13/26 EMA crosslong
Backtest-Ergebnisse @ EURUSD • Daily

Die Moving Average Crossover Strategie verwendet zwei gleitende Durchschnitte unterschiedlicher Perioden, um Kauf- und Verkaufssignale zu generieren. Sie nähert sich der Idee eines trendigen Marktes durch die Verwendung von 2 exponentiellen gleitenden Durchschnitten, einem kurzen schnellen EMA(13) und einem anderen langsamen längeren EMA(26). Sie kauft, wenn ein kurzer EMA(13) einen langen EMA(26) nach oben kreuzt, was impliziert, dass sich die Richtung des Marktes geändert hat. Sie verkauft, sobald ein kurzer EMA(13) einen langen EMA(26) nach unten kreuzt.

Eigenkapitalkurve

Der Backtest umfasst 9.6 years von EURUSD • Daily () Daten, von December 2, 2015 bis July 3, 2025.

Die Eigenkapitalkurve zeigt die Leistung der Strategie im Zeitverlauf. Sie sollten sie mit der Buy & Hold Performance des Assets vergleichen. Im Allgemeinen sollte der blaue Bereich deutlich über dem grauen Bereich liegen.

Drawdown zeigt, wie viel Verluste (realisiert oder nicht realisiert) die Strategie im Vergleich zum höchsten Eigenkapitalpeak hatte. Vergleichen Sie dies mit dem Drawdown des Assets, um zu sehen, ob Ihre Strategie eine anständige Arbeit leistet, Sie von Abwärtsvolatilität zu isolieren. Im Allgemeinen muss der rote Bereich gut innerhalb des grauen Bereichs liegen.

Eigenkapitalkurve
Strategie
Asset
Strategie Drawdown
Asset Drawdown

Also haben wir 13/26 EMA cross über 9.6 years von EURUSD • Daily Kerzen getestet. Dieser Backtest ergab 39 Positionen, mit einer durchschnittlichen Gewinnrate von 31% und einem Risiko-Rendite-Verhältnis von 2.85. Wenn Sie annehmen, dass das 2.85 Risiko-Rendite-Verhältnis gilt, benötigen Sie eine Mindestgewinnrate von 26.0, um profitabel zu sein. Sie stehen also gut da. Allerdings sind 39 Positionen eine kleine Stichprobe, nehmen Sie die Ergebnisse also mit einer großen Portion Skepsis. Die wichtigsten Metriken sind wie folgt:

  1. Gesamtrendite: Gesamtrendite: 7.70% vs 11.30% für das Asset
  2. Maximaler Drawdown: Maximaler Drawdown: -14.50% vs -23.30% für das Asset
  3. Exposition: Exposition: 47.30% Zeit im Markt
  4. Gewinnrate: Gewinnrate: 31.0%, vs 26.0% Minimum
  5. Risiko/Rendite-Verhältnis: Risiko/Rendite-Verhältnis: 2.85

Mit dieser Exposition können Sie erkennen, dass Sie bei 47% Marktzeit 68.14% des Asset-Aufwärtspotenzials und 62.23% des Asset-Abwärtspotenzials erhalten.

13/26 EMA cross: Position eingehen wenn

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

13/26 EMA cross: Position verlassen wenn

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

13/26 EMA cross @ EURUSD • Daily (7.7%) erklärt von Alex C, Mike, Sarah

Alex C

Autor

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

Autor

Yo fam, let me break down this EMA cross strategy! 🚀 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! 💎 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.

🤔 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! 🍗

Sarah

Autor

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.

Tabellarische Metriken von 13/26 EMA cross getestet auf EURUSD • Daily

Gesamttrades39Nettogewinn7.7%Buy & Hold Gewinn11.3%
Gewinnrate31%Risiko/Rendite-Verhältnis2.85Maximaler Drawdown-14.5%
Asset Maximaler Drawdown-23.3%Exposition47.3%Durchschn. Kerzen in Position27.4
Sharpe-Ratio-0.91Sortino-Ratio-0.85Realisierte Volatilität4.78%
Max. Gewinnserie3Durchschn. Gewinnserie1.3Max. Verlustserie10
Durchschn. Verlustserie3.0Durchschn. Trades pro Monat0.7Durchschn. Trades pro Tag0.0
Rendite Std Dev3.6Verlust Std Dev1.0Gewinn Std Dev4.8
Erwartungswert0.2Beta0.47

Alle Backtests für 13/26 EMA cross

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