‘In investing, you have to first make sure you don’t make big mistakes.’
‘I would advise small investors to be systematic, don’t be arbitrary; don’t be on either end of the risk spectrum.’
‘Don’t go from fixed deposit to option trading or crypto trading.’
In the second part of this interview with Prasanna D Zore/Rediff.com, Devina Mehra, chairperson and managing director, First Global deep dives into the rules and systems that has helped her company ace returns for small investors even while containing risk and drawdowns, a parameter that scares small investors away from the markets.
How do you define a small investor and how is the First Global HPM system working for small investors? What provides this fund the edge?
Everybody has a different impression of what a small investor is, just as everyone has a different idea of what middle classes in India, what are very upper class people also call themselves middle class.
As far as the PMS is concerned, there’s a Sebi (the market regulator Securities and Exchange Board of India) mandated minimum of Rs 50 lakh (Rs 5 million). You cannot open a PMS account with less than Rs 50 lakh but for the smaller investor (having lesser investment capacity), our Smallcase starts from about Rs two lakh (Rs 200,000) or so.
We have always conscientiously believed that as far as the Indian small investor is concerned, they should be able to access global markets and have true global diversification. So we have a product which starts at US $10,000, which is about over eight lakh rupees (Rs 800,000). That is what we wanted to do for the small investor.
The Smallcase came about because we had the PMS (which mandates an investment not less than Rs 50 lakh) and there was a lot of demand from people asking why don’t we have something for people who cannot invest Rs 50 lakh.
That is a significant amount in the Indian context (not many investors would have that kind of investible corpus) and that’s how we started the Smallcase.
I would advise the small investors to be systematic, don’t be arbitrary; don’t be on either end of the risk spectrum. Don’t go from fixed deposit to option trading or crypto trading.
That’s the latest fad among small investors. That’s what most small investors think brings quick money, easy money. They fear they will miss out on that apparently easy-money-making-route.
How do you manage risk and avoid falling into the fear of missing out (FOMO) trap? I’m sure you must be having solid processes running at the back end clearly defining what risks you are taking, what kind of returns you are expecting.
Could you give us a glimpse into this processes that you use to contain risk?
The base system, the bottom-up system is something we call Turbo, which is based on artificial intelligence and machine learning.
All the companies that meet a cut off, like in India, the cut off is Rs 1,000 crore (Rs 10 billion) market cap (we don’t invest in companies with market cap less than this limit), we will then rank (the companies whose market cap is more than Rs 1,000 crore), which is about 700 stocks (that is how we filter the universe of stocks in which to invest).
Our system will rank all those 700 (companies) from one to 700. And then we will like, let’s say we have to choose 50 stocks, so we will choose them.
After that we have overlay of some other human understanding and channel checks. This way we are able to choose those 50 stocks out of the top 70-75. We are not going to go to stock number 200. That’s the discipline, it (our method of stock-picking) mandates.
For risk management we use a lot of things. For example, it is not just market cap. We will look at liquidity also because in small caps it is very easy to get in when you want to get out, the doors are shut. So liquidity is important. We will never have an outsized allocation to any sector or for that matter to small caps. Even when we see the small caps are doing well, it might go up from 15 per cent allocation to maybe 22 per cent allocation. We are never going to go to 40-45 per cent small cap.
Then we use hedges. Like at the time of the Russia Ukraine war. Whenever we think there is risk of a crash or too much volatility, we will hedge. Of course, hedges have a cost, so you will not be hedged 100 per cent of the time.
We have systems again that enable you to look at risk comprehensively. For example Amazon is both a tech company and an e-commerce company, which means it’s a retailer and a tech company, so it might move with both those clusters. Our systems are very rigorous, very elaborate and they allow us to track risks and provide many legs to our risk management.
My basic philosophy is that investing is a loser’s game. There is a very good, almost 50-year-old article called The Loser’s Game by Charles Ellis (external link: https://www.empirical.net/wp-content/uploads/2012/06/the_losers_game.pdf), which talks about how everything in life is a winner’s game or a loser’s game.
