This strategy enters once price action beraks through the range of the last 20 candles, while accompanied with elevated trading volume. It exits once price closes below an SMA(20). The idea is to follow trends, riding momentum confirmed by volume.
Backtest covers 12.5 months of WMT β’ 10 Minutes (Walmart Inc.) data, from July 16, 2024 to July 25, 2025.
Equity curve is the strategy's performance over time. You should compare it to the asset's Buy & Hold performance. In general, you want the blue area to be well above the gray area.
Drawdown is how much losses (realized or unrealized) the strategy has had if compared to the highest equity peak. Compare this to the asset's drawdown to see whether your strategy does a decent job of isolating you from downside volatility. In general, the red area must be well within the gray area.
So, we have backtested Range breakout on 12.5 months of WMT β’ 10 Minutes candles.Β This backtest resulted in 209 positions, with the average win rate of 41% and reward-risk ratio of 2.10.Β If you assume that 2.10 reward-to-risk ratio holds, you need a minimum win rate of 32.3 to be profitable. So you're looking good so far.Β The key metrics are as follows:
With that exposure in mind, you can tell that for 32% time-in-market, you get 58.73% of the asset upside potential, and 22.27% of the asset downside potential.
All of the following: # Papa 10min Chart(high) > 10min Range (20, 0), High (1 candles ago) All of the following: (within 5 candles) 10min Relative Volume (20, SMA, 1) > 1.5
All of the following: # Delta 10min Chart(close) < 10min Range (20, 0), Middle
The results look quite solid from mathematical perspective. I see a few interesting patterns here which make me think this strategy has good potential.
First thing that catches my eye is the Risk/Reward ratio of 2.10 combined with 41% win rate. This is mathematically viable setup - you need only 32.3% win rate to break even, and you are achieving 41%. That's quite good margin of safety. The win rate leeway of 40.68 is significant enough to account for potential market changes without breaking the strategy.
However, I notice some concerning things in the data. The strategy underperforms buy & hold (23.2% vs 39.5%), which is not optimal. Also the maximum drawdown of -5.3% seems bit too optimistic for such long backtest period - I would expect higher drawdowns in real trading conditions. The correlation of 0.55 to underlying asset suggests strategy might not provide enough diversification benefit.
I would recommend to test this on different time periods and maybe add some position sizing rules. The average of 1.1 trades per day is good - not too frequent to make commission costs problem, but enough trades to have statistical significance. Just make sure to account for spread and commission in your real trading calculations.
Total Trades | 209 | Net Profit | 23.2% | Buy & Hold Profit | 39.5% |
Win Rate | 41% | Reward/Risk Ratio | 2.10 | Max Drawdown | -5.3% |
