investing

Why I never became a pundit

It’s been nearly a decade since i started writing in the mainstream media. Ahead of the Karnataka elections in 2013, I had published on this blog a series of quantitative analyses of the election, when R Sukumar (then editor-in-chief of Mint) picked it up and asked me if I could write for his paper on the topic – quantitative analysis of elections.

And so Election Metrics (what my pieces in Mint – they were analysis and not editorials, which meant it wasn’t a strict “column” per se, but I got paid well) was born. I wrote for Mint until the end of 2018, when my then contract ran out and Sukumar’s successor chose not to renew.

Having thus “cracked print”, I decided that the next frontier had to be video. I wanted to be on TV, as a pundit. That didn’t come easily. The 2014 national elections (when Modi first became PM) came and went, and I spent the counting day in the Mint newsroom, far from any television camera. I tried to get my way in to IPL auction analysis, but to no avail.

Finally, in 2018, on the day of the Karnataka elections, I got one guy I knew from way back to arrange for a TV appearance, and went on “News9” (a Bangalore-focussed English news channel) to talk about exit polls.

“I saw the video you had put on Facebook”, my friend Ranga said when he met me a few days later, “and you were waxing all eloquent about sample sizes and standard errors”. On that day I had been given space to make my arguments clear, and I had unleashed the sort of stuff you don’t normally see on news TV. Three days later, I got invited on the day of counting, enjoyed myself far less, and that, so far, has been the end of my career in punditry.

Barring a stray invitation from The Republic aside, my career in TV punditry has never gotten close to getting started after that. Of late I haven’t bothered, but in the past it has frequently rankled, that I’ve never been able to “crack TV”. And today I figured out why.

On my way to work this morning I was listening to this podcast featuring noted quant / factor investors Jim O’Shaughnessy and Cliff Asness. It was this nice episode where they spoke about pretty much everything – from FTX and AMC to psychedelics. But as you might expect with two quant investors in a room, they spent a lot of time talking about quantitative investing.

And then somewhere they started talking about their respective TV appearances. O’Shaughnessy started talking about how in the early days of his fund, he used to make a lot of appearances on Bloomberg and CNBC, but of late he has pretty much stopped going.

He said something to the effect of: “I am a quant. I cannot give soundbites. I talk in terms of stories and theories. In the 80s, the channels used to give me a minute or two to speak – that was the agreement under which I appeared on them. But on my last appearance, I barely got 10 seconds to speak. They wanted soundbites, but as a quant I cannot give soundbites”.

And then Asness agreed, saying pretty much the same thing. That it was okay to go on television in the time when you got a reasonable amount of time to speak, and build a theory, and explain stuff, but now that television has come down to soundbites and oneliners, he is especially unsuited to it. And so he has stopped going.

There it was – if you are the sort who is driven by theories, and you need space to explain, doing so over voice is not efficient. You would rather write, where there is room for constructing an argument and making your point. If you were to speak, unless you had a lot of time (remember that speaking involves a fair amount of redundancy, unlike writing), it would be impossible to talk theories and arguments.

And I realise I have internalised this in life as well – at work for example, I write long emails (in a previous job, colleagues used to call them “blogposts”) and documents. I try to avoid complicated voice discussions – for with my laborious style I can never win them. Better to just write a note after it is over.

How do bored investors invest?

Earlier this year, the inimitable Matt Levine (currently on paternity leave) came up with the “boredom markets hypothesis” ($, Bloomberg).

If you like eating at restaurants or bowling or going to movies or going out dancing, now you can’t. If you like watching sports, there are no sports. If you like casinos, they are closed. You’re pretty much stuck inside with your phone. You can trade stocks for free on your phone. That might be fun? It isn’t that fun, compared to either (1) what you’d normally do for fun or (2) trading stocks not in the middle of a recessionary crisis, but those are not the available competition. The available competition is “Animal Crossing” and “Tiger King.” Is trading stocks on your phone more fun than playing “Animal Crossing” or watching “Tiger King”?

