Christian Rudder and Corporate Ratings

One of the studdest book chapters I’ve read is from Christian Rudder’s Dataclysm. Rudder is a cofounder of OkCupid, now part of the match.com portfolio of matchmakers. In this book, he has taken insights from OkCupid’s own data to draw insights about human life and behaviour.

It is a typical non-fiction book, with a studmax first chapter, and which gets progressively weaker. And it is the first chapter (which I’ve written about before) that I’m going to talk about here. There is a nice write-up and extract in Maria Popova’s website (which used to be called BrainPickings) here.

Quoting Maria Popova:

What Rudder and his team found was that not all averages are created equal in terms of actual romantic opportunities — greater variance means greater opportunity. Based on the data on heterosexual females, women who were rated average overall but arrived there via polarizing rankings — lots of 1’s, lots of 5’s — got exponentially more messages (“the precursor to outcomes like in-depth conversations, the exchange of contact information, and eventually in-person meetings”) than women whom most men rated a 3.

In one-hit markets like love (you only need to love and be loved by one person to be “successful” in this), high volatility is an asset. It is like option pricing if you think about it – higher volatility means greater chance of being in the money, and that is all you care about here. How deep out of the money you are just doesn’t matter.

I was thinking about this in some random context this morning when I was also thinking of the corporate appraisal process. Now, the difference between dating and appraisals is that on OKCupid you might get several ratings on a 5-point scale, but in your office you only get one rating each year on a 5-point scale. However, if you are a manager, and especially if you are managing a large team, you will GIVE out lots of ratings each year.

And so I was wondering – what does the variance of ratings you give out tell about you as a manager? Assume that HR doesn’t impose any “grading on curve” thing, what does it say if you are a manager who gave out an average rating of 3, with standard deviation 0.5, versus a manager who gave an average of 3, with all employees receiving 1s and 5s.

From a corporate perspective, would you rather want a team full of 3s, or a team with a few 5s and a few 1s (who, it is likely, will leave)? Once again, if you think about it, it depends on your Vega (returns to volatility). In some sense, it depends on whether you are running a stud or a fighter team.

If you are running a fighter team, where there is no real “spectacular performance” but you need your people to grind it out, not make mistakes, pay attention to detail and do their jobs, you want a team full of3s. The 5s in this team don’t contribute that much more than a 3. And 1s can seriously hurt your performance.

On the other hand, if you’re running a stud team, you will want high variance. Because by the sheer nature of work, in a stud team, the 5s will add significantly more value than the 1s might cause damage. When you are running a stud team, a team full of 3s doesn’t work – you are running far below potential in that case.

Assuming that your team has delivered, then maybe the distribution of ratings across the team is a function of whether it does more stud or fighter work? Or am I force fitting my pet theory a bit too much here?

Conductors and CAPM

For a long time I used to wonder why orchestras have conductors. I possibly first noticed the presence of the conductor sometime in the 1990s when Zubin Mehta was in the news. And then I always wondered why this person, who didn’t play anything but stood there waving a stick, needed to exist. Couldn’t the orchestra coordinate itself like rockstars or practitioners of Indian music forms do?

And then i came across this video a year or two back.

And then the computer science training I’d gone through two decades back kicked in – the job of an orchestra conductor is to reduce an O(n^2) problem to an O(n) problem.

For a  group of musicians to make music, they need to coordinate with each other. Yes, they have the staff notation and all that, but still they need to know when to speed up or slow down, when to make what transitions, etc. They may have practiced together but the professional performance needs to be flawless. And so they need to constantly take cues from each other.

When you have n musicians who need to coordinate, you have \frac{n.(n-1)}{2} pairs of people who need to coordinate. When n is small, this is trivial, and so you see that small ensembles or rock bands can easily coordinate. However, as n gets large, n^2 grows well-at-a-faster-rate. And that is a problem, and a risk.

Enter the conductor. Rather than taking cues from one another, the musicians now simply need to take cues from this one person. And so there are now only n pairs that need to coordinate – each musician in the band with the conductor. Or an O(n^2) problem has become an O(n) problem!

For whatever reason, while I was thinking about this yesterday, I got reminded of legendary finance professor R Vaidya‘s class on capital asset pricing model (CAPM), or as he put it “Sharpe single index model” (surprisingly all the links I find for this are from Indian test prep sites, so not linking).

