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 exponential moving averages, one short fast EMA(13) and another slow longer EMA(26). It buys whenever a short EMA(13) crosses up a long EMA(26), thereby implying that the direction of the market has changed. It sells once a short EMA(13) crosses down a long EMA(26).
Backtest covers 32.4 years of SPY β’ Daily () data, from January 29, 1993 to July 3, 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 13/26 EMA cross on 32.4 years of SPY β’ Daily candles.Β This backtest resulted in 125 positions, with the average win rate of 45% and reward-risk ratio of 2.44.Β If you assume that 2.44 reward-to-risk ratio holds, you need a minimum win rate of 29.1 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 68% time-in-market, you get 24.65% of the asset upside potential, and 59.44% of the asset downside potential.
All of the following: # "Mike" D Exponential Moving Average (13, 0, close) Crosses β D Exponential Moving Average (26, 0, close)
All of the following: # "Kilo" D Exponential Moving Average (13, 0, close) Crosses β D Exponential Moving Average (26, 0, close)
The backtest results show some interesting metrics, but I am not very convinced about this strategy's real-world applicability. Let me explain why.
The strategy shows decent risk metrics with a 2.44 risk/reward ratio and good win rate leeway of 44.71% above the minimal required win rate. However, the overall performance significantly underperforms buy & hold (324.3% vs 1315.7%) over this long 32-year period. This is problematic since we are trading SPY, which has strong upward bias. The strategy's market exposure of 68.1% means we are missing out on significant upside moves.
What worries me most is the low trading frequency - only 0.6 trades per month on average. With just 125 trades over 32 years, the statistical significance is questionable. The max drawdown of -33.7% is also concerning, especially given the limited number of trades. The Sharpe ratio of 0.12 is quite poor, indicating the strategy is not delivering good risk-adjusted returns. I would want to see at least 0.5 here for a long-term strategy.
My recommendation would be to either modify the strategy to increase trade frequency while maintaining the positive risk/reward characteristics, or look for different entry/exit conditions altogether. The current implementation, despite some positive metrics, does not appear robust enough for real trading.
Yo fam, let me break down this EMA cross strategy on SPY! π
This is one of those OG strategies that's been around forever, and I can see why. We're looking at a solid 324% gain over 32 years, which isn't gonna get us a Lambo tomorrow, but it's definitely better than my Wendy's paycheck! The win rate is sitting at 45% with a juicy 2.44 risk/reward ratio - that's actually pretty sweet because we're making more on winners than we're losing on the L's. πͺ
The thing that's got me hyped is that 44.7% win rate leeway - means we've got tons of room for error and the strategy would still be profitable. That's like having a safety net while walking on the moon! But keeping it real, the 33.7% max drawdown might make some paper hands shake. Though compared to SPY's raw 56.7% drawdown, we're actually protecting our tendies better. π
Only bummer is we're underperforming buy & hold (1315% vs our 324%), but hey, we're only exposed to the market 68% of the time, so we're taking way less risk. Plus those recent returns are looking spicy - 40.7% in the last year? That's what I'm talking about! π₯ Would I YOLO my life savings into this? Probably not, but it's definitely worth keeping in the strategy toolkit, especially for managing risk in choppy markets.
Madre de Dios, this strategy is a complete disaster! I can't believe someone would even consider trading this garbage. Let me tell you why this is terrible.
First of all, the strategy severely underperforms buy & hold - 324% vs 1315% over 32 years? That's pathetic! You'd be better off putting your money under your pillow. The market exposure of 68% means you're missing out on a third of the potential gains, while still eating all that risk.
The win rate is absolutely horrible - 45%? Even with a decent risk/reward ratio of 2.44, this is just barely keeping the strategy's head above water. Yes, you have some "leeway" above minimal win rate, but who cares when the overall performance is so mediocre? Having 7 consecutive losing trades is just waiting to destroy someone's account or their nerve.
And let me tell you about those risk metrics - a Sharpe ratio of 0.12 is embarassingly bad! This means you're taking on enormous risk for minimal returns. The 33.7% drawdown is just unaccectable for such poor returns.
The only slightly positive thing I can see is the recent performance in the last 1-2 years, but this is probably just luck and market conditions. Any monkey could have made money in this bull market.
My advice? Delete this strategy and start over. This is amateur hour trading at its finest.
Total Trades | 125 | Net Profit | 324.3% | Buy & Hold Profit | 1315.7% |
Win Rate | 45% | Reward/Risk Ratio | 2.44 | Max Drawdown | -33.7% |
Asset Max Drawdown | -56.7% | Exposure | 68.1% | Avg Candles in Position | 43.5 |
Sharpe Ratio | 0.12 | Sortino Ratio | 0.44 | Realized Volatility | 10.59% |
Max Winning Streak | 4 | Avg Winning Streak | 1.6 | Max Losing Streak | 7 |
Avg Losing Streak | 2.0 | Avg Trades per Month | 0.6 | Avg Trades per Day | 0.0 |
Return Std Dev | 6.3 | Loss Std Dev | 2.0 | Win Std Dev | 6.5 |
Expectancy | 0.5 | Beta | 0.37 |
backtest | exposure | peformance vs asset | drawdown vs asset | win% | reward/risk |
---|---|---|---|---|---|
SPY β’ 10 Minutes | 60% | (7.3%/14.0%) 0.52x | (-10.2%/-20.7%) 0.49x | 34 | 2.3 |
BTCUSDT β’ 1 Hour | 55% | (46.4%/66.0%) 0.70x | (-32.0%/-30.6%) 1.05x | 34 | 2.6 |
EURUSD β’ 1 Hour | 53% | (4.0%/7.5%) 0.53x | (-7.6%/-9.0%) 0.84x | 31 | 2.7 |
SPY β’ 1 Hour | 62% | (51.8%/109.4%) 0.47x | (-17.6%/-35.1%) 0.50x | 43 | 1.9 |
BTCUSDT β’ Daily | 55% | (1428.5%/1223.3%) 1.17x | (-57.5%/-76.6%) 0.75x | 48 | 5.6 |
EURUSD β’ Daily | 47% | (7.7%/11.3%) 0.68x | (-14.5%/-23.3%) 0.62x | 31 | 2.9 |
SPY β’ Daily | 68% | (324.3%/1315.7%) 0.25x | (-33.7%/-56.7%) 0.59x | 45 | 2.4 |