Bond Market Liquidity and Selection Bias

I’ve long been a fan of Matt Levine’s excellent Money Stuff newsletter. I’ve mentioned this newsletter here several times in the past, and on one such occasion, I got a link back.

One of my favourite sections in Levine’s newsletter is called “people are worried about bond market liquidity”. One reason I got interested in it was that I was writing a book on Liquidity (speaking of which, there’s a formal launch function in Bangalore on the 15th). More importantly, it was rather entertainingly written, and informative as well.

I appreciated the section so much that I ended up calling one of the sections of one of the chapters of my book “people are worried about bond market liquidity”. 

In any case, the Levine has outdone himself several times over in his latest instalment of worries about bond market liquidity. This one is from Friday’s newsletter. I strongly encourage you to read fully the section on people being worried about bond market liquidity.

To summarise, the basic idea is that while people are generally worried about bond market liquidity, a lot of studies about such liquidity by academics and regulators have concluded that bond market liquidity is just fine. This is based on the finding that the bid-ask spread (gap between prices at which a dealer is willing to buy or sell a security) still remains tight, and so liquidity is just fine.

But the problem is that, as Levine beautifully describes the idea, there is a strong case of selection bias. While the bid-ask spread has indeed narrowed, what this data point misses out is that many trades that could have otherwise happened are not happening, and so the data comes from a very biased sample.

Levine does a much better job of describing this than me, but there are two ways in which a banker can facilitate bond trading – by either taking possession of the bonds (in other words, being a “market maker” (PS: I have a chapter on this in my book) ), or by simply helping find a counterparty to the trade, thus acting like a broker (I have a chapter on brokers as well in my book).

A new paper by economists at the Federal Reserve Board confirms that the general finding that bond market liquidity is okay is affected by selection bias. The authors find that spreads are tighter (and sometimes negative) when bankers are playing the role of brokers than when they are playing the role of market makers.

In the very first chapter of my book (dealing with football transfer markets), I had mentioned that the bid-ask spread of a market is a good indicator of market liquidity. That the higher the bid-ask spread, the less liquid a market.

Later on in the book, I’d also mentioned that the money that an intermediary can make is again a function of how inherent the market is.

This story about bond market liquidity puts both these assertions into question. Bond markets see tight bid-ask spreads and bankers make little or no money (as the paper linked to above says, spreads are frequently negative). Based on my book, both of these should indicate that the market is quite liquid.

However, it turns out that both the bid-ask spread and fees made by intermediaries are biased estimates, since they don’t take into account the trades that were not done.

With bankers cutting down on market making activity (see Levine’s post or the paper for more details), there is many a time when a customer will not be able to trade at all since the bankers are unable to find them a counterparty (in the pre Volcker Rule days, bankers would’ve simply stepped in themselves and taken the other side of the trade). In such cases, the effective bid-ask spread is infinity, since the market has disappeared.

Technically this needs to be included while calculating the overall bid-ask spread. How this can actually be achieve is yet another question!

Ratings revisited

Sometimes I get a bit narcissistic, and check how my book is doing. I log on to the seller portal to see how many copies have been sold. I go to the Amazon page and see what are the other books that people who have bought my book are buying (on the US store it’s Ray Dalio’s Principles, as of now. On the UK and India stores, Sidin’s Bombay Fever is the beer to my book’s diapers).

And then I check if there are new reviews of my book. When friends write them, they notify me, so it’s easy to track. What I discover when I visit my Amazon page are the reviews written by people I don’t know. And so far, most of them have been good.

So today was one of those narcissistic days, and I was initially a bit disappointed to see a new four-star review. I started wondering what this person found wrong with my book. And then I read through the review and found it to be wholly positive.

A quick conversation with the wife followed, and she pointed out that this reviewer perhaps reserves five stars for the exceptional. And then my mind went back to this topic that I’d blogged about way back in 2015 – about rating systems.

The “4.8” score that Amazon gives as an average of all the ratings on my book so far is a rather crude measure – since one reviewer’s 4* rating might differ significantly from another reviewer’s.

