13/26 EMA crosslong
Backtest Results @ EURUSD β€’ 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 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).

Equity Curve

Backtest covers 9.6 years of EURUSD β€’ Daily () data, from December 2, 2015 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.

Equity Curve
Strategy
Asset
Strategy Drawdown
Asset Drawdown

So, we have backtested 13/26 EMA cross on 9.6 years of EURUSD β€’ Daily candles.Β This backtest resulted in 39 positions, with the average win rate of 31% and reward-risk ratio of 2.85.Β If you assume that 2.85 reward-to-risk ratio holds, you need a minimum win rate of 26.0 to be profitable. So you're looking good so far.Β However, 39 positions is a small sample size, so take the results with a huge grain of salt.Β The key metrics are as follows:

  1. Total Return: Total Return: 7.70% vs 11.30% for the asset
  2. Max Drawdown: Max Drawdown: -14.50% vs -23.30% for the asset
  3. Exposure: Exposure: 47.30% time in the market
  4. Win Rate: Win Rate: 31.0%, vs 26.0% minimum
  5. Reward/Risk Ratio: Reward/Risk Ratio: 2.85

With that exposure in mind, you can tell that for 47% time-in-market, you get 68.14% of the asset upside potential, and 62.23% of the asset downside potential.

13/26 EMA cross: enter a position when

All of the following: # "Mike"
  D Exponential Moving Average (13, 0, close) Crosses β†— D Exponential Moving Average (26, 0, close)

13/26 EMA cross: exit a position when

All of the following: # "Kilo"
  D Exponential Moving Average (13, 0, close) Crosses β†˜ D Exponential Moving Average (26, 0, close)

13/26 EMA cross @ EURUSD β€’ Daily (7.7%) backtest results explained by Alex C, Mike, Sarah

Alex C

Author

The backtest results show some concerning patterns that I would not trade with real money. Let me explain why.

The strategy produces very few trades - only 39 over 9.6 years, which is roughly 0.7 trades per month. This is problematic because the sample size is too small to make reliable statistical conclusions. The win rate of 31% is quite low, although it is compensated by a good risk/reward ratio of 2.85. The max losing streak of 10 trades in row is particularly worrying - this could destroy account if position sizing is not careful managed.

The performance metrics are also not convincing. The Sharpe ratio is negative at -0.91, indicating poor risk-adjusted returns. The strategy underperforms buy & hold (7.7% vs 11.3%) while only being exposed to market 47.3% of time. The max drawdown of -14.5% is significant given the low overall return. While the strategy shows better performance in recent periods (last 1-3 months), I would not put much weight on such short timeframes due to small sample size.

I must say in my professional opinion, this strategy needs significant improvements before real money trading. The core idea might have potential, but current implementation lacks statistical robustness. Consider adjusting parameters or adding filters to increase trade frequency and improve win rate.

Mike

Author

Yo fam, let me break down this EMA cross strategy! πŸš€ The numbers are kinda interesting, giving me some mixed feels but there's definitely potential here.

First off, that 31% win rate might look scary low, but check this out - when we win, we win BIG (3.87% average wins vs -1.36% average losses). That's almost a 3:1 reward-to-risk ratio! πŸ’Ž Plus we're actually above the minimal required win rate with a solid 30.74% leeway, which is pretty sweet for risk management. The strategy is beating the market in some timeframes, especially in shorter periods where we're seeing some juicy gains.

But here's where it gets a bit rough fam - that 10-trade losing streak is no joke 😬 and the -14.5% max drawdown could shake out paper hands. Market exposure at 47.3% means we're not over-trading, but only 0.7 trades per month might be too slow for us Wendy's warriors looking for more action. The negative Sharpe and Sortino ratios are kinda sus too, suggesting we might need to tune this bad boy up a bit.

πŸ€” Overall, I'd say this strategy has bones but needs some tweaking. Maybe add some filters to avoid those losing streaks? Still, with proper position sizing and diamond hands through the drawdowns, this could be worth a shot with a small portion of the portfolio. Not exactly YOLO material yet, but definitely has potential for some tendies! πŸ—

Sarah

Author

Madre de Dios, what a piece of garbage strategy! Let me tell you why this is complete waste of time.

First, only 39 trades in 9.6 years? That's like watching paint dry in slow motion! And with a pathetic 31% win rate, you're basically paying to lose money. The only thing saving this estrategy from complete disaster is the risk/reward ratio of 2.85, but even that's not enough to compensate for how terrible everything else is.

The most alarming thing - and this makes me want to throw my computer out the window - is that 10-trade losing streak. Imaginate losing 10 trades in a row! Even with good position sizing, this would destroy most trader's confidence and probably their account too. And your average losing streak is 3 trades - absolutely horrible!

The cherry on top of this disaster cake is that it underperforms buy & hold (7.7% vs 11.3%). Why would anyone waste their time with a strategy that makes less money than simply buying and holding? And those negative Sharpe and Sortino ratios? Por favor, this is amateur hour!

Listen, if you're seriously considering this strategy, you need to reconsider your life choices. It's mathematically viable because of the R/R ratio, but practically speaking, it's pure garbage.

Tabular metrics of 13/26 EMA cross backtested on EURUSD β€’ Daily

Total Trades39Net Profit7.7%Buy & Hold Profit11.3%
Win Rate31%Reward/Risk Ratio2.85Max Drawdown-14.5%
Asset Max Drawdown-23.3%Exposure47.3%Avg Candles in Position27.4
Sharpe Ratio-0.91Sortino Ratio-0.85Realized Volatility4.78%
Max Winning Streak3Avg Winning Streak1.3Max Losing Streak10
Avg Losing Streak3.0Avg Trades per Month0.7Avg Trades per Day0.0
Return Std Dev3.6Loss Std Dev1.0Win Std Dev4.8
Expectancy0.2Beta0.47

All backtests for 13/26 EMA cross

backtestexposurepeformance vs assetdrawdown vs assetwin%reward/risk
SPY β€’ 10 Minutes
60%(7.3%/14.0%) 0.52x(-10.2%/-20.7%) 0.49x342.3
BTCUSDT β€’ 1 Hour
55%(46.4%/66.0%) 0.70x(-32.0%/-30.6%) 1.05x342.6
EURUSD β€’ 1 Hour
53%(4.0%/7.5%) 0.53x(-7.6%/-9.0%) 0.84x312.7
SPY β€’ 1 Hour
62%(51.8%/109.4%) 0.47x(-17.6%/-35.1%) 0.50x431.9
BTCUSDT β€’ Daily
55%(1428.5%/1223.3%) 1.17x(-57.5%/-76.6%) 0.75x485.6
EURUSD β€’ Daily
47%(7.7%/11.3%) 0.68x(-14.5%/-23.3%) 0.62x312.9
SPY β€’ Daily
68%(324.3%/1315.7%) 0.25x(-33.7%/-56.7%) 0.59x452.4