The idea was that with the coming of the pandemic, there was a stock market crash and that “normal forms of entertainment” were shut, so people took to trading stocks for fun. Discount brokers such as Robinhood or Zerodha allowed investors to trade in a cheap and easy way.

In any case, until August, a website called RobinTrack used to track the number of account holders on Robinhood who were invested in each stock (or ETF or Index). The service was shut down in August after Robinhood shut down access to the data that Robintrack was accessing.

In any case, the Robintrack archives exist, and just for fun, I decided to download all the data the other day and “do some data mining”. More specifically I thought I should explore the “boredom market hypothesis” using Robintrack data, and see what stocks investors were investing in, and how its price moved before and after they bought it.

Now, I’m pretty certain that someone else has done this exact analysis. In fact, in the brief period when I did consider doing a PhD (2002-4), the one part I didn’t like at all was “literature survey”. And since this blog post is not an academic exercise, I’m not going to attempt doing a literature survey here. Anyways.

First up, I thought I will look at what the “most popular stocks” are. By most popular, I mean the stocks held by most investors on Robinhood. I naively thought it might be something like Amazon or Facebook or Tesla. I even considered SPY (the S&P 500 ETF) or QQQ (the Nasdaq ETF). It was none of those.

The most popular stock on Robinhood turned out to be “ACB” (Aurora Cannabis). It was followed b y Ford and GE. Apple came in fourth place, followed by American Airlines (!!) and Microsoft. Again, note that we only have data on the number of Robinhood accounts owning each stock, and don’t know how many stocks they really owned.

In any case, I thought I should also look at how this number changed over time for the top 20 such stocks, and also look at how the stocks did at the same time. This graph is the result. Both the red and blue lines are scaled. Red lines show how many investors held the stock. Blue line shows the closing stock price on each day.

The patterns are rather interesting. For stocks like Tesla, for example, yoou find a very strong correlation between the stock price and number of investors on Robinhood holding it. In other words, the hypothesis that the run up in the Tesla stock price this year was a “retail rally” makes sense. We can possibly say the same thing about some of the other tech stocks such as Apple, Microsoft or even Amazon.

Not all stocks show this behaviour, though. Aurora Cannabis, for example, we find that the lower the stock price went, the more the investors who invested. And then the company announced quarterly results in May, and the stock rallied. And the Robinhood investors seem to have cashed out en masse! It seems bizarre. I’m sure if you look carefully at each graph in the above set of graphs, you can tell a nice interesting story.

Not satisfied with looking at which stocks most investors were invested in this year, I wanted to look at which the “true boredom” stocks are. For this purpose, I looked at the average number of people who held the stock in January and February, and the maximum number of of people who held the stock March onwards. The ratio of the latter to the former told me “by how many times the interest in a stock rose”. To avoid obscure names, I only considered stocks held by at least 1000 people (on average) in Jan-Feb.

Unsurprisingly, Hertz, which declared bankruptcy in the course of the pandemic, topped here. The number of people holding the stock increased by a factor of 150 during the lockdown.

And if you go through the list you will see companies that have been significantly adversely affected by the pandemic – cruise companies (Royal Caribbean and Carnival), airlines (United, American, Delta), resorts and entertainment (MGM Resorts, Dave & Buster’s). And then in July, you see a sudden jump in interest in AstraZeneca after the company announced successful (initial rounds of) trials of its Covid vaccine being developed with Oxford University.

And apart from a few companies where retail interest has largely coincided with increasing share price, we see that retail investors are sort of contrarians – picking up bets in companies with falling stock prices. There is a pretty consistent pattern there.

Maybe “boredom investing” is all about optionality? When you are buying a stock at a very low price, you are essentially buying a “real option” (recall that fundamentally, equity is a call option on the assets of a company, with the strike price at the amount of debt the company has).

So when the stock price goes really low, retail investors think that there isn’t much to lose (after all a stock price is floored at zero), and that there is money to be made in case the company rallies. It’s as if they are discounting the money they are actually putting in, and any returns they get out of this is a bonus.

