The Importance Of Risk-adjusted Returns In Trading And Investing – The Sharpe ratio compares an investment’s return to its risk. It is a mathematical expression of the understanding that higher returns over time may indicate greater volatility and risk than the investment’s potential.

Economist William F. Sharpe proposed the Sharpe ratio in 1966 as a result of his work on the capital asset pricing model (CAPM), called the premium-to-volatility ratio. Sharp received the Nobel Prize in Economics in 1990 for his work on the CAPM.

A Sharpe ratio calculator is the difference between the actual or expected return and an indicator, such as the risk-free rate of return or the performance of an investor class. Its definition is the standard deviation of returns over the same period of time, a measure of volatility and risk.

#### Risk Free Rate (rf)

Sharp ratio = R p − R f σ p where: R p = portfolio return R f = risk-free rate σ p = revolutionary standard deviation of portfolio return begin &textit = frac\ &textbf\ &R_= text\ &R_ = text\ &sigma_p = text\ end SharpeRatio = σ p R p − R f Where: R p = portfolio return R f = risk-free rate σ p = standard deviation of the portfolio Additional income.

The standard deviation is derived from the change in returns for a series of time intervals, which are aggregated over the overall sample of performance under consideration.

The return is calculated as the average of the differences in each incremental period, forming a total. For example, a 10-year Sharpe ratio number can average 120 times the difference in monthly returns for a fund compared to the industry benchmark.

The Sharpe ratio is one of the most popular methods of measuring risk-adjusted relative returns. It compares the fund’s historical or expected returns relative to an investment benchmark with the historical or expected change in such returns.

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The risk-free rate was originally used in the formula to represent the investor’s estimated minimum borrowing cost. Generally, it represents the risk premium of an investment associated with a safe asset such as a bill or treasury bond.

When compared to the returns of an industry sector or investment strategy, the Sharpe ratio provides a measure of risk-adjusted performance that is independent of such characteristics.

The ratio is useful in determining the extent to which historical excess returns have been accompanied by excess volatility. When excess returns are measured against an investment’s benchmark, the standard deviation formula calculates volatility based on the difference in returns from their average.

Ratio utility depends on the assumption that the historical record of risk-adjusted relative returns has at least some approximate value.

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The Sharpe ratio can be used to evaluate the performance of a risk-adjusted portfolio. Alternatively, an investor can use the fund’s target return to calculate the expected Sharpe ratio.

The Sharpe ratio can explain whether a portfolio’s excess returns are a smart investment decision or just luck and risk.

For example, low-quality, highly speculative stocks may outperform blue-chip stocks over long periods of time, such as the dot-com bubble or, more recently, the meme stock frenzy. If the YouTuber beats Warren Buffett in the market for a while, the Sharpe ratio provides a quick reality check by adjusting each manager’s performance for the volatility of their portfolio.

The higher a portfolio’s Sharpe ratio, the better its risk-adjusted performance. A negative Sharpe ratio means that the risk-free rate or benchmark rate is greater than the portfolio’s historical or expected return, otherwise the portfolio’s return would be negative.

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The Sharpe ratio can be manipulated by portfolio managers who want to maximize their risk-adjusted return history. This can be done by extending the return measurement intervals, which results in lower volatility estimates. For example, the standard deviation (volatility) of annual returns is generally lower than monthly returns, which in turn are less volatile than daily returns. Financial analysts typically consider the volatility of monthly returns using the Sharpe ratio.

Calculating the Sharpe ratio for favorable performance periods instead of objectively selected periods is another way of selecting data that distorts risk-adjusted returns.

The Sharpe ratio also has some inherent limitations. Calculating the standard deviation of the ratio denominator, which serves as a proxy for portfolio risk, estimates volatility based on a normal distribution and is more useful for estimating symmetric probability distribution lines. Conversely, financial markets subject to herd behavior may go to extremes more often than the normal distribution would allow. As a result, the standard deviation used to calculate the Sharpe ratio may underestimate the tail risk.

Market returns are also serially correlated. A simple example is that returns in nearby time periods may be correlated because they have been affected by the same market trend. But mean inversion also depends on serial correlations, such as market momentum. The result is that serial correlation reduces volatility, and as a result, investment strategies based on serial correlation factors can result in higher Sharpe coefficients.

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One way to visualize these criticisms is to consider the investment strategy of collecting nickels in front of a roller coaster that almost always moves slowly and unpredictably, except on rare occasions when it suddenly and fatally accelerates. Because such adverse events are rare, nickel hoarders often generate positive returns with minimal volatility, resulting in high Sharpe ratios. And if the fund that collects the proverbial nickels in front of the roller flattens out in one of those extremely rare and unfortunate circumstances, its long-term outlook might still look good: just one bad month. Unfortunately, this provides little comfort to fund investors.

The standard deviation in the Sharpe ratio formula assumes that price movements are equally risky in both directions. In fact, the risk of abnormal returns is very different from the probability of abnormally high returns for many investors and analysts.

A version of Sharpe, called the Sortino ratio, ignores above-average returns to focus only on its negative deviation as a better proxy for portfolio fund risk.

The standard deviation in the denominator of the Sortino ratio measures the variance of negative returns or below a selected threshold compared to the mean of such returns.

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Another variant of Sharpe is the Treynor ratio, which divides the excess return over the risk-free rate or beta rate by the beta of a security, fund or portfolio as a measure of its riskiness. Beta measures the degree to which a stock or fund’s volatility matches the market as a whole. The purpose of the Treynor ratio is to determine whether the investor is compensated for the excess exposure to market risk.

The Sharpe ratio is sometimes used to determine how adding an investment can affect a portfolio’s risk-adjusted return.

For example, an investor is considering adding a hedge fund to a portfolio that has returned 18% over the past year. The current risk-free rate was 3% and the annual standard deviation of the portfolio’s monthly returns was 12%, giving it an annualized Sharpe ratio of 1.25, or (18 – 3) / 12.

An investor believes that adding a hedge fund to a portfolio will reduce expected returns by 15% over the next year, but also expects the resulting portfolio volatility to decrease by 8%. The risk-free rate is expected to remain unchanged next year.

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Using the same formula as the estimated future numbers, the investor finds that the portfolio has an expected Sharpe ratio of 1.5, or (15% – 3%) divided by 8%.

In this case, when the hedge fund’s investment is expected to reduce the portfolio’s absolute return, given its expected volatility, it improves the portfolio’s risk-based performance. If new investment lowers the Sharpe ratio as predicted, this will be detrimental to risk-adjusted returns. This example assumes that the Sharpe ratio can be compared using the investor’s return and volatility estimates based on the portfolio’s historical performance.

A sharp ratio of 1 is generally considered “good” and suggests excess return relative to volatility. However, investors often compare a portfolio or fund’s Sharpe ratio to its peers or market sector. Therefore, a portfolio with a Sharpe ratio of 1 may underperform. For example, if many competitors have ratios above 1.2, a good Sharpe ratio may be the same in one context or worse in another.

To calculate the Sharpe ratio, investors subtract the risk-free rate from the portfolio’s rate of return, often using U.S. Treasury bond yields as a proxy for the risk-free rate of return. Then, they divide the result by the standard deviation of the portfolio’s excess return.

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