We had just learnt portfolio theory, and how using the expected returns, variances and correlations between a set of securities we could construct an “efficient frontier” of securities that could give us the best risk-adjusted return. Seemed very mathematically elegant, except that in case you needed to construct a portfolio of n stocks, you needed n^2 correlations. In other word, an O(n^2) problem.

And then Vaidya introduced CAPM, which magically reduced the problem to an O(n) problem. By suddenly introducing the concept of an index, all that mattered for each stock now was its beta – the coefficient of its returns proportional to the index returns. You didn’t need to care about how stocks reacted with each other any more – all you needed was the relationship with the index.

In a sense, if you think about it, the index in CAPM is like the conductor of an orchestra. If only all O(n^2) problems could be reduced to O(n) problems this elegantly!

IPOs and right to match

Long time readers of the blog might know that I’m not a big fan of the IPO pop. I’ve traditionally belonged to the party (led by Bill Gurley) that says that a big IPO pop is akin to “leaving money on the table” for the company.

And so as my party has grown, the IPO process itself has also changed. Way back in 2004, Google allocated shares using a simple Dutch auction. Facebook pushed its bankers hard enough on the IPO price that the IPO “pop” in that case was negative. Spotify and Slack and a few other companies went public in a direct listing. Nowadays you have SPACs. It’s all very interesting stuff for anyone interested in market design.

Over the last few years, though, Matt Levine has been trying hard (and sort of succeeding), in getting to move me to the side that says IPO pops are okay. His first compelling argument was the demand-supply (and market depth) one – in an IPO there is a large offload of shares, and so an IPO buyer can expect to get a discount on the shares. Another is that since the IPO is the first time the stock will be traded, buyers in the IPO are taking risk, and need to be compensated for it in the form of a lower price. Fair enough again.

Matt has outdone himself in his latest newsletter on the topic, where he talks about the IPOs of Roblox and Coupang. About Roblox, he wrote:

I mean, I’ll tell you the answer[1]: Roblox sold stock to venture capitalists at $45, and then it traded up in public markets to $70. In a traditional initial public offering, a company sells stock to mutual funds at $45, and then it trades up in public markets to $70. Venture capitalists are not happy when mutual funds get underpriced stock: It dilutes existing shareholders and “leaves money on the table.” Venture capitalists are of course perfectly happy when venture capitalists get underpriced stock; that’s the business they are in.

This served the purpose of moving me more to his side.

This blogpost, however, is about the Coupang IPO.

All normal enough. But here’s the unusual thing about Coupang. Apparently, of the hundreds of investors who put in orders to buy shares in the IPO—many of whom did roadshow meetings and put in work to understand the company and come up with a price—fewer than 100 were allocated any shares, with most of those shares going to about 25 accounts handpicked by Coupang. Coupang apparently kept tight control over the allocation, choosing its investors itself rather than deferring to its underwriters (led by Goldman Sachs Group Inc.). Now those favored investors—investors favored by Coupang, not investors favored by Goldman—will benefit from the IPO pop. Everyone else, who put in the work and decided they wanted to own Coupang, will have to buy in the aftermarket, from those initial investors, and pay up to do so.

Obviously Coupang has left money on the table, but who cares? Coupang underpriced its IPO, but the beneficiaries of the underpricing are the existing investors that it wanted to benefit.

Basically Coupang announced an IPO at a $27-30 price range. It did a roadshow to gauge investor demand. Demand was strong. And then the price range was upped to $31-34. Demand was strong once again. And then, instead of letting its banker Goldman Sachs price the IPO at 34, and allocate the shares to who Goldman thought would make the best investors, Coupang went to its existing investors and told them “we have a bunch of investors willing to buy our stock at $34. What do you think?”

And the existing investors, finding validation, said “Oh, in that case we can pay $35 for it”. In IPL auction parlance, Coupang’s existing investors basically had a “right to match option”. All the other potential investors were asked, and then the existing investors were “more equal” than the others.

The stock duly popped.

Now, right to match in an IPO might be an interesting structure, but I highly doubt that it will sustain. Basically banks won’t like it. Put yourself in Goldman’s shoes for a moment.

They have done all the hard work of pricing the IPO and taking it to potential clients and doing all the paperwork, and at the end of it, their buy side clients are a mostly pissed of bunch – they’ve again done all the hard work of deciding whether the IPO was worth it and then told that they were cut out of the deal.

