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How to measure Risk for Mutual Fund Investment

Here we will understand how common investors can measure Risk for Mutual Funds.

(A) Risk Measures of Mutual Funds

1.     Alpha Measures of Risk:

Alpha measures the performance of an asset manager. It measures the efforts put in by a fund manager in driving the fund that he or she is managing as against a benchmark index. Alpha’s baseline is 0 in case of mutual funds. If alpha is negative, then it indicates that the performance of the fund manager was underwhelming. If alpha is positive, then it suggests that the fund manager’s performance was overwhelming. Generally, the performance of a mutual fund is compared with that of an index

Alpha measures the difference between a fund’s expected returns based on its beta and its actual returns. A positive alpha indicates the fund has performed better than its beta would predict. A negative alpha indicates a fund has underperformed, given the fund’s beta.

For investors, alpha is useful in determining if a mutual fund is worth investing as it measures the capabilities of the fund manager to generate profits. Therefore, knowing how the fund manager has performed, they can make an informed decision. 

The following is the formula to calculate alpha in the case of mutual funds:

Alpha = (End Price – Start Price + DPS) / Start Price

# DPS - Distribution Per Share

2.     Beta Risk Measures:

Beta measures a fund’s sensitivity to market movements. A beta greater than one indicates the investment is more volatile than the market. If beta is less than one, the investment is less risky than the market.

Beta helps investors in understanding how sensitive the mutual fund was when the markets went volatile.

By checking beta of a mutual fund, the investors can decide if the fund that they are deliberating to invest in is suitable or not. Risk-averse investors would like to have the beta on the lower side as it is indicative of steady returns and response to market volatility. 

The following is the formula to calculate beta in the case of mutual funds:

Beta = Covariance / Variance

#          Here, Covariance is indicative of how two different stocks vary from one another in different market condition.

#          The Variance shows the variation of a fund’s price from its average and represents the fund’s volatility in its price over a period.

3.     R-Squared (R2) Risk Measures

R-Squared reflects the percentage of a fund’s movements that are explained by movements in its benchmark index. A higher R-squared indicates a more useful beta figure. A lower R-squared (less than 70%) is less relevant to the fund’s performance.

R-Squared is an analytical tool for mutual funds. It helps to determine how identical a mutual fund’s performance is to a given benchmark index. Do take note that R-squared does not measure the performance of the fund. R-squared does not tell us if a particular mutual fund is good to invest or not. It simply compares the performance to a given benchmark’s returns.

R-squared is expressed as a percentage within the 0-100 range.

The value of R-squared is divided into three tiers:

  • 1-40%                     : low correlation to the benchmark
  • 40%-70%    : average correlation to the benchmark
  • 70%-100%  : high correlation to the benchmark

R-squared is a technical tool and the formula for R-squared requires us to consider a few statistical metrics like correlation and standard deviation.

R-Squared = Square of Correlation

#          Correlation = Covariance between Benchmark (Index) and Portfolio/ (SD of Portfolio*SD of the benchmark)

[#         SD : Standard Deviation.]

4.     Sharpe Ratio in Mutual Fund

Sharpe ratio is used to evaluate the risk-adjusted performance of a mutual fund. Basically, this ratio tells an investor how much extra return he will receive on holding a risky asset.

Sharpe Ratio plays a significant part in evaluating the performance of an investment. Developed by American economist and Noble laureate William F. Sharpe, the Sharpe Ratio measures the risk-adjusted returns of an investment. Sharpe Ratio can be taken into account before starting investing in any fund. However, it is necessary to understand all the aspects of this ratio before using it for evaluating or comparing mutual funds.

Sharpe ratio indicates investors’ desire to earn returns which are higher than those provided by risk-free instruments like Treasury Bills. As Sharpe ratio is based on standard deviation which in turn is a measure of total risk inherent in an investment, Sharpe ratio indicates the degree of returns generated by an investment after taking into account all kinds of risks. It is the most useful ratio to determine the performance of a fund and you, as an investor, need to know its importance.

The Sharpe Ratio of any mutual fund can be easily calculated using a simple formula or by following these two steps:

  • Subtract the risk-free return of a mutual fund from its portfolio return or the average return
  • Divide the subtracted number, which is called the excess returns by the standard deviation of the fund’s returns.