Asset Max Drawdown | -23.8% | Exposure | 32.3% | Avg Candles in Position | 14.4 |
Sharpe Ratio | 1.48 | Sortino Ratio | 2.65 | Realized Volatility | 11.57% |
Max Winning Streak | 3 | Avg Winning Streak | 1.5 | Max Losing Streak | 6 |
Avg Losing Streak | 2.2 | Avg Trades per Month | 33.5 | Avg Trades per Day | 1.1 |
Return Std Dev | 0.9 | Loss Std Dev | 0.4 | Win Std Dev | 0.9 |
Expectancy | 0.3 | Beta | 0.25 |
backtest | exposure | peformance vs asset | drawdown vs asset | win% | reward/risk |
---|---|---|---|---|---|
BTCUSDT β’ 1 Minute | 26% | (0.4%/-0.5%) -0.80x | (-2.3%/-4.5%) 0.51x | 46 | 1.3 |
EURUSD β’ 1 Minute | 22% | (-0.5%/0.9%) -0.56x | (-0.6%/-0.7%) 0.86x | 22 | 2.8 |
GLD β’ 1 Minute | 32% | (0.6%/-1.4%) -0.43x | (-1.9%/-4.1%) 0.46x | 38 | 1.8 |
NVDA β’ 1 Minute | 25% | (7.8%/20.4%) 0.38x | (-3.7%/-5.3%) 0.70x | 34 | 3.0 |
PLTR β’ 1 Minute | 28% | (1.3%/15.0%) 0.09x | (-5.4%/-12.9%) 0.42x | 36 | 1.9 |
SPY β’ 1 Minute | 32% | (1.6%/6.6%) 0.24x | (-1.1%/-1.5%) 0.73x | 35 | 2.4 |
TSLA β’ 1 Minute | 26% | (0.7%/-0.2%) -3.50x | (-12.8%/-19.2%) 0.67x | 35 | 1.9 |
WMT β’ 1 Minute | 31% | (-0.5%/3.3%) -0.15x | (-3.2%/-5.1%) 0.63x | 32 | 2.0 |
BTCUSDT β’ 10 Minutes | 33% | (10.5%/14.3%) 0.73x | (-4.9%/-12.1%) 0.40x | 36 | 2.4 |
EURUSD β’ 10 Minutes | 23% | (1.1%/1.8%) 0.61x | (-1.2%/-4.3%) 0.28x | 39 | 1.8 |
GLD β’ 10 Minutes | 38% | (9.4%/35.8%) 0.26x | (-5.4%/-8.3%) 0.65x | 37 | 2.2 |
NVDA β’ 10 Minutes | 30% | (19.8%/37.4%) 0.53x | (-28.5%/-42.8%) 0.67x | 46 | 1.4 |
PLTR β’ 10 Minutes | 31% | (43.5%/467.7%) 0.09x | (-32.3%/-46.5%) 0.69x | 40 | 1.9 |
SPY β’ 10 Minutes | 33% | (5.1%/13.1%) 0.39x | (-9.7%/-20.7%) 0.47x | 39 | 1.8 |
TSLA β’ 10 Minutes | 28% | (30.7%/25.4%) 1.21x | (-21.4%/-55.3%) 0.39x | 40 | 1.9 |
WMT β’ 10 Minutes | 32% | (23.2%/39.5%) 0.59x | (-5.3%/-23.8%) 0.22x | 41 | 2.1 |
BTCUSDT β’ 1 Hour | 34% | (0.5%/70.3%) 0.01x | (-18.7%/-30.6%) 0.61x | 34 | 2.0 |
EURUSD β’ 1 Hour | 30% | (1.6%/7.1%) 0.23x | (-6.8%/-9.0%) 0.76x | 34 | 2.1 |
GLD β’ 1 Hour | 38% | (39.3%/122.5%) 0.32x | (-19.5%/-22.2%) 0.88x | 39 | 2.2 |
NVDA β’ 1 Hour | 44% | (555.6%/3243.4%) 0.17x | (-52.5%/-68.0%) 0.77x | 46 | 2.1 |
PLTR β’ 1 Hour | 38% | (449.7%/1466.7%) 0.31x | (-56.3%/-86.6%) 0.65x | 43 | 2.4 |
SPY β’ 1 Hour | 36% | (28.0%/107.0%) 0.26x | (-17.4%/-35.1%) 0.50x | 40 | 2.0 |
TSLA β’ 1 Hour | 39% | (1353.0%/1305.7%) 1.04x | (-40.8%/-75.1%) 0.54x | 39 | 3.1 |
WMT β’ 1 Hour | 33% | (60.9%/145.2%) 0.42x | (-15.7%/-26.9%) 0.58x | 39 | 2.4 |
BTCUSDT β’ Daily | 35% | (549.0%/1346.8%) 0.41x | (-54.7%/-76.6%) 0.71x | 47 | 3.3 |
GLD β’ Daily | 32% | (83.3%/592.8%) 0.14x | (-21.7%/-45.3%) 0.48x | 48 | 1.8 |
NVDA β’ Daily | 32% | (6469.1%/396269.9%) 0.02x | (-55.8%/-90.0%) 0.62x | 50 | 2.7 |
SPY β’ Daily | 22% | (90.1%/1344.4%) 0.07x | (-15.9%/-56.7%) 0.28x | 49 | 2.3 |
TSLA β’ Daily | 30% | (2791.1%/24273.6%) 0.11x | (-42.7%/-75.0%) 0.57x | 42 | 4.8 |
WMT β’ Daily | 30% | (30.4%/10116.3%) 0.00x | (-67.6%/-50.6%) 1.34x | 39 | 1.8 |