The least Goldman’s buy side clients would have wanted is the right to match Coupang’s original investors’ offer ($35). Having done all the hard work, and then being forced to buy the stock (if at all) at the popped price of $49, they will be a totally miffed lot. And they would have conveyed their displeasure to Goldman.

One thing about IPOs is that the companies selling the stock play a one-time game, while the bankers (and IPO investors) play a repeated game, participating in IPOs regularly. And because of this, the incentive structure of IPOs is that bankers tend to favour buy side clients than sell side, and so the big pop. And so bankers will not regularly want to do things that will piss off the buy side, such as offering “right to match” to the selling company’s chosen investors.

So will we see more such IPOs?

My take is that inspired by Coupang, some more companies might insist on a right to match while selling their shares in an IPO. And this right to match will piss off the buy side, who will push back against the bankers and demand a right to match for themselves.

And what happens when both sides (company’s favourite investors and bank’s favourite investors) insist on a mutual right to match? We get an auction of course.

I don’t think anyone will have that much of a problem if IPO share allocation gets resolved by a Dutch auction, like Google did way back in 2004.

Monetising volatility

I’m catching up on old newsletters now – a combination of job and taking my email off what is now my daughter’s iPad means I have a considerable backlog – and I found this gem in Matt Levine’s newsletter from two weeks back  ($; Bloomberg).

“it comes from monetizing volatility, that great yet under-appreciated resource.”

He is talking about equity derivatives, and says that this is “not such a good explanation”. While it may not be such a good explanation when it comes to equity derivatives itself, I think it has tremendous potential outside of finance.

I’m reminded of the first time I was working in the logistics industry (back in 2007). I had what I had thought was a stellar idea, which was basically based on monetising volatility, but given that I was in a company full of logistics and technology and operations research people, and no other derivatives people, I had a hard time convincing anyone of that idea.

My way of “monetising volatility” was rather simple – charge people cancellation fees. In the part of the logistics industry I was working in back then, this was (surprisingly, to me) a particularly novel idea. So how does cancellation fees equate to monetising volatility?

Again it’s due to “unbundling”. Let’s say you purchase a train ticket using advance reservation. You are basically buying two things – the OPTION to travel on that particular day using that particular train, sitting on that particular seat, and the cost of the travel itself.

The genius of the airline industry following the deregulation in the US in the 1980s was that these two costs could be separated. The genius was that charging separately for the travel itself and the option to travel, you can offer the travel itself at a much lower price. Think of the cancellation charge as as the “option premium” for exercising the option to travel.

And you can come up with options with different strike prices, and depending upon the strike price, the value of the option itself changes. Since it is the option to travel, it is like a call option, and so higher the strike price (the price you pay for the travel itself), the lower the price of the option.

This way, you can come up with a repertoire of strike-option combinations – the more you’re willing to pay for cancellation (option premium), the lower the price of the travel itself will be. This is why, for example, the cheapest airline tickets are those that come with close to zero refund on cancellation (though I’ve argued that bringing refunds all the way to zero is not a good idea).

Since there is uncertainty in whether you can travel at all (there are zillions of reasons why you might want to “cancel tickets”), this is basically about monetising this uncertainty or (in finance terms) “monetising volatility”. Rather than the old (regulated) world where cancellation fees were low and travel charges were high (option itself was not monetised), monetising the options (which is basically a price on volatility) meant that airlines could make more money, AND customers could travel cheaper.

It’s like money was being created out of thin air. And that was because we monetised volatility.

I had the same idea for another part of the business, but unfortunately we couldn’t monetise that. My idea was simple – if you charge cancellation fees, our demand will become more predictable (since people won’t chumma book), and this means we will be able to offer a discount. And offering a discount would mean more people would buy this more predictable demand, and in the immortal jargon of Silicon Valley, “a flywheel would be set in motion”.

The idea didn’t fly. Maybe I was too junior. Maybe people were suspicious of my brief background in banking. Maybe most people around me had “too much domain knowledge”. So the idea of charging for cancellation in an industry that traditionally didn’t charge for cancellation didn’t fly at all.

Anyway all of that is history.

Now that I’m back in the industry, it remains to be seen if I can come up with such “brilliant” ideas again.

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?

Conductors and CAPM

Recently I watched this video that YouTube recommended to me about why orchestras have conductors.

The basic idea is that an orchestra  needs a whole lot of coordination, in terms of when to begin and end, when to slow down or speed up, when to move to the next line and so on. And in case there is no conductor, the members of the orchestra need to coordinate among themselves.

