If, for example, a fund has a beta of 1.05 in relation to the S&P 500, the fund has been moving 5% more than the index. Therefore, if the S&P 500 increased by 15%, the fund would be expected to increase by 15.75%. On the other hand, a fund with a beta of 2.4 would be expected to move 2.4 times more than its corresponding index. So if the S&P 500 moved 10%, the fund would be expected to rise 24%, and if the S&P 500 declined 10%, the fund would be expected to lose 24%.
Once expected returns of a portfolio reach a certain level, an investor must take on a large amount of volatility for a small increase in return. Obviously, portfolios with a risk/return relationship plotted far below the curve are not optimal since the investor is taking on a large amount of instability for a small return. To determine if the proposed fund has an optimal return for the amount of volatility acquired, an investor needs to do an analysis of the fund’s standard deviation. To determine how well a fund is maximizing the return received for its volatility, you can compare the fund to another with a similar investment strategy and similar returns.
Understanding Market Volatility
If an investor expects the market to be bearish in the near future, the funds with betas less than one are a good choice because they would be expected to decline less in value than the index. For example, if a fund had a beta of 0.5, and the S&P 500 declined by 6%, the fund would be expected to decline only 3%. Beta, another useful statistical measure, compares the volatility of a fund to its index or benchmark. Khadija Khartit is a strategy, investment, and funding expert, and an educator of fintech and strategic finance in top universities.
When considering a fund’s volatility, an investor may find it difficult to decide which fund will provide the optimal risk-reward combination. Many websites provide various volatility measures for mutual funds free of charge; however, it can be hard to know not only what the figures mean but also how to analyze them. Up to this point, we have learned how to examine figures measuring risk posed by volatility, but how do we measure the extra return rewarded to you for taking on the risk posed by factors other than market volatility? Enter alpha, which measures how much if any of this extra risk helped the fund outperform its corresponding benchmark. Using beta, alpha’s computation compares the fund’s performance to that of the benchmark’s risk-adjusted returns and establishes if the fund outperformed the market, given the same amount of risk.
Understanding Volatility Measurements
The fund with the lower standard deviation would be more optimal because it is maximizing the return received for the amount of risk acquired. Remember, because volatility is only one indicator of the risk affecting a security, a stable past performance of a fund is not necessarily a guarantee of future stability. Since unforeseen market factors can influence the volatility, a fund with a standard deviation close or equal to zero this year may behave differently the following year. The relationship between portfolio returns and risk can be represented by the efficient frontier, a curve that is a part of modern portfolio theory.
She has been an investor, entrepreneur, and advisor for more than 25 years. The standard deviation is a statistic measuring the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. Volatility measures how much the price of a security, derivative, or index fluctuates.
Negative alphas are bad in that they indicate the fund underperformed for the amount of extra, fund-specific risk the fund’s investors undertook. Alpha is calculated using beta, so if the R-squared value of a fund is low, it is also wise not to trust the figure given for alpha. R-squared values range between 0 and 100, where 0 represents the least correlation, and 100 represents full correlation. If a fund’s beta has an R-squared value close to 100, the beta of the fund should be trusted.
Another way to measure risk is standard deviation, which reports a fund’s volatility, indicating the tendency of the returns to rise or fall drastically in a short period of time. Read on to learn about the four most common volatility measures and how they are applied in the type of risk analysis based on modern portfolio theory. If you are deciding on buying mutual funds, it is important to be aware of factors other than volatility that affect and indicate the risk posed by mutual funds.
Optimal Portfolio Theory And Mutual Funds
A fund with a consistent four-year return of 3%, for example, would have a mean, or average, of 3%. The standard deviation for this fund would then be zero because the fund’s return in any given year does not differ from its four-year mean of 3%. On the other hand, a fund that in each of the last four years returned https://xcritical.com/ -5%, 17%, 2%, and 30% would have a mean return of 11%. This fund would also exhibit a high standard deviation because each year, the return of the fund differs from the mean return. This fund is, therefore, riskier because it fluctuates widely between negative and positive returns within a short period.
- Volatility measures how much the price of a security, derivative, or index fluctuates.
- When considering a fund’s volatility, an investor may find it difficult to decide which fund will provide the optimal risk-reward combination.
- According to the modern portfolio theory, funds lying on the curve are yielding the maximum return possible, given the amount of volatility.
- For example, if a fund had a beta of 0.5, and the S&P 500 declined by 6%, the fund would be expected to decline only 3%.
- Alpha is calculated using beta, so if the R-squared value of a fund is low, it is also wise not to trust the figure given for alpha.
- If an investor expects the market to be bearish in the near future, the funds with betas less than one are a good choice because they would be expected to decline less in value than the index.
- The R-squared of a fund shows investors if the beta of a mutual fund is measured against an appropriate benchmark.
The curve forms from a graph plotting return and risk indicated by volatility, which is represented by the standard deviation. According to the modern portfolio theory, funds lying on the curve are yielding the maximum return possible, given the amount of volatility. Modern portfolio theory and volatility are not the only means investors use to analyze the risk caused by many different factors in the market. And things like risk tolerance and investment strategy affect how an investor views his or her exposure to risk.
The standard deviation essentially reports a fund’s volatility, which indicates the tendency of the returns to rise or fall drastically in a short period of time. A volatile security is also considered a higher risk because its performance may change quickly in either direction at any moment. The standard deviation of a fund measures this risk by measuring the degree to which the fund fluctuates in relation to its mean return.
Alpha (α) , used in finance as a measure of performance, is the excess return of an investment relative to the return of a benchmark index. Beta is a measure of the volatility, or systematic risk, of a security or portfolio in comparison to the market as a whole. For example, if a fund has an alpha of one, it means that the fund outperformed the benchmark by 1%.
A fund with a beta very close to one means the fund’s performance closely matches the index or benchmark. A beta greater than one indicates greater volatility than the overall market, and a beta less than one indicates less volatility than the benchmark. These figures can be difficult to understand, so if you use Crypto Volatility them, it is important to know what they mean. The R-squared of a fund shows investors if the beta of a mutual fund is measured against an appropriate benchmark. One examination of the relationship between portfolio returns and risk is the efficient frontier, a curve that is a part of modern portfolio theory.
Optimal Portfolio Theory And Mutual Funds
On the other hand, an R-squared value close to 0 indicates the beta is not particularly useful because the fund is being compared against an inappropriate benchmark. Alpha measures how much, if any, extra risk helped the fund outperform its corresponding benchmark. Beta by itself is limited and can be skewed due to factors other than the market risk affecting the fund’s volatility. Investors expecting the market to be bullish may choose funds exhibiting high betas, which increases the investors’ chances of beating the market.
Understanding Volatility Measurements
James Chen, CMT is an expert trader, investment adviser, and global market strategist. He has authored books on technical analysis and foreign exchange trading published by John Wiley and Sons and served as a guest expert on CNBC, BloombergTV, Forbes, and Reuters among other financial media. The Capital Asset Pricing Model helps to calculate investment risk and what return on investment an investor should expect. The offers that appear in this table are from partnerships from which Investopedia receives compensation.