I think that is a fair way to think about investing when you are using it as a cure for boredom. Do you?

Shooting, investing and the hot hand

A couple of years back I got introduced to “Stumbling and Mumbling“, a blog written by Chris Dillow, who was described to me as a “Marxist investment banker”. I don’t agree with a lot of the stuff in his blog, but it is all very thoughtful.

He appears to be an Arsenal fan, and in his latest post, he talks about “what we can learn from football“. In that, he writes:

These might seem harmless mistakes when confined to talking about football. But they have analogues in expensive mistakes. The hot-hand fallacy leads investors to pile into unit trusts with good recent performance (pdf) – which costs them money as the performance proves unsustainable. Over-reaction leads them to buy stocks at the top of the market and sell at the bottom. Failing to see that low probabilities compound to give us a high one helps explain why so many projects run over time and budget. And so on.

Now, the hot hand fallacy has been a hard problem in statistics for a few years now. Essentially, the intuitive belief in basketball is that someone who has scored a few baskets is more likely to be successful in his next basket (basically, the player is on a “hot hand”).

It all started with a seminal paper by Amos Tversky et al in the 1980s, that used (the then limited) data to show that the hot hand is a fallacy. Then, more recently, Miller and Sanjurjo took another look at the problem and, with far better data at hand, found that the hot hand is actually NOT a fallacy.

There is a nice podcast on The Art of Manliness, where Ben Cohen, who has written a book about hot hands, spoke about the research around it. In any case, there are very valid reasons as to why hot hands exist.

Yet, Dillow is right – while hot hands might exist in something like basketball shooting, it doesn’t in something like investing. This has to do with how much “control” the person in question has. Let me switch fields completely now and quote a paragraph from Venkatesh Guru Rao‘s “The Art Of Gig” newsletter:

As an example, take conducting a workshop versus executing a trade based on some information. A significant part of the returns from a workshop depend on the workshop itself being good or bad. For a trade on the other hand, the returns are good or bad depending on how the world actually behaves. You might have set up a technically perfect trade, but lose because the world does something else. Or you might have set up a sloppy trade, but the world does something that makes it a winning move anyway.

This is from the latest edition, which is paid. Don’t worry if you aren’t a subscriber. The above paragraph I’ve quoted is sufficient for the purpose of this blogpost.

If you are in the business of offering workshops, or shooting baskets, the outcome of the next workshop or basket depends largely upon your own skill. There is randomness, yes, but this randomness is not very large, and the impact of your own effort on the result is large.

In case of investing, however, the effect of the randomness is very large. As VGR writes, “For a trade on the other hand, the returns are good or bad depending on how the world actually behaves”.

So if you are in a hot hand when it comes to investing, it means that “the world behaved in a way that was consistent with your trade” several times in a row. And that the world has behaved according to your trade several times in a row makes it no more likely that the world will behave according to your trade next time.

If, on the other hand, you are on a hot hand in shooting baskets or delivering lectures, then it is likely that this hot hand is because you are performing well. And because you are performing well, the likelihood of you performing well on the next turn is also higher. And so the hot hand theory holds.

So yes, hot hands work, but only in the context “with a high R Square”, where the impact of the doer’s performance is large compared to the outcome. In high randomness regimes, such as gambling or trading, the hot hand doesn’t matter.

Investing in ETFs

So I put some money in an ETF today. This isn’t the first time I invested in one. A long time back, before my then employer had bought and essentially killed Benchmark, I had invested in a couple of their ETFs – the Nifty ETF to get invest in the broad Indian market, and GoldBees to hedge against increase in the price of gold as I was planning my wedding.

I had some Rupees lying around in my bank account for a long time, and given that the Indian markets have tanked, I thought this is a good time to get invested. In fact, this isn’t the first time in recent times I’m having such a thought – about a month back I had put in more money into the Indian markets, but had then chosen a low cost index tracking mutual fund (and I’m not tracking how my investment is doing).