This is easy enough when there is a small number of members, so you don’t see bands (for example) needing conductors. However, notice that if the orchestra has to coordinate among themselves, coordination is an O(n^2) problem. By appointing an external conductor whose only job is to conduct and not play, this O(n^2) problem is reduced to an O(n) problem.

When I saw this, this took me back to my Investments course in IIMB, where the professor one day introduced what he called the “Sharpe single index model“, which is sort of similar to the CAPM.

Just before learning the Sharpe Single Index Model, we had been learning about Markowitz’s portfolio theory. And then, as he introduced the Sharpe Single Index Model, Vaidya said something to the effect that “instead of knowing so many correlation terms” (which is an O(n^2) problem), “we only need to know the correlation of each stock to the market index” (makes it an O(n) problem).

As someone who has studied computer science formally, converting O(n^2) problems to O(n) problems is a massive fascination. It is interesting how I connected two such reductions from completely different fields.

In other words, conductors are the “market of the orchestra”.

People are worried about marriage market liquidity

Every time we have a sort of financial crisis that has something to do with settlement, and collaterals, and weird instruments, people start questioning why more instruments are not traded on exchanges. They cite the example of equities, which world over are exchange traded, centrally settled, and whose markets function rather efficiently.

After the 2008 Financial Crisis, for example, there was a move to take Credit Default Swaps (CDS) to exchanges, rather than letting the market go over the counter (OTC). Every few years, ideas are floated about trading bonds on exchanges (rather than OTC, like they are now), and the blame falls on “greedy bankers who don’t want to let go of control”.

There is an excellent podcast by Bloomberg Odd Lots where Chris White, a former Goldman Sachs banker, talks about how the equity markets went electronic in the 1970s with NASDAQ, and how the “big bang” in the UK markets propelled equities into electronic trading everywhere.

A lot of these ideas have also been discussed in my book on market design

In any case, I think I have the perfect explanation of why bond trading on exchanges hasn’t really taken off. To understand this, let’s look at another market that I discussed extensively in my book – the market for relationships (that chapter has been extracted in Mint).

The market for relationships is in the news thanks to this Netflix documentary called Indian Matchmaking. I started watching it on a whim on Saturday night, and I got so addicted to it that yesterday I postponed my work to late night so that I could finish the show instead.

Marriage can be thought of as a sale of “50% of the rest of your life“, paid for by 50% of the rest of someone else’s life.

There are two ways you can go about it – either “over the counter” (finding a partner by yourself) or “exchange traded” (said exchange could be anything from newspaper classifieds to Tinder to Shaadi.com). Brokers are frequently used in the OTC market – either parents or friends (who set you up) or priests.

The general rule of markets is that the more bespoke (or “weird” or “unusual”) an instrument is, the better the likelihood of finding a match in the OTC markets than on exchanges. The reason is simple – for an exchange to exist, the commodity being traded needs to be a commodity.

Read any literature on agricultural markets, for example, and they all talk about “assaying” and “grading” the commodities. The basic idea is that all goods being traded on a marketplace are close enough substitutes of each other that they can be interchanged for each other.

Equity shares, by definition, are commodities. Equity and index derivatives are commodities as well, easy enough to define. Commodities are, by definition, commodities. Bond futures are commodities, since they can be standardised on a small number of axes. We’ll come to bonds in a bit.

Coming back to relationship markets, the “exchanges” work best if you have very few idiosyncrasies, and can be defined fairly well in terms of a small number of variables. It also helps you to find a partner quicker in case many others in the market have similar attributes as you, which means that the market for “your type of people” becomes “liquid” (this is a recurring theme in my book).

However, in case you are either not easily describable by commonly used variables, or in case there are few others like you in the market, exchanges are likely to work less well for you. Either of these conditions makes you “illiquid”, and it is not a great idea to list an illiquid asset on an exchange.

When you list an illiquid asset on an exchange, unless you are extremely lucky, it is likely to sit there for a long time without being traded (think about “bespoke exchanges” like eBay here, where commodification is not necessary). The longer the asset sits on an exchange, the greater the likelihood that people who come across the asset on the exchange think that “something is wrong with it”.

So if you’re listing it on an exchange, its value will decay exponentially, and unless you are able to trade soon after you have listed it, you are unlikely to get much value for it.

