividend- and split-adjusted close (used as a total-return approximation)
- Sources: FRED, NBER, Yahoo Finance
feature[t] uses data through t; signal[t] formed at t; position[t+1] uses signal[t]; return[t+1] earned by position[t+1].
Cash / T-bill exposure (the cash fallback and the cash benchmark) earns the 13-week US Treasury-bill yield from Yahoo (^IRX), applied continuously across the full sample. BIL and SHV are included as tradable ETFs, but the continuous T-bill rate is used for cash so there is no 2007 inception gap.
Cost = turnover x bps / 10000, applied as a return drag.
Turnover = sum of absolute weight changes at a rebalance (total traded notional / NAV, including both buys and sells).
1 / 5 / 10 / 25 bps · primary 5 bps
- Train 2006-01 to 2016-12
- Test 2017-01 to present
- 4 expanding walk-forward windows
- Cost · parameter · rebalance · regime · crisis
Regime and crisis labels are used for retrospective validation, not live trading decisions. Macro inputs are lagged so labels use only information observable at the time.