Backtest covers 4.8 years of PLTR β’ 1 Hour (Palantir Technologies Inc.) data, from September 30, 2020 to July 31, 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 Parabolic SAR flip on 4.8 years of PLTR β’ 1 Hour candles.Β This backtest resulted in 314 positions, with the average win rate of 42% and reward-risk ratio of 2.05.Β If you assume that 2.05 reward-to-risk ratio holds, you need a minimum win rate of 32.8 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 55% time-in-market, you get 36.87% of the asset upside potential, and 89.26% of the asset downside potential.
All of the following: # India 60min Parabolic SAR (0.02, 0.02, 0.2, 0) < 60min Chart(close)
Exits as soon as None of the entry conditions are true any more.
The backtest shows some interesting patterns, but I have several concerns about the strategy's robustness. The win rate of 42% combined with a 2.05 risk/reward ratio mathematically makes sense - it's well above the minimal sufficient win rate of 32.8%. This is actually quite good.
However, the maximum drawdown of 77.3% is extremely problematic. No professional trader would accept such a high drawdown - it's simply too risky. The strategy also underperforms buy & hold significantly (538% vs 1459%), while still exposing you to substantial risk. The Sharpe ratio of 0.50 and Sortino of 0.24 are both quite poor, indicating bad risk-adjusted returns.
I notice the strategy produces relatively few trades - only 0.4 per day on average. This makes me worry about statistical significance, even though we have 314 trades total over the period. The correlation with the underlying asset is 0.68, which suggests this strategy is basically just giving you leveraged exposure to PLTR's movements rather than finding truly independent trading opportunities. In my experience, you want correlation below 0.3 for a truly robust strategy.
Total Trades | 314 | Net Profit | 538.0% | Buy & Hold Profit | 1459.0% |
Win Rate | 42% | Reward/Risk Ratio | 2.05 | Max Drawdown | -77.3% |
Asset Max Drawdown | -86.6% | Exposure | 54.9% | Avg Candles in Position | 13.8 |
Sharpe Ratio | 0.50 | Sortino Ratio | 0.24 | Realized Volatility | 46.10% |
Max Winning Streak | 5 | Avg Winning Streak | 1.7 | Max Losing Streak | 9 |
Avg Losing Streak | 2.5 | Avg Trades per Month | 10.7 | Avg Trades per Day | 0.4 |
Return Std Dev | 6.8 | Loss Std Dev | 2.5 | Win Std Dev | 7.4 |
Expectancy | 0.3 | Beta | 0.49 |
backtest | exposure | peformance vs asset | drawdown vs asset | win% | reward/risk |
---|---|---|---|---|---|
BTCUSDT β’ 1 Minute | 55% | (-2.7%/0.5%) -5.40x | (-3.4%/-4.4%) 0.77x | 36 | 1.5 |
