Mutual Fund Stress Test: In what sense does the test include "stress"?

Mutual Fund Stress Test: In what sense does the test include "stress"?

Although the stress test's purpose, as stated by SEBI, is undoubtedly a step in the right direction, Jain notes that the data provided by the AMCs could not be accurate in actual stressful circumstances.

Because small-cap companies have less equity and lower market capitalizations, their liquidity decreases under stressful market circumstances, which raises the impact cost.

Vineet Jainn, Volvin Ltd.'s CIO and co-founder

The Association of Mutual Funds in India (AMFI) was instructed by the Securities and Exchange Board of India (Sebi) a few months ago to request that all small and mid-cap mutual funds do a stress test in order to evaluate their liquidity levels and to provide an update on their results every fifteen days beginning on March 15, 2024. Has the test fulfilled its intended function, while causing a great deal of stress and worry in the ecosystem?

It seems that there are some obstacles to reaching the intended objective because of the test's technique.  Mutual funds must be able to analyze the following in order to really grasp liquidity:

• Accurately identifying a market slump as a potentially stressful situation

• In the case of a slump, if the mutual fund can really sell its shares or less liquid assets.

       The real dangers involved in selling off mutual fund investments

Stress Test Results and Restrictions

The following are some of the small and midcap funds' findings from their first round of the test, which are based on the stress test methodology that AMFI supplied with the AMCs:

The mutual funds' findings, which they released, provide light on the liquidity profile of their small- and mid-cap portfolio and demonstrate their capacity to turn assets into cash in a timely manner under stressful situations. This information is critical for investors to comprehend the liquidity risk associated with the fund; a longer period of time needed to sell off assets may be a sign of increased liquidity risk, particularly if investors must redeem their investments in the midst of volatile market circumstances.

These findings also aid in comparing the liquidity risk of different funds, which helps investors understand the caliber of liquid equities in mutual fund portfolios.

It's interesting that the findings highlight two restrictions:

• To begin with, the stress calculations indicate that it will take almost twice as many days to liquidate 50% of the fund as it would to liquidate 25% of the fund. Doesn't it seem a little too straightforward and basic?

Because small-cap companies have less equity and lower market capitalizations, their liquidity decreases under stressful market circumstances, which raises the impact cost. For instance, if a stock has 10% floating stock and a fund purchases 1% of that 10% floating stock, the impact cost on that stock would undoubtedly differ from that of a similar fund purchasing the subsequent 1% of the remaining 9% floating stock. As a result, the link between selling the first 25% and the second 25% of the portfolio cannot be linear; rather, it would be exponential, and the second lot would almost likely need more time and money to liquidate its shares than the first.

• Secondly, it seems pointless to use data that was calculated using a methodology for "normal" market conditions, as this exercise is intended to test the funds' ability to liquidate their assets under "stressful" market conditions. In other words, the test should ideally be carried out when the markets are not performing well, not when they are performing well or as usual.

The "linear" nature of the data indicates that the exercise was conducted under "Normal" circumstances rather than "stressful" conditions, which obviously defeats the very purpose of the exercise and, by extension, the results as well, will not produce the desired outcome.

This leads us to the crucial query: what really constitutes "stress" in markets?

Characterizing a Calm vs. Anxious Market Situation in the Indian Market

The first stage is to determine whether stress situations, such as a severe market decline, might have an effect on the mutual fund's portfolio.

Using the "Normal Distribution or Six Sigma Bell Curve," which statisticians use to describe the likelihood of an occurrence, is a straightforward technique to ascertain this. With most observations grouped around the average and fewer observations at the extremes, the data in a graph of this kind is symmetrically distributed around the mean.

The Normal Distribution Curve may be used to determine the range of both normal and stressful market circumstances in our situation, as well as the likelihood of stress zones and periods and how likely they are to occur. Mutual funds will be able to provide their statistics during really difficult market situations by adding these factors.

Finding a Factual Stress Scenario by Evaluating the 24-Year Movement of NIFTY

The monthly movement of the NIFTY from January 2000 to March 2024, or for 291 months (24 years and 3 months), is presented here to help determine a general metric or definition of a "stressful market condition" in the context of the Indian markets. The following criteria were used to analyze and classify the data from these 291 readings:

The variation in the NIFTY movement is indicated by the symbols +/-1, +/-2, and +/-3 in the graph above. The Normal range is between -1 and +1 Sigma, the Moderate Stress Range is between -1 and -2 Sigma and +1 to +2 Sigma, and the Extreme range is between -2 and -3 Sigma and +2 to +3 Sigma. Therefore, about 68.2% of the readings, or the majority of the positive or negative movement of NIFTY, lie between the -1 Sigma to +1 Sigma range. Nonetheless, NIFTY would be classified as Moderate Stress if its movement has been between -6% and -10.5%, or within the range of -1 Sigma to -2 Sigma. If, on the other hand, its movement falls between - 10.5% and -15%, it would be classified as Extreme Stress. Seldom may be characterized as being beyond 3 Sigma.

In order to determine realistic results for the Stress Test, as opposed to the currently offered results that reflect data considered under the Normal Condition, the data supplied by the AMCs for our Stress Test must therefore be for at least the -1 Sigma to -2 Sigma range, i.e. the Moderate Stress State of affairs, or up to 3 Sigma, i.e. the Extreme Stress condition.

SEBI's Correct Course Actions

Although the stress test was designed with SEBI's intentions in mind, the information provided by the AMCs may not be accurate under actual stressful circumstances. All things considered, fund managers will find SEBI's effort, if carried out properly, to be very beneficial in understanding the real risks involved in selling their less liquid small and mid-cap equities. Moreover, it's possible that fund managers were encouraged to add premium equities with strong liquidity and little portfolio effect costs. It's also possible that SEBI is subtly conveying the message that, in order to protect investors' hard-earned money, they should only invest in eminently liquid, high-quality equities, regardless of their size, level of knowledge, or stage in the redemption race.