50/200 SMA crosslongBacktest Results @ EURUSD • Daily
The Moving Average Crossover strategy uses two moving averages of different periods to generate buy and sell signals. It appoximates the idea of a trending market by using 2 SMAs, one short fast SMA(50) and another slow longer SMA(200). It buys whenever a short SMA(50) crosses up a long SMA(200), thereby implying that the direction of the market has changed. It sells once a short SMA(50) crosses down a long SMA(200). These are fairly long MAs, which means that this strategy is naturalyl meant to capture bigger moves, and thereby might not be a good fit for short time frames. But assumptions like that do not mean anything, because we've backested it! See youself.
Equity Curve
Backtest covers 9.6 years of EURUSD • Daily (Euro vs USD spot (Interactive Brokers)) data, from December 2, 2015 to July 10, 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 50/200 SMA cross on 9.6 years of EURUSD • Daily candles. This backtest resulted in 7 positions, with the average win rate of 71% and reward-risk ratio of 0.67. If you assume that 0.67 reward-to-risk ratio holds, you need a minimum win rate of 59.9 to be profitable. So you're looking good so far. However, 7 positions is a small sample size, so take the results with a huge grain of salt. The key metrics are as follows:
- Total Return: Total Return: 4.80% vs 10.80% for the asset
- Max Drawdown: Max Drawdown: -12.20% vs -23.30% for the asset
- Exposure: Exposure: 34.70% time in the market
- Win Rate: Win Rate: 71.0%, vs 59.9% minimum
- Reward/Risk Ratio: Reward/Risk Ratio: 0.67
With that exposure in mind, you can tell that for 35% time-in-market, you get 44.44% of the asset upside potential, and 52.36% of the asset downside potential.
50/200 SMA cross: enter a position when
All of the following: # "Papa" D Simple Moving Average (50, 0, close) Crosses ↗ D Simple Moving Average (200, 0, close)
50/200 SMA cross: exit a position when
All of the following: # "India" D Simple Moving Average (50, 0, close) Crosses ↘ D Simple Moving Average (200, 0, close)
50/200 SMA cross @ EURUSD • Daily (4.8%) backtest results explained by Alex C, Sarah
Alex C
AuthorThe backtest results for this 50/200 SMA cross strategy show some concerning patterns. With only 7 trades over 9.6 years, the sample size is way too small to make any statistically significant conclusions. This is like trying to predict weather patterns from just one week of data - mathematically unsound.
The strategy's performance metrics are not convincing. While the 71% win rate looks good at first glance, it is based on just 5 winning trades versus 2 losers. More problematic is the risk/reward ratio of 0.67, meaning average losses are larger than average wins. Combined with the -12.2% maximum drawdown and negative Sharpe/Sortino ratios, this suggests poor risk-adjusted returns. The strategy also underperforms buy & hold by more than 50% (4.8% vs 10.8%).
I would absolutely not recommend trading this strategy in its current form. The extremely low trade frequency (0.1 trades per month) makes it impossible to achieve statistical significance. One would need at least 30-50 trades minimum for meaningful analysis. Additionally, the negative risk-adjusted return metrics indicate the strategy is not mathematically sound from a risk management perspective. If you want to pursue this further, I would suggest optimizing the parameters to generate more signals while maintaining strict risk controls.
Sarah
AuthorMadre de dios, this is one of the most patetic backtests I've seen in my carrier! Only 7 trades in almost 10 years? Are you seriously considering this?
The statistics are completly useless becouse there are too few trades to make any meaningfull conclusions. Even a monkey throwing darts would give you more trades than that! And the performance is horrible - you're underperforming buy & hold by more than 50%.
Look at those drawdowns - 12.2% max drawdown for just 7 trades? That's completly unacceptable! The strategy is spending 65% of the time doing absolutly nothing, just sitting there like a lazy cat. And when it finally decides to trade, it produces worse results than simply buying and holding.
My recomendation? Throw this "strategy" in the garbage where it belongs. If you want to use moving averages, at least pick something that actually generates enough trades to be statistically relevant. This is just a waste of computing power.