In that sense, if you are “illiquid” for whatever reason (can’t be easily described, or belong to a type that few others in the market belong to), exchanges are not for you. And if you think about each of the characters in Indian Matchmaking who come to Sima aunty, they are illiquid in one way or another.

  • Aparna has entered the market at 34, and few other women of her age are in the market. Hence illiquid.
  • Nadia belongs to a small ethnicity, Indian-Guyanese-American, which makes her illiquid.
  • Pradhyuman has quirky interests (jewelry and fashion), which his parents are trying to suppress as they pass him off a liquid “rich Maadu boy”. Quirky interests mean he’s not easily describable. Hence illiquid.
  • Vyasar, by Indian-American standards, doesn’t have a great job. So not too many others like him. Illiquid, even before you take his family situation into account.
  • Ankita is professionally ambitious. Few of those women in the Indian arranged marriage market. Illiquid.
  • Rupam is divorced with a child. Might be liquid by conventional American markets, but illiquid in an Indian context. And she is, rather inexplicably, going the Indian way despite being American.
  • Akshay is possibly the most liquid (characterless except for an overly-dominating mom), and maybe that’s why he’s shown getting engaged.

All of these people will be wasting themselves listing themselves on exchanges. And so they come to a matchmaker. Now, Sima Auntie is both a broker and a clearinghouse (refer to Chapter 3 of my book 😛). She helps find matches for people, but only matches within her own inventory (though she decided Ankita has no matches at all in her own inventory, so connected her with another broker-clearinghouse).

This makes it hard – first of all you have illiquid assets, and you are trying to fulfil them within limited inventory. This is why she is repeatedly showing saying that her candidates need to “compromise” (something that seems to have triggered a lot of viewers). By compromise, she is saying that these people are so illiquid that in case they need to get a deal in her little exchange, they need to be willing to accept an “illiquidity discount” in order to get a trade. 

Back to bonds, why is trading them on an exchange so difficult? Because each bond is so idiosyncratic. There is the issuer, the exact date of expiry and the coupon, and occasionally some weird derivatives tacked on. The likelihood that you might find someone quickly enough to take the other side of such a deal is minuscule, so if you were to list your bond on an exchange, its value would drop significantly (by being continuously listed) before you could find a counterparty.

Hence, people trade this uncertain discount to a certain discount, by trading their bonds with market makers (investment banks) who are willing to take the other side of the deal immediately.

Unfortunately, market making is not a viable strategy when it comes to relationship markets. So what do you do if you can either be not defined easily in a few parameters, or if there are few others like you in the arranged  marriage market? You basically go Over The Counter. Ditch the market and find someone for yourself, or ask people you know to set you up. Or hire a matrimonial advisor who will tell you what to do.

If this doesn’t convince you on why matchmakers are important, then may be you should read what my other half has to say. If she’s the better half or not, you figure.

More On Direct Listings

Regular long-time readers of this blog might know that I’m not a big fan of IPO pops (I’ve written about them at least four times so far: one, two, three and four). You can think of this as Number Five, though this is specifically about Direct Listings.

In case you don’t have patience to click through and read my posts, what is the big deal about direct listings? And what is the problem with traditional IPOs? To put it simply, companies looking to raise capital through IPOs are playing a one-time game (you only do an IPO once), while companies that are investing in them are playing a repeated game (they participate in pretty much every IPO that comes on the market – ok may be not WeWork).

This means that investment banks, which stand between the buyer and the seller in such cases, have an incentive to structure the deal to favour the (repeated) buyers, and they price the IPO conservatively. This means that when the company actually lists on the market, it usually does so at a price higher than the IPO price, resulting in a quick win for the IPO investors.

This is injurious for the original investors in the company (founders, VCs, employees) since they are “leaving money on the table”. A pop of 10-20% is considered fair game (a price for the uncertainty on how the market will react to the IPO), but when MakeMyTrip lists 60% higher, or Beyond Meat lists 160% up, it is a significant loss to the early shareholders.

Over the last few months (possibly after the Beyond Meat IPO), Silicon Valley has woken up to this problem of the IPO pop, and suggested that the middleman (equity capital markets divisions of investment banks) be disintermediated from the IPO process. And their vehicle of choice for disintermediation is the direct listing.

A direct listing is what it is. Rather than raising fresh capital from the market, the company picks an auspicious date and declares that on that date its stock will list on the exchanges. The opening auction in the exchange on that day sets what is effectively the IPO price, and the company is public just like that.