For example, my “default rating” for a book might be 5/5, with 4/5 reserved for books I don’t like and 3/5 for atrocious books. On the other hand, you might use the “full scale” and use 3/5 as your average rating, giving 4 for books you really like and very rarely giving a 5.

By simply taking an arithmetic average of ratings, it is possible to overstate the quality of a product that has for whatever reason been rated mostly by people with high default ratings (such a correlation is plausible). Similarly a low average rating for a product might mask the fact that it was rated by people who inherently give low ratings.

As I argue in the penultimate chapter of my book (or maybe the chapter before that – it’s been a while since I finished it), one way that platforms foster transactions is by increasing information flow between the buyer and the seller (this is one thing I’ve gotten good at – plugging my book’s name in random sentences), and one way to do this is by sharing reviews and ratings.

From this perspective, for a platform’s judgment on a product or seller (usually it’s the seller, but for products such as AirBnb, information about buyers also matters) to be credible, it is important that they be aggregated in the right manner.

One way to do this is to use some kind of a Z-score (relative to other ratings that the rater has given) and then come up with a normalised rating. But then this needs to be readjusted for the quality of the other items that this rater has rated. So you can think of some kind of a Singular Value Decomposition you can perform on ratings to find out the “true value” of a product (ok this is an achievement – using a linear algebra reference given how badly I suck in the topic).

I mean – it need not be THAT complicated, but the basic point is that it is important that platforms aggregate ratings in the right manner in order to convey accurate information about counterparties.

Thaler and Uber and surge pricing

I’m writing about Uber after a really long time on this blog. Basically I’d gotten tired of writing about the company and its ideas, and once I wrote a chapter about dynamic pricing in cabs in my book, there was simply nothing more to say.

Now, the Nobel Prize to Richard Thaler and his comments sometime back about Uber’s surge pricing has given me reason to revisit this topic, though I’ll keep it short.

Basically Thaler makes the point that when businesses are greedy and seen to be gouging customers in times of high demand, they might lose future demand from the same customers. In his 2015 book Misbehaving (which I borrowed from the local library a few months ago but never got down to reading), he talks specifically about Uber, and about how price gouging isn’t a great idea.

This has been reported across both mainstream and social media over the last couple of days as if Thaler is completely against the concept of surge pricing itself. For example, in this piece about Thaler, Pramit Bhattacharya of Mint introduces the concept of surge pricing and says:

Thaler was an early critic of this model. In his 2015 book Misbehaving: The Making of Behavioral Economics, Thaler argues that temporary spikes in demand, “from blizzards to rock star deaths, are an especially bad time for any business to appear greedy”. He argues that to build long-term relationships with customers, firms must be seen as “fair” and not just efficient, and that this often involves giving up on short-term profits even if customers may be willing to pay more at that point to avail themselves of its product or service.

At first sight, it is puzzling that an economist would be against the principle of dynamic pricing, since it helps the marketplace allocate resources more effectively and more importantly, use price as an information mechanism to massively improve liquidity in the system. But Thaler’s views on the topic are more nuanced. To continue to quote from Pramit’s piece:

“I love Uber as a service,” writes Thaler. “But if I were their consultant, or a shareholder, I would suggest that they simply cap surges to something like a multiple of three times the usual fare. You might wonder where the number three came from. That is my vague impression of the range of prices that one normally sees for products such as hotel rooms and plane tickets that have prices dependent on supply and demand. Furthermore, these services sell out at the most popular times, meaning that the owners are intentionally setting the prices too low during the peak season.

Thaler is NOT suggesting that Uber not use dynamic pricing – the information and liquidity effects of that are too massive to compensate for occasionally pissing off passengers. What he suggests, however, is that the surge be CAPPED, perhaps at a multiple of three.

There is a point after which dynamic pricing ceases to serve any value in terms of information and liquidity, and its sole purpose is to ensure efficient allocation of resources at that particular instant in time. At such levels, though, the cost of pissing off customers is also rather high. And Thaler suggests that 3 is the multiple at which the benefits of allocation start getting weighed down by the costs of pissing off passengers.