[Sharpe Ratio = (Average fund returns − Risk-free Rate) / Standard Deviation of fund  returns]

It means that if the Sharpe ratio of a fund is 1.25 per annum, then the fund generates 1.25% extra return on every 1% of additional annual volatility. A fund with a higher standard deviation should earn higher returns to keep its Sharpe ratio at higher levels. Conversely, a fund with a lower standard deviation can achieve a higher Sharpe ratio by earning moderate returns consistently.  

What is considered a good Sharpe Ratio?

 

Sharpe Ratio

Risk Rate

Verdict

Less than 1.00

Very low

Poor

1.00 – 1.99

high

Good

2.00 – 2.99

high

Great

3.00 or above

high

Excellent

The table shows the features or parameters of a good Sharpe Ratio. Investments with less than 1.00 Sharpe Ratio do not generate high returns. Contrarily, investment with Sharpe Ratio of 1.00 to 3.00 or above have higher returns subsequently.

5.     Treynor Ratio in Mutual Fund

Jack Treynor, an eminent American economist and one of the founding fathers of the Capital Asset Pricing Model, developed this metric.

Treynor Ratio measures the efficiency with which the fund manager has allocated the fund’s assets to compensate the investor for taking the given level of risk. Treynor Ratio exclusively focuses on how well the portfolio has performed in the backdrop of risks prevailing in the economy. Treynor Ratio of a mutual fund indicates how well you will be rewarded for taking the risk of investing in a particular mutual fund scheme.

This measure gauges the returns from a collection of securities’ above a risk-free rate, adjusted by the beta value.

Thus, the Treynor Ratio (TR) is calculated based on the following formula –

TR = (Portfolio’s returns – Risk-free return rate) / Beta value of the portfolio

Beta is a crucial factor in the Treynor ratio formula that distinguishes this metric. That is because it represents the systematic risk, which is volatility at a macro level. It’s determined by factors that are not influenced by portfolio diversification.

>>        Treynor Ratio example

XYZ is a mutual fund with a rate of return of 15%. Its beta value is 1.3, meaning it’s 30% more volatile than the market. And the risk-free return rate is 3%.

Thus, XYZ’s Treynor ratio = (15% – 3%) / 1.3

Or, XYZ’s TR = 9.23

It’s a measure of risk-reward. Hence, if one were to invest in XYZ mutual fund, their compensation or reward for assuming one unit of risk will be Rs.9.23.

An example would better illustrate how investors can use TR to make investment decisions.

Raj is comparing between two mutual funds, X and Y. X is an equity fund, while Y is a fixed income fund. The rate of return of X is 12%, and that of Y is 7%. Additionally, Y’s beta is 0.5 and X’s is 1.2. It denotes that X is 20% more volatile, and Y is 50% less volatile than the market.

Let’s assume the risk-free return rate is 2%.

Therefore, X’s Treynor Ratio = (12% – 2%) / 1.2

Or, X’s TR = 8.33

The Treynor ratio of Y = (7% – 2%) / 0.5

Or, Y’s TR = 10

If Raj chose to go by such rates of returns, the obvious choice would have been X. However, this conclusion changes when those two options are compared based on Treynor ratio.

It shows that although X provides higher returns, it does not justify the risk such a fund assumes. Y compensates better for the assumed risk, and thus, is a better choice.

6.     Difference between Treynor Ratio and Sharpe Ratio ?

The table below demonstrates the differences between these two metrics.

Basis of distinction

Treynor Ratio 

Sharpe Ratio

Definition

It measures the risk-adjusted returns of a portfolio based on its beta.

It measures the risk-adjusted returns of a portfolio based on the standard deviation of its gains.

Nature of risk considered

It considers the systematic risk of a portfolio, which a fund manager cannot set off by diversifying.

It considers the unsystematic risk of a portfolio, which can be set off by diversification.

Suitability

It’s more suitable to assess portfolios that are well diversified.

It’s more suitable to assess a bevvy of securities that is less diversified.

Investment decisions go hand in hand with ratio analysis. Thus, having a clear understanding of them and applying metrics correctly can facilitate more effective decisions.

(B) Market Volatility Measures

1.     Capture Ratio

Capture ratio measures the performance of an investment (like mutual funds) during upward and downward market trends with respect to its benchmark index.

The ratio is essentially a statistical representation of how a fund manager has managed the fund during different market conditions for addressing risk. It is expressed in percentages for a period of 1, 3, 5, 10, and 15 years.

