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 4.8 years of PLTR β’ 1 Hour (Palantir Technologies Inc.) data, from September 30, 2020 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 4.8 years of PLTR β’ 1 Hour candles.Β This backtest resulted in 192 positions, with the average win rate of 43% and reward-risk ratio of 2.35.Β If you assume that 2.35 reward-to-risk ratio holds, you need a minimum win rate of 29.9 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 38% time-in-market, you get 30.66% of the asset upside potential, and 65.01% of the asset downside potential.
All of the following: # Papa 60min Chart(high) > 60min Range (20, 0), High (1 candles ago) All of the following: (within 5 candles) 60min Relative Volume (20, SMA, 1) > 1.5
All of the following: # Delta 60min Chart(close) < 60min Range (20, 0), Middle
The data shows some interesting patterns, but I have concerns about the strategy's robustness. While the R/R ratio of 2.35 and win rate leeway of 42.7% look mathematicaly solid, the max drawdown of 56.3% is too high for my taste. This indicates high risk exposure that could be problematic in real trading situations.
The market exposure of 37.8% combined with only 0.2 trades per day suggests this is a relatively selective strategy, which is good. However, the 11-trade losing streak is concerning - this could psychologicaly break many traders even if they follow the system perfectly. The low Sharpe ratio of 0.34 also indicates suboptimal risk-adjusted returns, especialy when compared to the buy & hold performance which outperformed the strategy by more than 3x.
From pure mathematical perspective, the strategy shows statistical edge with its 43% win rate against 29.9% minimal required win rate. But I would want to see how sensitive these metrics are to parameter changes - even small adjustments to the 20-period range or 1.5 volume threshold could dramaticaly impact performance. Before considering real money implementation, I would suggest extensive robustness testing across different market regimes.
Total Trades | 192 | Net Profit | 449.7% | Buy & Hold Profit | 1466.7% |
Win Rate | 43% | Reward/Risk Ratio | 2.35 | Max Drawdown | -56.3% |
Asset Max Drawdown | -86.6% | Exposure | 37.8% | Avg Candles in Position | 15.6 |
Sharpe Ratio | 0.34 | Sortino Ratio | 0.51 | Realized Volatility | 37.37% |
Max Winning Streak | 5 | Avg Winning Streak | 1.8 | Max Losing Streak | 11 |
Avg Losing Streak | 2.5 | Avg Trades per Month | 6.5 | Avg Trades per Day | 0.2 |
Return Std Dev | 6.1 | Loss Std Dev | 2.0 | Win Std Dev | 6.5 |
Expectancy | 0.4 | Beta | 0.38 |
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 |