EURUSD β’ 1 Minute | 55% | (-1.7%/-2.7%) 0.63x | (-1.9%/-3.3%) 0.58x | 37 | 1.3 |
GLD β’ 1 Minute | 56% | (-4.4%/-0.9%) 4.89x | (-4.9%/-4.8%) 1.02x | 41 | 1.1 |
NVDA β’ 1 Minute | 56% | (11.3%/20.6%) 0.55x | (-3.2%/-5.3%) 0.60x | 40 | 2.0 |
PLTR β’ 1 Minute | 56% | (-4.0%/10.4%) -0.38x | (-8.6%/-12.9%) 0.67x | 38 | 1.5 |
SPY β’ 1 Minute | 58% | (1.4%/4.0%) 0.35x | (-2.0%/-1.5%) 1.33x | 41 | 1.6 |
TSLA β’ 1 Minute | 55% | (-5.0%/-9.9%) 0.51x | (-11.0%/-15.9%) 0.69x | 38 | 1.5 |
WMT β’ 1 Minute | 55% | (-0.8%/-0.7%) 1.14x | (-2.9%/-5.1%) 0.57x | 37 | 1.6 |
BTCUSDT β’ 10 Minutes | 57% | (3.2%/4.7%) 0.68x | (-10.6%/-11.7%) 0.91x | 39 | 1.6 |
EURUSD β’ 10 Minutes | 56% | (-1.3%/0.6%) -2.17x | (-2.3%/-3.6%) 0.64x | 40 | 1.4 |
GLD β’ 10 Minutes | 57% | (22.1%/37.4%) 0.59x | (-8.4%/-8.3%) 1.01x | 46 | 1.6 |
NVDA β’ 10 Minutes | 58% | (24.3%/45.0%) 0.54x | (-28.0%/-42.8%) 0.65x | 44 | 1.4 |
PLTR β’ 10 Minutes | 60% | (121.1%/459.2%) 0.26x | (-45.7%/-46.5%) 0.98x | 47 | 1.5 |
SPY β’ 10 Minutes | 59% | (7.9%/14.1%) 0.56x | (-16.1%/-20.7%) 0.78x | 44 | 1.4 |
TSLA β’ 10 Minutes | 56% | (86.8%/24.4%) 3.56x | (-30.8%/-55.3%) 0.56x | 43 | 1.7 |
WMT β’ 10 Minutes | 58% | (37.0%/38.7%) 0.96x | (-12.4%/-23.8%) 0.52x | 45 | 1.7 |
BTCUSDT β’ 1 Hour | 55% | (40.1%/65.5%) 0.61x | (-25.5%/-30.6%) 0.83x | 42 | 1.6 |
EURUSD β’ 1 Hour | 55% | (-3.2%/3.5%) -0.91x | (-7.5%/-9.0%) 0.83x | 39 | 1.5 |
GLD β’ 1 Hour | 55% | (61.4%/118.5%) 0.52x | (-21.7%/-22.2%) 0.98x | 43 | 1.8 |
NVDA β’ 1 Hour | 58% | (1284.1%/3304.6%) 0.39x | (-42.2%/-68.0%) 0.62x | 47 | 1.8 |
PLTR β’ 1 Hour | 55% | (538.0%/1459.0%) 0.37x | (-77.3%/-86.6%) 0.89x | 42 | 2.0 |
SPY β’ 1 Hour | 61% | (70.4%/104.7%) 0.67x | (-14.9%/-35.1%) 0.42x | 45 | 1.6 |
TSLA β’ 1 Hour | 56% | (5558.2%/1240.0%) 4.48x | (-40.4%/-75.1%) 0.54x | 44 | 2.4 |
WMT β’ 1 Hour | 57% | (100.4%/142.7%) 0.70x | (-18.3%/-26.9%) 0.68x | 43 | 1.8 |
BTCUSDT β’ Daily | 57% | (379.6%/1339.3%) 0.28x | (-68.0%/-76.6%) 0.89x | 43 | 2.3 |
EURUSD β’ Daily | 55% | (-1.5%/8.0%) -0.19x | (-17.8%/-23.3%) 0.76x | 37 | 1.7 |
GLD β’ Daily | 57% | (301.4%/585.6%) 0.51x | (-23.7%/-45.3%) 0.52x | 46 | 1.9 |
NVDA β’ Daily | 59% | (14739.3%/417479.9%) 0.04x | (-76.5%/-90.0%) 0.85x | 46 | 2.0 |
PLTR β’ Daily | 57% | (559.1%/1476.3%) 0.38x | (-50.4%/-84.9%) 0.59x | 49 | 2.7 |
SPY β’ Daily | 65% | (117.1%/1354.3%) 0.09x | (-48.3%/-56.7%) 0.85x | 47 | 1.4 |
TSLA β’ Daily | 57% | (440.9%/25131.3%) 0.02x | (-75.3%/-75.0%) 1.00x | 37 | 2.6 |
WMT β’ Daily | 59% | (476.7%/10620.7%) 0.04x | (-60.7%/-50.6%) 1.20x | 45 | 1.6 |