Investing may have started out as a winner’s game when excel sheets didn’t exist, where information did not exist to that extent, so you might know of a company which nobody knew of or what’s happening there.
Now with so many smart people, with so much data with everyone, you are not going to be right all the time. You have to first make sure that there are no big drawdowns, that you are not on the loser’s side and then the market will give you opportunities to be the winner.
That’s the way we play the game.
When you say investing is a loser’s game, it’s kind of a paradox where if I were an investor, if investing is a losing game, why would I invest? How do you convince people that they must invest?
It is not a losing game; it is a loser’s game and you must make sure you are not the loser. You must make sure that you are not taking outsized risks which will decimate your capital to a large extent, so that you cannot play the game anymore.
It is like aviation when J R D Tata and Charles Lindbergh were flying was an adventure sport. You had to make decisions on the fly, maybe not even have the right part and make do with some part. Now there’s only one way to play the aviation game, which is go by the checklist and make no mistakes.
So in investing also you have to first make sure you don’t make big mistakes.
That is what a loser’s game is; it is like if you are playing tennis at the Grand Slam level, you have to be very good. That is a winner’s game. But when you are playing tennis at the club level, your effort should be not to make mistakes. Just keep the ball in play and the other guy will make enough mistakes for you to win. So the focus has to be on no mistakes.
No mistake doesn’t mean none of your decisions will go wrong. You have to ensure that when your decisions are wrong, you don’t suffer huge losses.
Let me emphasise on the part I missed that out in risk management that we are strict on stop losses. While we say it’s a Human Plus Machine system on the investing side, it is a machine-only system on the risk management side in many aspects, including stop losses.
The human tendency is always to say that I was right (not to accept mistakes when one goes wrong), we should wait it out; maybe this stock is different. Basically, keep making some deviation from the system you have set. You should not allow human emotions to override the system.
The only way the human beings can override the risk management system is to make the risk parameters tighter, never more lax.
When you talk about stop losses, are these stock specific stop losses or do you have a system in place wherein you derive a stop loss looking at the entire portfolio?
The system derives the stop losses which are stock specific.
While we say ours is a human plus machine system, it’s a human plus machine system on the investment side, not on the risk management and specifically stop-loss side.
Human tendency is to not admit mistakes, to say that I was right, this time it is different, this stock is different, let me wait a while.
So all those kind of things (human emotions that cloud investing decisions) we eliminate by having system generated stop loss and yes, that stop loss will, number one, be on a trailing basis. It is not from your purchase price, it is from the high that stock had reached.
For example, if I buy something at Rs 50, and let’s say the stop loss is 25 per cent, and if it goes up to Rs 200 and then comes to Rs 150, we will exit.
That’s how the stop loss works and it is not exactly the same percentage for every stock because for a very low-volatility, defensive stock, you might have stop loss, like 25 per cent might be too much for them.
Maybe you should exit if it falls 20 per cent. Whereas for another very volatile stock the stop loss might be a little further away.
It is system generated and depends on the stock volatility as well.
Tell us what those human emotions are that give birth to FOMO and how should small investors tackle these fears or emotions?
This is a difficult one because it is virtually impossible to eliminate human biases and also random noise.
There’s a very good book that I often talk about, Thinking, Fast and Slow by Daniel Kahneman, which is all about human cognitive biases; he’s won a Nobel Prize for that work. And then he has written Noise: A Flaw in Human Judgement also.
He says that in spite of spending my entire lifetime doing this work, my decision-making still suffers from biases because these are so hardwired (into our brain), these are evolutionary.
It is like an optical illusion. You see an optical illusion, you are told that these two lines or these two objects look different, but they are the same.
Even after you intellectually understand that, your eyes still see it the same way. It is like that for human biases as well, that everything appears a different way, but what the reality is, you can never really perceive.
I would tell small investors that first of all, you write down why you are buying a stock, what your thesis is, keep documenting (all these things) because your mind will play tricks. It will tell you that you thought something different from what you actually thought. That is one.
