What does a high quality entry signal look like?

Introduction

As traders, we constantly seek ways to compare the quality of our strategy's entry signals. We yearn to identify signals that offer a better edge, increasing our chances of success. In this article, we will explore an interesting tool for entry signal evaluation known as the edge ratio. We will delve into the components required to calculate the edge ratio and how it can be used to both quantify and visualise the profitability of an entry signal.

Understanding the Edge Ratio

The edge ratio quantifies the extent of beneficial price changes relative to unfavourable price changes anticipated after a signal event. More specifically, the edge ratio is derived from the following equation:

Edge Ratio = MFE/MAE

Where:

MFE is the Maximum Favourable Excursion;

MAE is the Maximum Adverse Excursion.

By calculating the average of this ratio for all the trading signals generated, we can gain insights into the potential profitability and risk associated with a trade.

Maximum Adverse Excursion (MAE)

MAE measures the maximum unrealised loss (or drawdown) incurred during the lifespan of a trade while it remains open. It represents the worst-case scenario in terms of the negative price movement experienced. Understanding the MAE allows us to gauge the level of risk associated with a particular trading signal.

Maximum Favourable Excursion (MFE)

In contrast to MAE, MFE represents the maximum unrealised profit gained during the lifespan of a trade while it remains open. It showcases the best-case scenario in terms of positive price movement. Analysing MFE helps us determine the potential reward a trade may offer.

Normalising by the Average True Range (ATR)

The values of MFE and MAE are normalised for volatility at the time when the position is opened. This allows like-for-like comparisons of edge ratios across different markets and time frames. More specifically, the MFE and MAE are reported as multiples of the measured Average True Range (ATR). The ATR is the average computed over a lookback period (typically 14 trading days) of the true range (TR), which is calculated as follows:

TR = max(H-L, H-C1, C1-L)

Where:

H is the high of the current bar;

L is the low of the current bar;

C1 is the close of the previous bar.

Once normalised for volatility, edge ratios above 1 indicate more favourable price action than adverse. The opposite is the case for edge ratios below 1.

Using the edge ratio as a single point metric

One way of calculating the edge ratio involves computing one MAE and MFE capturing price excursions the entire duration of the trade. This calculation returns a single value that lends itself to comparisons between different trading systems.

The rationale behind the edge ratio is very intuitive; if the price action following an entry signal is more favourable than adverse, clearly this is indicative of an edge. In addition, the edge ratio is evaluating a notably different aspect of a strategy than commonly used volatility-adjusted return metrics like the Sharpe ratio. In other words, while the edge ratio captures the quality of the entry signal, other metrics such as the Sharpe Ratio are more birds-eye metrics capturing overall portfolio performance (which can include other aspects e.g. exit criteria, risk management etc.). Hence why the edge ratio could be a valuable addition to traders’ strategy evaluation process.

To further underscore this point, an interesting finding reported on a YouTube video [1] showed that the edge ratio has a low correlation with conventional metrics, including the Sharpe ratio, suggesting they could be highly complementary (Figure 1 below). To illustrate this point: two different but very similar metrics like CAGR and the Sharpe ratio have a very strong correlation. One way of interpreting this finding is that if you’re already using one of these metrics, adding the other will add little to no informational value to your understanding of the strategy. By extension, incorporating multiple uncorrelated, intuitively valuable, metrics can help paint a more complete picture.

Visualising your edge through edge ratio curves

An alternative way of using the edge ratio involves calculating edge ratio values at the close of every bar after the opening of the position for a fixed number of bars. The edge ratio values are then plotted against the time elapsed from the start of the trade, as shown below.

Visualising the edge ratio can help refine our assessment of the quality of our entry signals. Ideally, we would like to observe a stable region of values above one for a sustained period of time elapsed from the start of a trade. Such a finding would speak to the robustness of the strategy being scrutinised. By contrast, if edge ratios are sporadically above 1 for very limited time periods, this indicates that a seemingly good strategy’s performance may be the result of pure luck - it may be overfit to some spurious noise patterns.

One way of quantifying the stability of the aforementioned region of values could entail calculating the integral or area between the edge ratio curve and the horizontal line corresponding to an edge ratio value of 1 as shown below.

Applications and benefits of the edge ratio

By utilising the Edge Ratio, traders gain several advantages in evaluating trading signals:

1. Comparative Analysis: The Edge Ratio facilitates a direct comparison between different entry signals, enabling traders to identify which signals possess a superior edge

2. Risk Assessment: Evaluating the MAE component helps traders assess the potential risk associated with a trade. By understanding the worst-case scenario, traders can better manage their risk exposure

3. Profit Potential: Analysing the MFE component provides insights into the potential profit that a trade can generate. It helps traders focus on signals that offer a higher potential reward

4. Market Adaptability: The normalisation of MFE/MAE by ATR allows traders to evaluate signals across various markets and instruments. This adaptability enhances the versatility of the Edge Ratio as a trading tool.

Conclusion

The edge ratio emerges as a valuable tool in the trader's arsenal, enabling the evaluation of strategy entry signals based on potential rewards and risks. By considering the MFE, MAE, and normalising the ratio by the ATR, traders gain valuable insights into the profitability and risk associated with their trades.

While the edge ratio provides a helpful framework, it should be considered alongside other key factors such as win rate, position sizing, and risk management strategies. Combining these elements empowers traders to make well-informed decisions and optimise their trading performance.

References

[1] “What is Edge Ratio? How to use it to vet strategies for robustness?” by StatOasis https://www.youtube.com/watch?v=s8SheOy82nU