Spotify was among the first well-known companies in recent times to do a direct listing, when it went public in 2018. Earlier this year, Slack did a direct listing as well. Here is Benchmark Capital’s Bill Gurley (a venture capitalist) on the benefits of a direct listing.

Direct Listing is all well and good when a company doesn’t have to raise capital. The question is how do you go public while at the same time raising capital (which is what a traditional IPO does)? Slack and Spotify were able to do the direct listing because they didn’t want capital from the IPOs – they just wanted to offer liquidity to their investors.

The New York Stock Exchange thinks it can be done, and has proposed a product where companies can use the opening daily auction to price the new shares being offered. There are issues, of course, about things like supply of shares, lock-ups, price support and so on, but the NYSE thinks this can be done.

NYSE’s President Stacey Cunningham recently appeared on the a16z podcast (again run by a VC, notice!) and spoke eloquently about the benefits of direct listing.

The SEC (stock regulator in the US) isn’t very happy with the proposal, and rejected it. Traditional bankers are not happy with the NYSE’s proposal, either, and continue to find problems with it (my main source of this angst is Matt Levine, who is a former ECM Banker and who thus has solid reasons as to why ECM Bankers should exist). In any case, the NYSE has refiled its proposal.

So what is the deal with direct listings?

In a way, you can think about them as a way to simply disintermediate the market. The ECM Banker, after all, is a middleman who stands between the buyer (IPO investor) and seller (company raising capital), helping them come up with a smooth deal, for a fee. The process has been set for about 40 years now, and has become so stable that the sellers think it has become unfair to them. And so there is the backlash.

Until now, the sellers were all independent entities with their own set of investors, and so they were unable to coordinate and express their displeasure with the IPO process. The buyers, on the other hand, play the game repeatedly, and can thus coordinate among themselves and with the middlemen to give themselves a sweet deal.

The development in this decade is that the same set of VC investors invest in a large number of go-to-public companies, and so suddenly you have sellers who are present across deals, and that has changed the game in a sense. And so direct listings are on every tech or investing podcast.

Among the things I wrote in my book (which came out a bit over two years ago) is that one important role that middlemen play is to reduce uncertainty and volatility in the market.

One concern with direct listings is that there can be a wide variation in the valuations by different players in the market, and the opening auction is not an efficient enough process to resolves all these variations. The thing with the Spotify and Slack listings was that there was a broad consensus on the valuation of these companies (more in line with public company valuations), a set of investors who wanted to get in and a set of investors who wanted to get out. And so it all went smoothly.

But what do you do with something like WeWork? The problem with private market valuations is that with players like SoftBank, they can be well divorced from market realities. In WeWork’s case, the range of IPO valuations that came up differed by an order of magnitude. And that kind of difference is not usually reconcilable in one normal opening auction (imagine a bid of 8 billion and an ask of 69 billion, and other numbers somewhere in between) without massive volatility going forward. In that sense, the attempted traditional IPO did a good job of understanding demand and supply and just declaring “no deal”. “No deal” is usually not an option when you do a direct listing.

OK I’ve written a lot I know (this is already 2X the length of my usual blog posts), so what do I really think about IPOs? I think all this talk about direct listings will shift the market ever so slightly in favour of the sellers. Companies will follow a mixed strategy – well known companies (consumer brands, mostly) with stable valuations will go for direct listings. Less well known companies, or those with unstable valuations will go for IPOs.

And in the latter case, I predict that we will move closer to a Dutch auction (like what Google did) among the investors rather than the manual allocation process that ECM bankers indulge in nowadays. It will have the benefit of large blocks being traded at time zero, at a price considered fair by everyone, and hopefully low volatility.

Housing

The Bank of England’s Bank Underground blog has two excellent posts on house prices (first this one, then this one). The basic idea is that houses are assets, not goods, since the “goods” consumed is “living”, which is basically a point in time thing.

As the first of these posts points out:

You can’t buy flowers when they are cheap and store them for months until Valentine’s day. Similarly, you can’t store housing services by, say, renting two flats this year and saving one’s rental services for next year. So the price of rents is determined “on the spot” by the current balance of demand and supply of places to live. Add a load of extra people and/or make them richer and the higher demand pushes up rents. Boost supply and rents fall.

Combined with this comes the news that a friend’s parents have moved to Mysore (from Bangalore) for their retirement.

Taking these blogposts, and this piece of news, together, I’m beginning to reconsider my views on housing.

