#1 Stable Returns

Stable returns are one of the key indicators for evaluating the quality of a quantitative strategy. They represent the strategy’s ability to consistently generate profits during the backtest period. A truly robust quantitative strategy should not rely on a single market environment or specific opportunities, but rather be capable of delivering steady returns across various market conditions. Specifically, this includes the following aspects:

Consistent Return Growth
Stable returns imply that the strategy’s equity curve shows a relatively smooth and consistently upward trend, rather than experiencing sudden spikes or drops during specific periods. This steady growth indicates the strategy’s ability to capture opportunities amid different levels of market volatility, demonstrating long-term profitability. In contrast, an equity curve with excessive fluctuations often suggests higher risk or potential for significant losses in extreme market conditions.

Adaptability Across Diverse Market Environments
Stable returns also mean that the strategy performs well in bull, bear, and sideways markets. If a strategy only profits during a unidirectional market—either rising or falling—then a change in market conditions could quickly erode its profitability. Therefore, a truly stable strategy should be able to adapt to different environments and possess a certain level of risk resistance.

Avoidance of Dependence on a Single Factor or Pattern
Many strategies may appear profitable in backtests because they rely heavily on specific market factors or trading patterns. For example, during a certain period, a particular trend or event might drive returns, but once that factor disappears, the performance deteriorates significantly. Thus, stable returns require diversified sources of profit, enabling the strategy to identify opportunities in various market scenarios, rather than depending on a single factor or pattern.

Sustainable Alpha Generation
Stable returns are not just about achieving positive returns—they also mean the strategy can continuously generate excess returns (Alpha) beyond the market benchmark. Many strategies may seem effective in bull markets, but that may simply reflect overall market gains rather than true outperformance. Therefore, a strategy with stable returns should deliver above-benchmark returns even after accounting for market influences.

Low Return Volatility
Stable returns also indicate low volatility in the strategy’s backtested returns. Even if a strategy is profitable overall, highly volatile returns signal higher risk and a greater chance of severe future drawdowns. When evaluating stability, it’s important to consider return standard deviation or volatility to ensure the growth in returns is reliable and consistent.

Ability to Withstand Risk Events
Markets often face risk events such as economic crises, policy shifts, or geopolitical tensions. A strategy with stable returns can generally maintain relatively steady performance during such events—and may even benefit from them. This indicates the strategy has enough resilience and flexibility to respond to sudden market changes and seize new opportunities.

Long-Term Profitability
Stable returns should reflect not only short-term performance but also long-term profitability. In backtests, a good strategy should generate consistent returns over an extended time frame, avoiding scenarios where it performs exceptionally well in one period but poorly in others. Only with long-term profitability can a strategy be truly considered as delivering stable returns.

#2 Higher Sharpe Ratio

The Sharpe Ratio is a key metric for evaluating how much excess return a quantitative strategy can generate relative to the risk it takes. It is calculated by dividing the strategy’s average excess return (strategy return minus the risk-free rate) by the standard deviation (or volatility) of returns. In essence, the higher the Sharpe Ratio, the more excess return the strategy generates per unit of risk—indicating stronger risk-adjusted performance.

Why is the Sharpe Ratio so important?
The Sharpe Ratio is widely used to assess the quality of a quantitative strategy because it considers not only returns but also the volatility and risk associated with those returns. Unlike simply looking at absolute return rates, the Sharpe Ratio helps investors determine whether a strategy can provide more stable and reliable returns in real-world trading, and whether the risks involved are worth taking. As such, it offers a more comprehensive and realistic evaluation of a strategy’s performance.

How to interpret the Sharpe Ratio?

  • Above 1.0: This generally indicates good performance, meaning the strategy delivers relatively high returns per unit of risk. It’s considered a strategy worth considering.
  • Above 2.0: The strategy is considered excellent. It shows strong risk control and consistently attractive returns across different market conditions.
  • Below 1.0: This suggests the strategy’s returns do not sufficiently compensate for the risk taken. It may perform poorly in volatile environments, or its excess returns are inadequate to offset risks. Such strategies typically require further optimization or should be approached with caution.

How to improve the Sharpe Ratio?

  • Reduce volatility: One way to improve the Sharpe Ratio is by reducing the strategy’s volatility. This can be done through diversification, lowering leverage, or controlling position sizes. For example, allocating capital across different asset classes or strategies can effectively reduce overall volatility, thereby increasing the Sharpe Ratio.
  • Enhance excess returns: Improving the model, identifying more profitable trading signals, or increasing execution efficiency can boost the strategy’s excess returns. Accurately capturing market opportunities and avoiding impulsive trading behavior (e.g., chasing highs or panic selling) is key to increasing the Sharpe Ratio.
  • Implement strong risk management: Good risk management practices—such as stop-loss mechanisms and effective capital allocation—can help control downside risk and limit losses during backtesting. This contributes to higher overall Sharpe Ratios.

