How did EMA 12/26 Crossover perform in Bull Run 2017 H1?

On real historical data, EMA 12/26 Crossover returned +1.5% with a maximum drawdown of -1.8%. These results are based on a historical backtest under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in China Sideways (2015 H2)?

On real historical data, EMA 12/26 Crossover returned -0.4% with a maximum drawdown of -4.1%. These results are based on a historical backtest under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in Fed-Bear 2022 H2?

On real historical data, EMA 12/26 Crossover returned -3.0% with a maximum drawdown of -11.8%. These results are based on a historical backtest under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in Lehman GFC (2008)?

On real historical data, EMA 12/26 Crossover returned -6.1% with a maximum drawdown of -6.1%. These results are based on a historical backtest under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in COVID Crash (Feb-Aug 2020)?

On real historical data, EMA 12/26 Crossover returned -2.9% with a maximum drawdown of -3.3%. These results are based on a historical backtest under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in Volmageddon (Feb 2018)?

On real historical data, EMA 12/26 Crossover returned -4.3% with a maximum drawdown of -5.1%. These results are based on a historical backtest under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in Slow Stagflation (Synthetic)?

Across 50 simulated variants, EMA 12/26 Crossover returned -5.6% with a maximum drawdown of -10.5%. These results are based on model-driven scenario simulation under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in Sustained Low-Vol Grind (Synthetic)?

Across 50 simulated variants, EMA 12/26 Crossover returned +10.7% with a maximum drawdown of -3.9%. These results are based on model-driven scenario simulation under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in Slow Crash, No Recovery (Synthetic)?

Across 50 simulated variants, EMA 12/26 Crossover returned -4.1% with a maximum drawdown of -6.8%. These results are based on model-driven scenario simulation under simplified assumptions and do not constitute a forecast or recommendation.

How did EMA 12/26 Crossover perform in Controlled Whipsaw (Synthetic)?

Across 50 simulated variants, EMA 12/26 Crossover returned +0.4% with a maximum drawdown of -6.9%. These results are based on model-driven scenario simulation under simplified assumptions and do not constitute a forecast or recommendation.

Strategy Report

EMA 12/26 Crossover

Q: Is EMA 12/26 crossover better than SMA crossover? Backtest simulation results.

In model-based simulations across 206 scenario runs, EMA 12/26 Crossover scored 73/100 on robustness. Worst-case simulated drawdown (P95): -2.0%. Robustness Score: 73/100. This strategy demonstrates solid stability across simulated scenarios. Key risk: WCDD₉₅ of -2%. These results are based on synthetic data under simplified assumptions and do not constitute a forecast or recommendation.

Enter when 12-day EMA crosses above 26-day EMA. Exit on cross below.

trend-followingmoving-averageshort-term

Strategy Logic & Backtest Setup

Buy when EMA(12) crosses above EMA(26). Sell when EMA(12) crosses below EMA(26). 3% stop loss.

Showing the score, regime breakdown and weakest spot.

Robustness

Strong

206 scenarios · SPY

Robustness Score: 73/100. This strategy demonstrates solid stability across simulated scenarios. Key risk: WCDD₉₅ of -2%.

Typical Return

-1.7%

median across cases

Worst Case

-8.9%

5th percentile

Win Rate

30%

3/10 cases

How does this strategy behave in different market regimes?

Model results from 206 simulation runs across curated historical market phases and synthetic stress tests, aggregated by market regime.

Values are model estimates: average and range (±1 standard deviation) from Monte Carlo variations across historical market phases and synthetic stress tests. Not a prediction of future performance, not investment advice.

Rising Market

Stocks & indices climb over weeks or months — like Bull Run 2017 or Tech Rally 2021.

Average+10.8%

Range+0.3% … +21.2%

Sample52 cases · 2 subtypes

Sideways Market

Market drifts directionless inside a range — like SPY 2015 or Range 2011–2012.

Average+1.3%

Range-7.7% … +10.3%

Sample102 cases · 2 subtypes

Calm Market

Low volatility, muted price action — like mid-2017 or pre-Lehman 2007.

Average+6.2%

Range-4.7% … +17.2%

Sample101 cases

High Volatility

Large daily swings, vol spikes — like the February 2018 vol shock.

Average-2.8%

Range-11.8% … +6.2%

Sample51 cases

Falling Market

Markets decline over an extended period — like Dotcom Bust 2001 or 2022 Bear Market.

Average-3.5%

Range-9.4% … +2.3%

Sample152 cases · 2 subtypes

Market Crash

Sudden sharp drawdowns, liquidity stress — like Lehman 2008 or COVID Crash 2020.

Average-5.0%

Range-6.5% … -3.6%

Sample3 cases · 2 subtypes

Aggregation note: Cases can contribute to multiple regimes — a crash counts as both "Market Crash" and "High Volatility", for example. Range combines within-subtype and between-subtype spread. Total 461 case contributions across 10 failure modes.

Weakest spot · Liquidity Stress

Your strategy returned -6.1% on average across liquidity crises. Increase slippage assumptions or avoid microcap/illiquid windows.

Model-based scenario simulation. All values are produced by computational market models — curated historical market phases and synthetic stress tests with Monte Carlo variations. They describe how the strategy behaves in the modelled scenarios, not future performance in live markets.

Not investment advice, not financial analysis under § 34b WpHG (German Securities Trading Act), not a recommendation to buy or sell. Past or simulated performance is not a reliable indicator of future results.

These results are based on model-driven simulations under simplified assumptions. They do not constitute a forecast, recommendation, or financial advice. Real market outcomes may differ significantly.

Case Studies

Strategy performance across curated market episodes — real historical periods plus synthetic stress scenarios. Each case is chosen to test a distinct failure mode of trading strategies.

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