Tabular metrics of 50/200 SMA cross backtested on EURUSD • Daily
| Total Trades | 7 | Net Profit | 4.8% | Buy & Hold Profit | 10.8% |
| Win Rate | 71% | Reward/Risk Ratio | 0.67 | Max Drawdown | -12.2% |
| Asset Max Drawdown | -23.3% | Exposure | 34.7% | Avg Candles in Position | 115.3 |
| Sharpe Ratio | -0.27 | Sortino Ratio | -0.20 | Realized Volatility | 2.80% |
| Max Winning Streak | 3 | Avg Winning Streak | 1.7 | Max Losing Streak | 1 |
| Avg Losing Streak | 1.0 | Avg Trades per Month | 0.1 | Avg Trades per Day | 0.0 |
| Return Std Dev | 3.6 | Loss Std Dev | 2.7 | Win Std Dev | 1.8 |
| Expectancy | 0.2 | Beta | 0.28 |
All backtests for 50/200 SMA cross
| backtest | exposure | peformance vs asset | drawdown vs asset | win% | reward/risk |
|---|---|---|---|---|---|
BTCUSDT • 1 Minute | 57% | (5.4%/8.9%) 0.61x | (-2.0%/-1.9%) 1.05x | 39 | 5.4 |
EURUSD • 1 Minute | 61% | (-1.1%/-1.0%) 1.10x | (-1.2%/-1.2%) 1.00x | 20 | 1.1 |
GLD • 1 Minute | 52% | (1.7%/0.0%) Infinityx | (-2.5%/-5.5%) 0.45x | 36 | 2.5 |
NVDA • 1 Minute | 61% | (1.2%/16.7%) 0.07x | (-7.9%/-4.4%) 1.80x | 28 | 2.9 |
SPY • 1 Minute | 60% | (0.5%/4.6%) 0.11x | (-2.5%/-2.1%) 1.19x | 33 | 2.3 |
TSLA • 1 Minute | 47% | (6.6%/-10.3%) -0.64x | (-11.2%/-21.4%) 0.52x | 39 | 2.1 |
WMT • 1 Minute | 41% | (-0.5%/-5.4%) 0.09x | (-3.9%/-6.4%) 0.61x | 29 | 2.4 |
BTCUSDT • 10 Minutes | 57% | (18.2%/22.4%) 0.81x | (-8.6%/-12.1%) 0.71x | 41 | 3.1 |
EURUSD • 10 Minutes | 55% | (2.5%/5.8%) 0.43x | (-2.2%/-4.3%) 0.51x | 38 | 2.4 |
GLD • 10 Minutes | 58% | (26.1%/43.7%) 0.60x | (-5.9%/-8.3%) 0.71x | 54 | 3.1 |
NVDA • 10 Minutes | 57% | (5.0%/32.9%) 0.15x | (-33.4%/-42.8%) 0.78x | 44 | 1.4 |
SPY • 10 Minutes | 60% | (6.6%/14.3%) 0.46x | (-13.4%/-20.7%) 0.65x | 41 | 1.9 |
TSLA • 10 Minutes | 47% | (18.4%/59.0%) 0.31x | (-34.8%/-55.3%) 0.63x | 41 | 1.9 |
WMT • 10 Minutes | 60% | (37.4%/40.1%) 0.93x | (-10.3%/-23.8%) 0.43x | 62 | 1.8 |
BTCUSDT • 1 Hour | 56% | (36.4%/68.2%) 0.53x | (-31.3%/-30.6%) 1.02x | 43 | 2.2 |
EURUSD • 1 Hour | 50% | (6.9%/6.8%) 1.01x | (-5.7%/-9.0%) 0.63x | 42 | 2.4 |
GLD • 1 Hour | 60% | (35.8%/117.6%) 0.30x | (-26.6%/-22.2%) 1.20x | 36 | 3.0 |
NVDA • 1 Hour | 61% | (783.4%/3126.3%) 0.25x | (-51.4%/-68.0%) 0.76x | 52 | 3.5 |
SPY • 1 Hour | 64% | (85.7%/106.7%) 0.80x | (-19.0%/-35.1%) 0.54x | 61 | 2.3 |
TSLA • 1 Hour | 55% | (2930.2%/1395.5%) 2.10x | (-38.7%/-75.1%) 0.52x | 56 | 6.0 |
WMT • 1 Hour | 60% | (33.6%/138.2%) 0.24x | (-28.4%/-26.9%) 1.06x | 50 | 1.6 |
BTCUSDT • Daily | 59% | (638.7%/1337.5%) 0.48x | (-61.1%/-76.6%) 0.80x | 83 | 7.3 |
EURUSD • Daily | 35% | (4.8%/10.8%) 0.44x | (-12.2%/-23.3%) 0.52x | 71 | 0.7 |
GLD • Daily | 61% | (242.9%/595.1%) 0.41x | (-36.4%/-45.3%) 0.80x | 46 | 6.4 |
NVDA • Daily | 65% | (83183.3%/373678.5%) 0.22x | (-57.1%/-90.0%) 0.63x | 77 | 16.0 |
SPY • Daily | 72% | (1127.3%/1316.3%) 0.86x | (-32.5%/-56.7%) 0.57x | 87 | 3.8 |
TSLA • Daily | 57% | (3139.0%/24185.2%) 0.13x | (-65.4%/-75.0%) 0.87x | 38 | 25.3 |
WMT • Daily | 64% | (1143.9%/13022.2%) 0.09x | (-57.1%/-50.6%) 1.13x | 39 | 8.1 |