#3 Controllable Maximum Drawdown

Maximum drawdown reflects the worst loss a strategy experiences during the backtest period and is a key indicator of its risk tolerance. While returns are important for investors, avoiding significant losses is equally critical. Even if a strategy shows high returns in backtesting, an excessively large drawdown may signal substantial real-world risks—potentially resulting in unrecoverable capital losses. Therefore, maximum drawdown is a vital metric for evaluating a strategy’s risk profile.

Ideal Range for Maximum Drawdown
Generally, a good quantitative strategy should maintain a maximum drawdown within the 10%–20% range:

  • Below 10%: Indicates that the strategy is highly robust during backtesting, with excellent risk control. This is considered a very strong performance.
  • 10%–20%: This range is typically acceptable, suggesting the strategy manages risk and capital effectively amid market fluctuations.
  • Above 20%: If the maximum drawdown exceeds 20%, the strategy may require further optimization or a reevaluation of its risk management mechanisms, as such a level of drawdown could lead to significant losses in live trading.

How to Control Maximum Drawdown?

  • Strict Stop-Loss Mechanisms: Implementing well-defined stop-loss rules allows positions to be closed quickly during unfavorable market movements, preventing deeper losses. This helps avoid emotional trading and effectively limits drawdowns during backtests.
  • Diversification and Portfolio Management: Allocating capital across various asset classes, markets, and strategies reduces exposure to any single risk source, thereby lowering overall drawdown. A diversified portfolio mitigates the impact of poor performance in specific market conditions.
  • Dynamic Position Sizing: Adjusting position sizes based on market volatility and risk levels can help. For instance, reducing position sizes during periods of high volatility minimizes the pressure of losses during risky market phases.

While minimizing drawdown can enhance strategy stability, an excessive focus on low drawdowns may sacrifice return potential. The key lies in striking the right balance between returns and drawdown. In practice, investors choose strategies based on their own risk tolerance. For example, high-risk investors may accept larger drawdowns in pursuit of higher returns, while risk-averse investors prioritize controlling drawdowns.

In bull markets, with generally rising trends, strategies tend to experience smaller drawdowns. Still, even in such conditions, effective drawdown control is necessary to guard against losses from short-term corrections. In bear or sideways markets, the risks increase, and larger drawdowns are more likely. A well-designed strategy should maintain relatively small drawdowns in these environments, showcasing its resilience to adverse conditions.

#4 High Return-to-Drawdown Ratio

Often, we come across strategies that deliver extremely high returns in a short period, but once the market shifts, their maximum drawdown spikes just as quickly—like walking a tightrope, where a single misstep can lead to disaster. The return-to-drawdown ratio helps us identify strategies that not only pursue returns but also maintain control over risk. This ratio is calculated by dividing a strategy’s annualized return by its maximum drawdown. For example, if a strategy has a return-to-drawdown ratio of 2.0, it means that for every unit of risk (as measured by its worst loss), it delivers two units of return.

How to Interpret the Return-to-Drawdown Ratio

  • Ratio > 1.0: Indicates the strategy earns more than one unit of return for each unit of risk taken. In general, the higher the ratio, the better—especially when it exceeds 2.0, which suggests the strategy is robust, capable of generating returns while effectively controlling losses.
  • Ratio between 0.5 and 1.0: This range reflects an average performance. The strategy shows a decent balance between return and risk but doesn’t particularly stand out.
  • Ratio < 0.5: A cause for concern. It may indicate that the returns during periods of maximum drawdown are insufficient to cover the losses, suggesting the strategy performs poorly on a risk-adjusted basis.

How to View the Return-to-Drawdown Ratio in Practice

A high return-to-drawdown ratio is not automatically good—it’s just one metric among many. One shouldn’t blindly assume a strategy is the best simply because of a high ratio. In practice, this metric should be evaluated in conjunction with other indicators, since the market is complex and ever-changing. Relying on a single number can lead to misjudgments.

For instance, a strategy might have a return-to-drawdown ratio of 2.0, but a very low Sharpe ratio. This could suggest that while the strategy avoids deep drawdowns, its returns are highly volatile in certain extreme scenarios. Alternatively, the strategy might perform well during a bull market, producing an impressive return-to-drawdown ratio, but falter during bear markets—indicating it’s not as stable as it initially appears.

