Normalized return is a key concept in trading and investing that helps traders compare the performance of different assets by adjusting returns for risk or volatility. Unlike raw returns, which simply measure the percentage change in an asset’s price over a given period, normalized returns provide a more meaningful metric by factoring in how much risk or fluctuation was involved in achieving those returns. This adjustment allows traders and investors to make better-informed decisions, especially when comparing assets or strategies that exhibit different levels of volatility.

At its core, normalized return is designed to answer the question: “How much return did I earn per unit of risk?” One common approach to normalizing returns involves dividing the asset’s return by a measure of its volatility, such as the standard deviation of returns. The standard deviation reflects the degree to which an asset’s price tends to fluctuate around its average return. By dividing the return by this measure, you get a normalized figure that expresses return in terms of risk-adjusted performance.

Formula: Normalized Return = (Return) / (Standard Deviation of Returns)

For example, consider two stocks: Stock A and Stock B. Over a year, Stock A returns 10% with a standard deviation of 5%, while Stock B returns 15% but with a standard deviation of 20%. Calculating the normalized return for both:

– Stock A: 10% / 5% = 2.0
– Stock B: 15% / 20% = 0.75

Although Stock B has a higher raw return, Stock A provides a better return relative to the risk taken, with a normalized return of 2.0 compared to 0.75. This insight can prevent traders from chasing higher returns without considering the risk involved.

In the context of foreign exchange (FX) trading, normalized returns are particularly useful. FX markets can be highly volatile, and comparing two currency pairs purely on their returns may be misleading. Suppose you are evaluating two currency pairs: EUR/USD and GBP/JPY. Over a month, EUR/USD returns 2% with a volatility of 1.5%, while GBP/JPY returns 3% but has a volatility of 5%. Using normalized returns helps identify which pair is providing superior risk-adjusted performance. This is crucial when building a portfolio or allocating capital across different instruments.

Another practical example can be found in indices trading. Consider the S&P 500 index and a tech-heavy index like the NASDAQ Composite. The NASDAQ might show higher returns during bullish periods but also comes with higher volatility. Normalizing returns enables investors to see if the extra risk is being adequately compensated by higher returns.

A common misconception is to equate normalized return with absolute or raw return. New traders often focus solely on the percentage gain without accounting for how much risk was taken. This approach can lead to favoring high-volatility assets that may have high returns in good times but can result in significant losses during downturns. Normalized return helps avoid this pitfall by emphasizing the importance of risk-adjusted performance.

Another mistake is using inappropriate measures of risk. While standard deviation is common, some traders use other metrics like beta or value at risk (VaR) depending on the context. It’s important to choose a risk measure consistent with your trading strategy and the nature of the asset.

People often search for related terms such as “risk-adjusted return,” “Sharpe ratio,” and “how to compare returns with volatility.” The Sharpe ratio, in fact, is a popular metric that closely relates to normalized return as it adjusts returns by the standard deviation of excess returns over the risk-free rate. Understanding normalized return is a step toward grasping more advanced concepts like the Sharpe ratio.

In summary, normalized return is a powerful tool for traders who want to evaluate the true performance of their investments. By adjusting returns for volatility or risk, it provides a clearer picture of how efficiently an asset or strategy generates profits relative to the risk taken. Whether trading stocks, FX, CFDs, or indices, incorporating normalized returns into your analysis can lead to more balanced and informed trading decisions.