There are two types of capture ratio –

(i) Up-market or Upside Capture Ratio

Up-market or upside capture ratio evaluates the performance of an investment against a benchmark index when the market is bullish.

A mutual fund with an up-market capture ratio above 100 denotes that it has performed better than the benchmark. For instance, if the ratio is 110, it indicates that the fund has outperformed the index by 10%.

The up-market capture ratio is one of the ways for investors to gauge trustworthy products as well as fund managers. It is specifically helpful for those seeking relative returns instead of absolute or with active management of funds.

The up-market capture ratio formula is given by –

Up-market capture ratio = (Fund returns during an upside market/Benchmark returns) x 100 

It shows the ability of the fund to beat the benchmark at the time of bull runs. You get an idea of how much more returns the fund earned as compared to the benchmark. An upside capture ratio of more than 100 indicates that the fund beat the benchmark during the period of the market rally. A fund having upside capture ratio of say 150 shows that it gained 50% more than its benchmark in bull runs.  

(ii) Down-Market or Downside Capture Ratio 

Down-market or downside capture ratio is precisely the opposite of the above. It evaluates the performance of an investment against a benchmark index when the market is bearish.

A mutual fund with a down-market ratio of less than 100 indicates that it has performed better than the index. For instance, if the ratio is 90, it denotes that the investment has lost only 90% as much as the benchmark.

The down-market capture ratio is often considered alongside up-market. In some cases, mutual funds with an up-market ratio lower than 100 may still have a favourable down-market ratio.

The down-market capture ratio formula is given as –

Down-market capture ratio = (Fund returns during a downside market/ Benchmark returns) x 100

These ratios can be understood better with the aid of an example –

Following is the current up-market and down-market capture ratio of Axis Bluechip Fund –

1 year

3 year

5 year

9 year

Up-market

77

85

90

93

Down-market

66

63

78

77

The above upside and downside capture ratios indicate that remaining invested in the Axis Bluechip Fund for 5 years will enable individuals to enjoy favourable returns.

Contrarily, investing for less than 5 years can lead to a loss.

Please note, Axis Blue Chip Fund has been used just for the purpose of explaining the example. This is not a recommendation. Please conduct your own research and due diligence before selecting a mutual fund.

2.     MDD (Maximum Drawdown)

It is the peak-to-trough decline during a specific recorded period of a fund. It measures the largest percentage drawdown that has occurred in a certain time period.

A Maximum Drawdown (MDD) -or Max Drawdown- is the most observed loss when the funds in a portfolio are measured from their peak to their trough, prior to a new peak forming. As an indicator, maximum drawdown looks at the downside risk over a certain period of time. As a measure, maximum drawdown can be used on a standalone basis, or as an input with other metrics like the “Calmara Ratio” and “Return over Maximum Drawdown.” It is expressed as a percentage value.

To illustrate the meaning of max drawdown better, let’s take a look at the max drawdown formula below.

MDD = (Trough Value — Peak Value) / Peak Value

Example:

Let’s assume that an investment portfolio started off with an initial value of ₹5 lakhs. Over a period of time, the portfolio’s value increases to ₹7.5 lakhs before plunging back to ₹4 lakhs in a bear market that is quite brutal. Next investors observe that the value rebounds to ₹6 lakhs it drops down to ₹3.5 lakhs again. Following this, the value suddenly shoots up by more than twice its prior value to ₹8 lakhs. What is the max drawdown of this portfolio?

To find the max drawdown of this, we will pluck the initial peak value and lowest value from the information provided. The initial peak is ₹7.5 lakhs, and the lowest position held by the portfolio is ₹3.5 lakhs. In this case, the maximum drawdown looks like this:

MDD = (3,50,000 – 7,50,000) / 7,50,000 = -53.33%

Take note of the following:

–        For calculating max drawdown, the initial peak of ₹7.5 lakhs will be used. The peak of ₹6 lakhs that is in between the final and initial high positions will not be used since this value does not represent a new peak for MDD.

–        The latest peak of ₹8 lakhs will also not be taken as part of the calculation for the max drawdown as the original drawdown is supposed to consider the first peak only.

–             To calculate MDD, unlike the peak value, the trough value will be cherry-picked for the lowest among all, rather than choosing the first lowest value. In the case mentioned above, this value will be ₹3.5 lakhs, which appeared right before the new peak was formed. Although the first drop that appeared was down to ₹4 lakhs, this value is not considered valid to know the maximum dropdown.

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