#5 High R-squared Value

The R-squared value is a metric that is often mentioned but easily overlooked, especially when evaluating the performance of quantitative strategies. It tells us the extent to which a strategy’s returns are correlated with a market benchmark. In other words, the higher the R-squared, the more closely the strategy’s performance tracks that of the benchmark.

What Does R-squared Mean?

R-squared is essentially a measure of fit, ranging from 0 to 1, and is sometimes expressed as a percentage. For example, if a strategy has an R-squared of 0.8 (or 80%), it means that 80% of the strategy’s return variance can be explained by movements in the benchmark index. The remaining 20% is due to the strategy’s own features or other non-market-related factors.

What Does a High R-squared Value Indicate?

When a strategy has a high R-squared value, it usually means its returns closely follow the market benchmark. In other words, the strategy’s performance is primarily influenced by the overall market trend. If the market performs well, the strategy is likely to perform well too—and vice versa. For investors aiming to align with the market and capture beta returns, this is a positive sign.

However, a high R-squared doesn’t mean the strategy lacks added value. In fact, even with a high R-squared, a strategy can still generate alpha—returns above the benchmark—through superior selection or timing. High R-squared simply indicates that the strategy follows the general market trend; whether it adds value beyond that requires further analysis using other metrics.

What About Low R-squared Values?

A low R-squared typically suggests that the strategy’s return fluctuations are not strongly related to the benchmark. Such strategies may operate based on unique logic or trading mechanisms, potentially performing well even when the overall market is declining—or diverging from the benchmark during rising markets. For investors pursuing absolute returns, this can be attractive, as it implies the strategy may deliver performance independent of market movements.

How Should We View Strategies with High R-squared?

A high R-squared is not inherently good or bad—it depends on the investor’s goals. If your strategy aims to profit by tracking market indices or capturing broader trends, then a high R-squared is desirable—it means your strategy is successfully moving with the market. But if your objective is to generate returns uncorrelated with the market, or to maintain stability amid uncertainty, then a high R-squared strategy might not meet your needs.

#6 High Win Rate + High Profit-Loss Ratio

Win rate and profit-loss ratio are two of the most intuitive metrics in quantitative strategies. Many people focus on them from the very beginning, as they directly reflect a strategy’s profitability and risk control. But these two indicators are more than just surface-level numbers—their real value lies in understanding their deeper meaning and how they interact. This understanding is essential for properly evaluating a strategy.

Win Rate refers to the percentage of trades that end in profit out of the total number of trades. Simply put, it tells you how often the strategy wins. Many people assume that the higher the win rate, the better the strategy—but that’s not necessarily true.

High Win Rate Isn’t Always Better: A strategy with a high win rate might look like it’s making money consistently, but if each winning trade earns very little, and a single loss wipes out all prior gains, the strategy is still flawed. For example, a strategy with a 90% win rate might earn $1 per win, but lose $50 in one bad trade. This kind of risk-reward structure carries substantial hidden risk.

What’s a Reasonable Win Rate?
In general, a win rate above 50% feels reassuring, but a lower win rate doesn’t automatically make a strategy bad. For instance, trend-following strategies often have relatively low win rates (sometimes just 30%-40%) but rely on very high profit-loss ratios—meaning each winning trade earns much more than each losing one—to stay profitable overall.

Profit-Loss Ratio refers to the average profit per winning trade divided by the average loss per losing trade. It reveals the “risk-reward” per trade. Even a strategy with a modest win rate can be profitable over the long term if the profit-loss ratio is sufficiently high.

High Profit-Loss Ratio Strategies: These strategies may lose money on most trades, but a few large wins more than make up for the losses. Such strategies require a strong psychological tolerance for frequent losses and are commonly found in trend-following systems.

Low Profit-Loss Ratio Strategies: These typically require very high win rates to remain profitable, because each win earns only a small amount. One significant loss can wipe out many small gains. These are often found in intraday or arbitrage strategies, but any dip in win rate can lead to sharp declines in performance.

Win Rate and Profit-Loss Ratio Are Two Sides of the Same Coin
You can’t evaluate one in isolation. A good strategy doesn’t need the highest win rate, but it must strike a healthy balance between win rate and profit-loss ratio. Together, these two metrics determine whether a strategy can generate consistent profits over the long run. So when choosing or evaluating a strategy, it’s crucial to assess how these two metrics interact—rather than chasing the “best” number for just one.