Anyway, today I decided to invest in ETFs since the transaction costs (in terms of both trading, and annual expenses) are much lower. A quick chat with a friend currently trading the Indian markets revealed that the SBI Nifty ETF is the best option to go with, and I was left with the small matter of just making the investment.

I’m generally happy with ICICI Direct as my broker, since in general the interface and app are pretty nice. Last month, the purchase of the mutual fund through the same app had been pretty simple. And I imagined buying the ETF will be easy as well. It wasn’t. And if I, as a professional investor with considerable capital markets experience, find it hard to invest in ETFs, I can only imagine how hard it might be for mango people to invest in them.

So the points of pain, in order, that prevent people from investing in ETFs:

Knowing that indexing exists. Most people seem to think that the only ways to invest are by researching the stocks themselves, or by paying an asset manager fairly hefty fees.
Once you know you can index, the fact that you can do it through an ETF. ETFs are again not well known, and not really marketed broadly since their fees are low (with Benchmark’s demise, we don’t really have ETF-first fund houses in India, like we have Vanguard in the US).
1. Related, even some of the more popular robo advisory funds in India largely use mutual funds, rather than ETFs.
Once you know you can index, and do so through an ETF, the next task is to find out which ETF you should invest in. Literature exists, but is not easy to find. My friend sent me this page, and asked me to select the fund with highest market size. Knowing that I want to invest in the broad market, and in large caps, the choice of SBI Nifty ETF was easy for me.
1. But it’s not so intuitive for a less sophisticated investor. For example, correlating asset size with liquidity isn’t exactly intuitive.
2. Different ETFs track different indices, and knowing which one to invest in is again not a trivial task.
Having selected an ETF to invest in, you go to your broker’s site or app (I used the app). And you need to know that ETFs are clubbed with equities, and not with mutual funds (not an intuitive classification for most people)
So I go to ICICI Direct’s Equities page, allocate funds to it (from my bank account, also with ICICI), and hit “buy”. There’s a text box where I need to enter what I’m looking for, and then there’s a dropdown that pops up.
I type “SBI”, and the first thing it shows is the SBI Bank Nifty tracker. This is followed by lots of bonds. I don’t know if it’s clever nudging on ICICI’s part to get you to invest in the Bank Nifty, since that has a significant exposure to ICICI, or if it’s something as mundane as alphabetical sorting. The latter is more likely.
Scrolling down the list past all the bonds, it’s not easy to know which is the SBI Nifty ETF. Because there’s a “SBI Nifty Next 50 ETF” (smaller caps, so more volatile, not something I want), and a few others with confusing names.
Then you need to enter the number of units you need to purchase. This is unlike in mutual funds where you just enter the amount you want to invest. Here I had to pull up a calculator to know exactly how many units I had to buy.
I hit “market order”, and then on the next screen I got a warning that since this wasn’t a particularly liquid instrument I was only allowed to post limit orders. So I had to guess what was a reasonable spread I was willing to pay, and put that. Thankfully the ETF was fairly liquid, and I got execution close to mid.

Honestly, I felt rather daunted at the end of the exercise, and I’m what most people would classify as a sophisticated investor. So there is no wonder that more people aren’t investing in ETFs.

The advantage of ETFs is extremely low fees (the fund I purchased today charges 7 basis points a year), and one downside of it is that it doesn’t allow for more marketing budget.

I’m beginning to think that the way to “solve” this market is by having a bundled ETF and robo advisory offering. Perhaps more on that later.

Weighting indices

One of the biggest recent developments in finance has been the rise of index investing. The basic idea of indexing is that rather than trying to beat the market, a retail investor should simply invest in a “market index”, and net of fees they are likely to perform better than they would if they were to use an active manager.

Indexing has become so popular over the years that researchers at Sanford Bernstein, an asset management firm, have likened it to being “worse than Marxism“. People have written dystopian fiction about “the last active manager”. And so on.

