Backtested research example
🗓 Backtest period: 2020-01-01..2026-07-16
Spec ID: spec-multitimeframe-momentum-us-stocks-1783167355_v3 · Generated: 2026-07-09 10:34 UTC
Cluster: Momentum · Sub Cluster: Weekly-Daily Trend Alignment
Long-only US large-cap trend-following strategy that buys stocks only when daily and completed-week trends are both bullish. Positions are ATR-sized, capped per name, and exited on trend failure, ATR trailing stop, or max holding period.
Persistent equity trends can arise from gradual information diffusion, investor underreaction, institutional rebalancing, and benchmark-driven flows. Requiring both daily and weekly trend confirmation attempts to filter short-lived rallies and participate only when momentum is visible across horizons.
The strategy is long-only and applied to liquid large-cap stocks, where capacity is plausible but alpha may be more modest. Volatility-adjusted sizing seeks to normalize risk across names, while ATR trailing stops and trend exits are designed to cut deteriorating positions before large drawdowns dominate the portfolio.
[code omitted from public view]
| Param | Value | Notes |
|---|---|---|
| Rule type | MULTI_TIMEFRAME_TREND_MOMENTUM |
Long-only trend/momentum rule |
| Universe | 20 US stocks | Top market-cap-style universe supplied in spec; includes AAPL, AMZN, BRK-A/B, GOOG/GOOGL, JPM, MSFT, NVDA, TSLA, etc. |
| Liquidity filter | $10,000,000 |
Minimum 20-day average dollar volume |
| Daily trend | 20-day SMA, 50-day SMA | Require close > 20-day SMA, 20-day SMA > 50-day SMA, and positive 5-day 20-SMA slope |
| Weekly trend | 20-week SMA, 50-week SMA | Require weekly close > 20-week SMA, 20-week SMA > 50-week SMA, and positive 4-week 20-SMA slope |
| Weekly bars | Friday close, completed week only | Weekly close is last available daily close in the completed week |
| Rebalance | Daily at close | Signals and execution evaluated on daily bars |
| Position sizing | ATR volatility-adjusted | 14-day ATR, 1% target risk per position, 10% max position size |
| Leverage cap | 4.0x |
Portfolio-level maximum leverage parameter |
| Exit rules | Trend failure, 3x ATR trailing stop, 126-day max hold | Exit if daily or weekly trend turns non-bullish |
| Backtest window | 2020-01-01..2026-07-16 |
As specified in backtest plan; available data period is 2018-01-01..2023-01-01 |
| Costs | $0.004/share, $1 min/order, 1% max commission, 0 bps slippage |
No explicit slippage modeled, which may overstate realizable results |
| # | Concern | Status |
|---|---|---|
| 1 | Weekly signal look-ahead | Mitigated by using completed weekly bars only and last available daily close for the week |
| 2 | Close-to-close execution timing | Needs care: signals use close data and rebalance at close, so live implementation may require next-close or MOC assumptions |
| 3 | Survivorship bias | Potential concern if the 20-stock universe is selected with knowledge of later market capitalizations or delistings |
| 4 | Corporate actions | Requires split/dividend-adjusted prices and consistent volume/dollar-volume history |
| 5 | Missing data | Signals/trades are skipped when required prices, volume, or execution data are missing |
| 6 | Transaction costs | Commissions included, but slippage is set to 0 bps and should be stress-tested |
The reported backtest is profitable, with total return of 64.90%, Sharpe of 0.80, Sortino of 0.93, and Calmar of 0.59. Drawdown is moderate at -13.57% with 12.43% volatility, while the low win rate of 36.14% is offset by larger average wins than losses and a profit factor of 1.55. The result is directionally consistent with a trend-following profile, but robustness should be checked with point-in-time universe construction, slippage stress, and out-of-sample testing.
| Metric | Value |
|---|---|
| Total Return | 64.90% |
| Sharpe | 0.80 |
| Sortino | 0.93 |
| Calmar | 0.59 |
| Max Drawdown | -13.57% |
| Volatility | 12.43% |
| Win Rate | 36.14% |
| Profit Factor | 1.55 |
| Total Trades | 1328 |
| Symbols | 20 (AAPL, ACON, AMZN, BETR, BRK-A, BRK-B, GOODO, GOOG, GOOGL, HOLO, +10 more) |
Backtests are historical simulations for research purposes only. They are not investment advice and do not guarantee future performance.