Invest or Trade for optimal returns; not for adrenaline rush

8 Dec 2023 , 09:30 AM

The story of stock market excitement

Back in 2014, while discussing portfolio performance with a client, I came across an interesting feedback. Apparently, the client in question, who was an aggressive trader in the equity market, told me that he had traded smartly through 2014 and had seen returns of 30% for the full year. That was surely impressive, but there was a small problem. During the year, the Nifty had given 32% returns and so the investor would have done equally well by just putting money in a passive index fund. 

When confronted with this data, the investor had a ready response, “But you don’t get the adrenaline rush in mutual funds.” That brings us to a very critical question about investing and trading. You cannot invest or trade the market for the adrenaline rush. You have to invest or trade because it makes money. The funny part about stock markets is that you don’t make big returns by chasing returns. Instead, big returns would come to you when you manage the risk. And, for that we need to understand the idea of optimal returns; but before that we need to understand absolute returns and relative returns.

Absolute returns versus relative returns

When it comes to returns on an investment, our focus is normally on absolute returns or relative returns. To understand optimal returns, let us first understand the concept of absolute returns and relative returns first. At an absolute level, how do you define high returns? The concept of high return can change from investor to investor. For one investor, 20% may be high returns and for another investor 30% may be high returns. One way to fine tune this concept is to look at relative returns, which is compared to a benchmark. 

Here you compare returns with a benchmark like the Nifty or Sensex. For example, if the index like Nifty or Sensex is earning 14% returns in a year, then you expect your equity portfolio to at least earn 14% or more. Now you are judging by relative returns. An equity portfolio that earns 18% beats the index by 400 basis points while an equity portfolio that earns 20% beats the index by 600 basis points. This way, you have a much better basis for comparison of portfolios or investments. You can, at least say, that the equity portfolio or investment that beats the index by a bigger margin is better. However, that still only answers part of the question. Here is why?

Enter Optimal Returns: the third portfolio dimension

Relative returns, as we understand above, is a good measure but it still ignores a very important aspect of risk. The investor must be assured that the fund manager is not taking on unnecessary risks with their money. In colloquial English language, it is called playing ducks and drakes with somebody’s money. You obviously cannot have a fund manager who does that and such a fund manager is dangerous even if they have beaten the Nifty for 3 years in a row. That is where optimal returns come in handy. Here, optimal returns refer to the maximum level of returns you can earn for a given level of risk or the minimum risk you can take for a given level of returns. Let us again get into an example.

Here we shall compare two funds that are of similar objective and portfolio mix. Fund X earned 15% returns and Fund Y earned 17% returns last year; in a year when the Nifty gave 13.5% returns. So, Fund X beat the index by 150 bps and Fund Y by 350 bps. That means, Fund Y had higher relative returns, but there is more to the story. Here, your counter question should be how much risk are Fund X and Fund Y taking. A fund manager who earns 2% extra returns by taking twice the risk is not really doing a great job. That is just punting with your money, and you don’t want that. Optimal returns are always measured with reference to the risk of the investment. Therefore, optimizing returns means maximizing the returns for a given level of risk or minimizing risk for a given level of returns. But how do we measure risk here? The best proxy for risk is volatility of returns or standard deviation!

Minimizing risk means minimizing volatility

If you want to get optimal returns (which should be your target anyways), you should be able to get the maximum level of returns that you can get for a given level of risk. Here, risk is defined as volatility or the standard deviation of returns. Higher the standard deviation, higher is the volatility and, therefore, higher is the risk. Similarly, lower the standard deviation, lower is the volatility and, therefore, lower is the risk. Hence, given two funds with same level of returns, you prefer the fund with a lower level of volatility or lower standard deviation. That sounds great on paper, but you also need to understand why this is practically so important. For that, we once again go back to an illustration to understand the kind of damage that volatility can do to your investment returns or portfolio returns.

 Let us now consider the example of two funds and their returns over a period of 5 years. Fund X is a high risk volatile fund and Fund Y is a low risk stable fund. The returns of the fund over 5 years are used to calculate the eventual CAGR returns and assess which fund is better. Base investment is Rs1,000. We will see how much your base investment grows into in the case of Fund X and in the case of Fund Y over the period of 5 years.