And as Matt Levine keeps writing in his excellent newsletter, the rise of indexing means that the balance of power in the financial markets is shifting from asset managers to people who build indices. The context here is that because now a lot of people simply invest “in the index”, determining which stock gets to be part of an index can determine people’s appetite for the stock, and thus its performance.

So, for example, you have indexers who want to leave stocks without voting rights (such as those of SNAP) out of indices. Some other indexers want to leave out extra-large companies (such as a hypothetically public Saudi Aramco) out of the index. And then there are people who believe that the way conventional indices are built is incorrect, and instead argue in favour of an “equally weighted index”.

While one an theoretically just put together a bunch of stocks and call it an “index” and sell it to investors making them believe that they’re “investing in the index” (since that is now a thing), the thing is that not every index is an index.

Last week, while trying to understand what the deal about “smart beta” (a word people in the industry throw around a fair bit, but something that not too many people are clear of what it means) is, I stumbled upon this excellent paper by MSCI on smart beta and factor investing.

About a decade ago, the Nifty (India’s flagship index) changed the way it was computed. Earlier, stocks in the Nifty were weighted based on their overall market capitalisation. From 2009 onwards, the weights of the stocks in the Nifty are proportional to their “free float market capitalisation” (that is, the stock price multiplied by number of shares held by the “public”, i.e. non promoters).

Back then I hadn’t understood the significance of the change – apart from making the necessary changes in the algorithm I was running at a hedge fund to take into account the new weights that is. Reading the MSCI paper made me realise the sanctity of weighting by free float market capitalisation in building an index.

The basic idea of indexing is that you don’t make any investment decisions, and instead simply “follow the herd”. Essentially you allocate your capital across stocks in exactly the same proportion as the rest of the market. In other words, the index needs to track stocks in the same proportion that the broad market owns it.

And the free float market capitalisation, which is basically the total value of the stock held by “public” (or non-promoters), represents the allocation of capital by the total market in favour of the particular stock. And by weighting stocks in the ratio of their free float market capitalisation, we are essentially mimicking the way the broad market has allocated capital across different companies.

Thus, only a broad market index that is weighted by free flow market capitalisation counts as “indexing” as far as passive investing is concerned. Investing in stocks in any other combination or ratio means the investor is expressing her views or preferences on the relative performance of stocks that are different from the market’s preferences.

So if you invest in a sectoral index, you are not “indexing”. If you invest in an index that is weighted differently than by free float market cap (such as the Dow Jones Industrial Average), you are not indexing.

One final point – you might wonder why indices have a finite number of stocks (such as the S&P 500 or Nifty 50) if true indexing means reflecting the market’s capital allocation across all stocks, not just a few large ones.

The reason why we cut off after a point is that beyond that, the weightage of stocks becomes so low that in order to perfectly track the index, the investment required is significant. And so, for a retail investor seeking to index, following the “entire market” might mean a significant “tracking error”. In other words, the 50 or 500 stocks that make up the index are a good representation of the market at large, and tracking these indices, as long as they are free float market capitalisation weighted, is the same as investing without having a view.

Why VCs continue to fund me-too startups

In a previous post, I had written about how a large number of startups in India are “me-too” companies, and that a sector, once it becomes hot, gets overcrowded. I had also expressed incredulity at the fact that Venture Capitalists continue to fund such “me-too” startups despite knowing that they are copies of companies that exist.

Thinking about it, however, there is one reason that makes the decisions by VCs to fund me-too startups worthwhile – mergers and acquisitions. And this hypothesis is based on M&A activity in the “hyperlocal delivery” (one of those “hot” buzzphrases) space.

Nowadays, due to activity in the sector, the hyperlocal delivery sector has become the equivalent of Pets.com from the turn of the millennium. At a conversation a month ago, for example, a bunch of us weren’t able to fathom how something like Swiggy is valued at what it is, given its decidedly low-tech business of taking packed food from restaurants and delivering it to customers. A couple of months before that, TinyOwl, which is in a very similar business, had raised similar money.

