Benchmarks & Relative Performance

Benchmarks & Relative Performance

A strategy that returned 20% sounds good. But if the asset itself went up 35% over the same period, you would have made more money by doing nothing -- just buying and holding. Without a benchmark to compare against, a raw return number has no context. You cannot tell whether the strategy added value or just rode the market.

This article explains what benchmarks are, how Simula uses buy-and-hold as the benchmark, and how metrics like alpha and beta measure your strategy's performance relative to the market.

Why You Need a Benchmark

A benchmark answers the question: "Compared to what?" Every strategy operates on a specific asset during a specific time period. The simplest alternative to your strategy is to buy that asset at the start and hold it until the end. If your strategy cannot beat that approach, the added complexity of entry conditions, exit conditions, and active management is not paying for itself.

This does not mean every strategy needs to beat buy-and-hold to be useful. A strategy that returns 15% while the asset returned 20% might still be valuable if it did so with significantly less risk -- smaller drawdowns, lower volatility, and smoother equity growth. The benchmark gives you a reference point for evaluating both return and risk.

Buy-and-Hold as the Benchmark

In Simula, the benchmark is always buy-and-hold of the same asset your strategy is trading. If you are backtesting a strategy on EUR/USD, the benchmark is buying EUR/USD at the start of the date range and holding it until the end. If you are testing on AAPL, the benchmark is buying AAPL and holding it.

This is the most direct comparison possible. It strips away all the complexity of your strategy and asks: did the active trading produce a better outcome than the passive alternative on the exact same asset over the exact same period?

Simula calculates and displays three benchmark metrics alongside your strategy's results: the buy-and-hold total return, the buy-and-hold annualized return, and the buy-and-hold max drawdown. You can see the delta between your strategy and the benchmark for each metric directly in the results summary.

Alpha -- Excess Return

Alpha measures how much your strategy returned beyond what the benchmark delivered, after adjusting for market exposure. It is the value your strategy added through its trading decisions rather than through market movement.

Positive alpha means the strategy outperformed the benchmark on a risk-adjusted basis. Negative alpha means it underperformed -- the benchmark would have been the better choice. An alpha of zero means the strategy's returns were fully explained by market movement, with no additional value from the active trading.

Alpha is annualized, so an alpha of 0.05 means the strategy added roughly 5 percentage points of return per year beyond what market exposure alone would explain. See the alpha article for the full calculation and worked examples.

Beta -- Market Sensitivity

Beta measures how sensitive your strategy's returns are to the benchmark's movements. It tells you how much of your strategy's behavior is driven by the underlying asset versus its own trading logic.

A beta of 1.0 means the strategy moves in lockstep with the asset. When the asset goes up 2%, the strategy goes up about 2%. A beta of 0.5 means the strategy captures about half the asset's movement -- it is less exposed to the market's swings. A beta of 1.5 means the strategy amplifies the asset's movement by 50%.

Beta below 1.0 is common for strategies that spend time out of the market -- when your strategy has no open position, it is not exposed to price movement, which dampens its correlation with the asset. A strategy that is in the market 50% of the time will naturally have a lower beta than one that is always invested.

Reading the Comparison

When you run a backtest in Simula, the results summary shows your strategy's metrics alongside the buy-and-hold metrics, with the difference (delta) highlighted. Here is how to interpret the comparison:

Total Return Delta

If your strategy returned +30% and buy-and-hold returned +20%, the delta is +10 percentage points. Your strategy outperformed. If the delta is negative, buy-and-hold won.

Drawdown Comparison

Return is only half the picture. Compare the max drawdown of your strategy against the benchmark's. A strategy that returned 25% with a 10% max drawdown is arguably better than buy-and-hold that returned 30% with a 40% max drawdown. The strategy earned slightly less but protected capital during the worst period.

The Risk-Adjusted Picture

The Sharpe ratio, Sortino ratio, and Calmar ratio combine return and risk into single numbers. These metrics help answer the question: "Was the strategy's return worth the risk it took?" A strategy that beats buy-and-hold on raw return but has a worse Sharpe ratio took on disproportionately more risk to earn that extra return.

When Beating the Benchmark Is Not the Goal

Not every strategy aims to maximize return above buy-and-hold. Some strategies prioritize capital preservation -- they aim to capture a portion of the upside while avoiding the worst drawdowns. A strategy that returns 15% while buy-and-hold returned 25% might still be the better choice for someone who cannot stomach a 30% drawdown along the way.

Similarly, short strategies and hedging strategies are designed to profit when the market falls. Comparing them against buy-and-hold during a bull market is misleading -- they are designed for different conditions. The benchmark comparison is most informative for long-biased strategies where the natural alternative is simply holding the asset.

Common Mistakes

Ignoring the Benchmark Entirely

A 40% return feels impressive until you check whether the asset itself returned 50%. Always look at the delta. If the strategy underperformed buy-and-hold, the active trading destroyed value rather than creating it.

Comparing Return Without Risk

A strategy that beat buy-and-hold by 5% but had triple the drawdown is not obviously better. Use alpha and risk-adjusted ratios to see whether the excess return justified the additional risk.

Cherry-Picking the Period

A strategy can beat buy-and-hold over one specific date range and lag behind on another. If you chose the date range because you already knew the strategy would perform well during that period, the comparison is meaningless. Test across longer periods that include multiple market conditions, or use out-of-sample testing to validate results on data the strategy was not designed on.

Where to Go Next

Alpha -- the full calculation and interpretation of excess return.

Beta -- understanding market sensitivity and exposure.

Total & Annualized Return -- the raw return numbers that benchmarks put in context.

Sharpe Ratio -- comparing risk-adjusted performance.

Max Drawdown -- the risk metric that benchmarks reveal.