	Year 1	Year 2	Year 3	Year 4	Year 5	Mean
Fund X	30%	25%	40%	-70%	81%	21.20%
Cumulative Amount	1,300	1,625	2,275	683	1,235
Fund Y	12.20%	11.90%	13.20%	12.50%	13%	12.56%
Cumulative Amount	1,122	1,256	1,421	1,599	1,807

Here are 5 important takeaways that emerge from the above table.

1. Fund X is volatile over the 5 year period with returns going as high as 81% in a year and as low as -70% in another year. The cumulative amount shows how much an investment of Rs1,000 in the fund would have grown to at the end of each year and after 5 years.

    

2. Fund Y is relatively stable over the 5 year period with returns almost even and no major positive or negative surprises. The cumulative amount shows how much an investment of Rs1,000 in the fund would have grown to at the end of each year and after 5 years.

    

3. If you look at the arithmetic mean of returns of the two funds, then Fund X has earned mean returns of 21.2% while Fund Y has earned mean returns of 12.56%. Obviously, Fund X looks better and also more exciting? But, there is a problem with that.

    

4. For longer period returns, it is not the arithmetic mean returns but the compounded average growth rate (CAGR) returns that really matter. That is captured in the cumulative amount column, where the corpus gets adjusted each year.

    

5. Now we come to a rather surprising and interesting conclusion. Fund Y has delivered 12.6% CAGR returns over the 5 year period, which is very close to the mean returns. However, in case of Fund X, the CAGR returns are just 4.32% against the mean returns of 21.2%. What explains this huge dichotomy in mean returns and CAGR returns for Fund X.

The reason why Fund Y created substantially more wealth at the end of 5 years compared to Fund X is the far lower volatility. Remember, Fund X had negative returns only in one out of the five years and in the other four years the returns were substantially in the positive. Yet, that one year of negative returns had a deep impact on the eventual performance of Fund X. In investment parlance, this phenomenon is often referred to as the “Difficulty of Bouncing Back.” Here is why it is a very serious problem in terms of portfolio returns.

Difficulty of bouncing back, is a very serious challenge

The difference between the mean returns and CAGR returns of Fund X can be explained by the difficulty of bouncing back. If you look at the annual returns of Fund X, it has earned negative returns in just 1 year while it has earned high positive returns in the other 4 years. But that one negative return is sufficient to bring down the CAGR returns of the fund over 5 years. That is due to the difficulty in bouncing back. Let us understand that with an arithmetic illustration of how this works in reality.

Base Amount	Correction in Price	Bounce to get back
Rs1,000	-40%	+66.67%
Rs1,000	-50%	+100%
Rs1,000	-60%	+150%
Rs1,000	-75%	+300%
Rs1,000	-80%	+400%
Rs1,000	-90%	+900%
Rs1,000	-95%	+1900%

Once you see the above table, the problem of bouncing back becomes so much more obvious. The real message is in the incremental difference that each fall makes to the difficulty of bouncing back. If a stock corrects 80% from the peak, it has to bounce back 5-fold to get back to the original price. However, if it falls by 90% instead of 80%, then it has to bounce back 10-fold to get back to the original price. Now, hold your breath! If the stock falls by 95%, then it has to bounce 20-fold to get back to the original price. 

Now you understand why the sharp fall of -70% in the fourth year of Fund X had such a deep impact on the CAGR returns of the fund. It just made bouncing back so much more difficult for the fund in question. The moral of the entire story is that volatility has a much bigger impact on your portfolio that you care to imagine. Even one bad year of negative volatility over a period of 5 years can be the reason for substantial underperformance. And that is largely on account of the difficulty of bouncing back.

Bottom line; Rather focus on optimization, than on excitement

If you thought that Fund X looks a lot more exciting, just think again. It comes with the huge risk of bouncing back to the base level. The impact of this difficulty in bouncing back can substantially magnify the losses and make it very tough to earn positive returns. That is why optimization focus not on high returns but on maximizing the returns for a given level of risk. That is the crux of optimal returns, so don’t fall for that adrenaline rush story again!

In any investment decision, be it in equities, mutual funds, or any other asset, focus purely on optimization of returns. Do not just look at the returns, but also at the volatility or risk of the asset or fund. Given an assumption of returns, you must just focus on selecting the asset with the lowest risk. That is half your investment job done and it begins with optimization. Excitement in the market is great; but that is not what you are invest your hard earned money for, in the first place!