Use a system. What also happens is that in fact, Daniel Kahneman also says that almost any properly designed system, even if it is not very elaborate, will outperform a human being, because a human being, besides the biases, is also prone to random noise.
For example, if you give the same data to 15 qualified financial analysts, they will come to a different conclusion about that company. Not only that, the same person might come to a different conclusion depending on whether she had a fight in the traffic in the morning or what her mood is like or something like that. We are all prone to that.
Let’s say, as a small investor, you say that I want to buy high growth company or with good return ratios or whatever those three, four criteria of yours are, make sure you put it in a system and do that. Because otherwise you will find that you think you are doing this, but you are actually not doing it; when you look at your portfolio, you bought something because you heard about it on TV, because some friend told you about it. So you have to, first of all, make sure you are doing what you are supposed to be doing.
The other thing, which is actually much easier to do than eliminating biases, is that get your asset allocation right. This is a basic of investing.
It’s there on the first page of any book on investing that 85 per cent to 90 per cent of your returns in investing come from asset allocation, not from a particular stock you buy.
How much do you have in equity?
How much do you put equity mutual fund?
How much do you have in fixed income? Fixed deposits are slightly different from a fixed income mutual fund.
How much do you have in gold? How much do you have in real estate? So know that and then consciously make that allocation.
Most importantly, how much do you have globally? This is something Indians don’t think about, because we did not have capital account convertibility 20 years ago. Now, the Liberalized Remittance Scheme (LRS) is very generous. Over time, make sure at least 30-40 per cent of your corpus is global.
I’ll give you an example why you must go global.
When I started working, the US$1 was Rs 12. Now it is above 82. So there’s like 85 per cent depreciation in the course of less than ten years. It is issues like this that pushed me towards globalisation almost 25 years ago.
We were the first Asian firm to become a member of the London Stock Exchange back in 1999.
How do you fine tune your research and zero in on a particular company that becomes a must have in your portfolio? Could you talk about the processes, the parameters that you use to choose companies that you would invest in?
At first we used to do it the human way.
This is another thing which has evolved why we went from human only to human plus machine. And the reason for that was that it (investing) is like (playing) hockey. All of us know that hockey was our national game. Today, we’ve not been anywhere in the hockey rankings for decades.
Why was hockey our national game? It was a national game because we dominated hockey from 1930s to 1970s. Earlier it was only India; then it was India and Pakistan. Why did we lose out completely? Because the playing field changed from natural grass to Astro Turf and the skills required, therefore, changed.
All that lovely dribbling and stick work went out of the window and what mattered was how fit you were; how fast you could run where Indians were not that good. In investing too, something similar has been happening.
In investing something like that happened. Earlier the edge was that you could get some differential information by meeting companies. This is true not just of India, but Fidelity could get something different from an IBM or Walmart by sitting in a room.
I did a lot of that and I love doing it; in the 1990s I went to not just company offices, but I saw so many plants (factories of companies which were potential investments or companies where investments had already been made) of all kinds, from steel to cement to automobiles and so on. Now that game has changed.
The game now is that all over the world regulators insist that all information has to be available to everyone, you cannot give differential information.
Earlier for example, it was a big deal to be even called for a conference call (where the company managements speak with potential investors and brokerages who then publish research reports based on these calls and the information gathered during these calls) after (quarterly or annual) results. Now everybody gets the same transcript.
The edge has now moved from getting the information to processing the tons of information (intelligently to make investment decisions) that is available to everyone.
That is the reason why we moved over time to this artificial intelligence and machine learning system which on an unbiased basis can look at 700 securities (companies that trade in stock markets) and rank them or globally we look at more than 20,000 securities.
No matter how large a research team I have, I cannot look at 20,000 securities or look at them consistently, even if I have 1000 analysts; they are not going to look at everything the same way.
The system enables you to do that and that’s why now you see that most people are still managing funds the way they were in the 1990s and that is why most of them are underperforming because the game has changed and their game has not changed.
The playing field has changed.