About 7-8 years back, I got “personal finance advice” that one needs to start “saving for retirement” at age 30, and one of the best ways of doing that is to buy a house. I was about to turn 30 around then, and I took this advice seriously enough to invest in an apartment in 2014. Looking at it five years on, I’m not sure buying a house for retirement in your thirties is the best idea.

For starters, India is (still) a fast-growing and fast-changing nation, so I have no clue what are going to be good places to live 10 years down the line (forget 30 or 40, at which point I’ll retire).

Secondly, my needs from a house now are very different from what they will be 30 or 40 years down the line. For example, right now, my daughter’s school is a “fixed point” (assuming I don’t want to change that), and I need a house that isn’t too far from there. As she grows up and grows out of school, this will cease to be a factor.

Similarly, the work that I do demands a certain pattern of travel in the city, and that again guides my choice of place to live. This is likely to change as the years go by as well.

Then, what I need from my house and my surroundings are likely to change as well. For example, I might want peace and quiet right now, and might be willing to take my car everywhere. At some other point in time, I might place a higher premium on shops in a walkable distance. Similarly, my preferences on entertainment activities might change as well.

Taking all this into account, making a housing decision now on where I want to live 15-20 years down the line is futile. There are simply too many variables and any decision I take now will only lock me in to something that is possibly not optimal.

From that point of view I need to look at my needs over the next 10-15 years (when things will change, but maybe not by that much) to make my current investing decisions. This includes rent/buy/sell decisions, taking into account whatever I’m optimising for now, and will in the next few years. And if I’m setting aside money to “buy a house for retirement” now, I should simply just focus on saving and growing that money so that I can make an informed decision at a time when it matters, and matters are more clear.

Monetising the side bets

If you were to read Matt Levine’s excellent newsletter regularly, you might hypothesize that the market for Credit Default Swaps (CDS) is dying. Every other day, we see news of either engineered defaults (companies being asked to default by CDS holders in exchange for cheap loans in the next round), transfer of liability from one legal entity to another (parent to subsidiary or vice versa), “orphaning” of CDSs (where on group company pays off debt belonging to another) and so on.

So what was once a mostly straightforward instrument (I pay you a regular stream of money, and you pay me a lumpsum if the specified company defaults) has now become an overly legal product. From what seemed like a clever way to hedge out the default risk of a loan (or a basket of loans), CDSs have become an over-lawyered product of careful clauses and letters and spirits, where traders try to manipulate the market they are betting on (if stuff like orphaning or engineered default were to happen in sports, punters would get arrested for match-fixing).

One way to think of it is that it was a product that got too clever, and now people are figuring out a way to set that right and the market will soon disappear. If you were to follow this view, you would thin that ordinary credit traders (well, most credit traders work for large banks or hedge funds, so not sure this category exists) will stop trading CDSs and the market will die.

Another way to think about it is that these over-legalistic implications of CDSs are a way by the issuer of the debt to make money off all the side bets that happen on that debt. You can think about this in terms of horse racing.

Horse breeding is largely funded by revenues from bets. Every time there is a race, there is heavy betting (this is legal in most countries), and a part of the “rent” that the house collects from these bets is shared with the owners of the horses (in the form of prizes and participation fees). And this revenue stream (from side bets on which horse is better, essentially) completely funds horse rearing.

CDSs were a product invented to help holders of debt to transfer credit risk to other players who could hedge the risk better (by diversifying the risk, owning opposite exposures, etc.). However, over time they got so popular that on several debt instruments, the amount of CDSs outstanding is a large multiple of the total value of the debt itself.

This is a problem as we saw during the 2008 financial crisis, as this rapidly amplified the impacts of mortgage defaults. Moreover, the market in CDSs has no impact whatsoever on the companies that issued the debt  – they can see what the market thinks of their creditworthiness but have no way to profit from these side bets.

And that is where engineered defaults come in – they present a way for debt issuers to actually profit from all the side bets. By striking a deal with CDS owners, they are able to transfer some of the benefits of their own defaults to cheaper rates in the next round of funding. Even orphaning of debt and transferring between group companies are done in consultation with CDS holders – people the company ordinarily should have nothing to do with.

The market for CDS is very different from ordinary sports betting markets – there are no “unsophisticated players”, so it is unclear if anyone can be punished for match fixing. The best way to look at all the turmoil in the CDS market can thus be looked at in the same way as horse rearing – an activity being funded by “side bets”.