But then two events in the recent (and maybe not-so-recent) past have indicated why VCs continue to invest (and heavily ) in such sectors. Firstly, in February, Foodpanda acquired the Indian operations of Justeat. Both companies are in the business of delivering packed foods from restaurants to people’s homes. And last week, grocery retailer BigBasket acquired Delyver, yet another company in the business of transporting packed food from restaurants to homes.

There is this Panchatantra story about a Jackal and a dead elephant. Basically a jackal comes across a dead elephant, and wants to eat it. But for this, he has to fight off other competitors, and also get the elephant’s skin torn in the process. The story involves how he uses different strategies to outwit different animals. Here is a youtube video, not very well made, of this story:

https://www.youtube.com/watch?v=IXF51y3uZJA

This is the cover of the Amar Chitra Katha edition where I first came across this story.

And this link has a good summary of the story, all you need to know. Exactly like how it’s in the Amar Chitra Katha story.

The moral I derive from this story in this context is that there are different ways to deal with opponents/competitors. Some opponents you just fight off and finish. Others you learn to coexist with. Yet other you simply “swallow” or acquire. Each of them has its own set of payoffs.

Based on the deals described above, what we notice in the “transport-of-packed-food-from-restaurant-to-homes” business is that companies are preferring to swallow each other (and coexisting with some others) rather than fighting. And when one company acquires another, investors in the target company get a “soft landing”, and don’t lose all of their investment (though it is well possible that the acquisition happens at a valuation lower than that when the investors invested, but ratchets might take care of that).

Apart from investors not losing too much, the advantage of acquisitions is that existing infrastructure of an erstwhile competitor can be leveraged. And when companies are in growth mode and profit and cash are not as important as growth, an acquisition works really well in generating significant inorganic growth. It is a win-win for multiple reasons.

The fact that mergers are the preferred way of getting rid of competition in the startup world puts a cap on the losses an investor might have to bear on an investment (and there are ratchets in any case). And since the downside is now limited, the risk of investing in a me-too startup is significantly lower. In other words, investors invest in a me-too startup since they believe that in the near-worst case it will get acquired rather than shut down. And as a further consequence, there is more incentive for entrepreneurs to set up me-too startups (assuming they can get funded) rather than venturing into virgin territory.

I made some money in the markets last week. I bought the Nifty (September futures) at around 5190 on the 28th of August and cashed out at 5660 on the 6th of September. A fair trade I think, considering that so far in my life I’ve been a fairly poor investor (despite having worked as a quant at an investment bank and a hedge fund). This trade, however, raised more questions than answers.

Firstly, the markets have gone up significantly after I sold out. I exited at 5660. The Nifty closed today at well over 5900. Last couple of days I’ve been wondering if I panicked and cashed out too early. I must admit that when I entered I had a target price of 6000. However, given the rather choppy nature of the Indian markets, I decided that the 10% appreciation in 10 days was enough and cashed out. To that extent, I didn’t stay honest to the strategy I entered the trade in.

However, the reason I decided to cash out when I did was that I thought the market was going to top out and a steep fall was imminent. From that perspective, it made sense to cash out when I did. Yes, I might have made more money had I hung on for another two trading days, but there was no guarantee that the markets would continue to rise. In that sense I was happy pulling out.

More importantly when I cashed out, I realized that I’m still an amateur at investing. When you are a professional investor, you look at investment vehicles in terms of opportunity cost. If you wanted to pull out of the Nifty, you would do so only if you could put your money in another investment which would give you superior returns to what the Nifty would in the subsequent time period (technically hard currency is also an investment!), after accounting for the transaction cost of switching. As far as I was concerned here, though, I still invest basically for kicks (don’t invest huge amounts). So it’s basically about spotting a potential boom, riding it and then moving out. Light touch investing.

There are times when I want to get back to the world of investment (as a professional). I have some unique ideas for fund management. Perhaps I should use my next break in billable work to flesh that out. For now, check out my only other post on investing – on why you should not track your portfolio too closely.