This is exactly what I’ve been proposing in terms of cab regulation for a couple of years now, though I don’t think I’ve put it down in writing anywhere. That rather than banning these services from not using dynamic pricing at all, a second best solution for a regulator who wants to prevent “price gouging” is to have a fare cap, and to set the cap high enough that there is enough room for the marketplaces to manoeuvre and use price as a mechanism to exchange information and boost liquidity.

Also, the price cap should be set in a way that marketplaces have flexibility in how they will arrive at the final price as long as it is within the cap – regulators might say that the total fare may not exceed a certain multiple of the distance and time or whatever, but they should not dictate how the marketplace precisely arrives at the price – since calculation of transaction cost in taxi pricing has historically been a hard problem and one of the main ways in which marketplaces such as Uber bring efficiency is in solving this problem in an innovative manner using technology.

For more on this topic, listen to my podcast with Amit Varma about how taxi marketplaces such as Uber use surge pricing to improve liquidity.

For even more on the topic, read my book Between the buyer and the seller which has a long chapter dedicated to the topic,

The nature of the professional services firm

This is yet another rejected section from my soon-t0-be-published book Between the buyer and the seller


In 2006, having just graduated from business school, I started my career working for a leading management consulting firm. This firm had been one of the most sought after employers for students at my school, and the salary they offered to pay me was among the highest offers for India-based jobs in my school in my year of graduation.

The elation of being paid better than my peers didn’t last too long, though. In what was my second or third week at the firm, I was asked to help a partner prepare a “pitch deck” – a document trying to convince a potential client to hire my firm for a piece of work. A standard feature in any pitch deck is costing, and the cost sheet of the document I was working on told me that the rate my firm was planning to bill its client for my services was a healthy multiple of what I was being paid.

While I left the job a few months later (for reasons that had nothing to do with my pay), I would return to the management consulting industry in 2012. This time, however, I didn’t join a firm – I chose to freelance instead. Once again I had to prepare pitch decks to win businesses, and quote a professional fee as part of it. This time, though, the entire billing went straight to my personal top line, barring some odd administrative expenses.

The idea that firms exist in order to take advantage of saving in transaction costs was first proposed by Ronald Coase in what has come to be a seminal paper in 1937. In “The Nature of the Firm”, Coase writes:?

The main reason why it is profitable to establish a firm would seem to be that there is a cost of using the price mechanism. The most obvious cost of ‘organising’ production through the price mechanism is that of discovering what the relevant prices are.

In other words, if an employer and employee or two divisions of a firm were to negotiate each time the price of goods or services being exchanged, the cost of such negotiations (the transaction cost) would far outstrip the benefit of using the price mechanism in such a case. Coase’s paper goes on to develop a framework to explain why firms aren’t larger than they were. He says,

Naturally, a point must be reached where the costs of organising an extra transaction within the firm are equal to the costs involved in carrying out the transaction in the open market.

While Coase’s theories have since been widely studied and quoted, and apply to all kinds of firms, it is still worth asking the question as to why professional services firms such as the management consulting firm I used to work for are as ubiquitous as they are. It is also worth asking why such firms manage to charge from their clients fees that are far in excess of what they pay their own employees, thus making a fat spread.

The defining feature of professional services firms is that they are mostly formed by the coming together of a large number of employees all of whom do similar work for an external client. While sometimes some of these employees might work in teams, there is seldom any service in such firms (barring administrative tasks) that are delivered to someone within the firm – most services are delivered to an external client. Examples of such firms include law firms, accounting firms and management consulting firms such as the one I used to work for (it is tempting to include information technology services firms under this banner but they tend to work in larger teams implying a higher contribution from teamwork).

One of my main challenges as a freelance consultant is to manage my so-called “pipeline”. Given that I’m a lone consultant, there is a limit on the amount of work I can take on at any point in time, affecting my marketing. I have had to, on multiple occasions, respectfully decline assignments because I was already tied up delivering another assignment at the same point in time. On the other hand, there have been times (sometimes lasting months together) where I’ve had little billable work, resulting in low revenues for those times.

If I were to form a partnership or join a larger professional services firm (with other professionals similar to me), both my work and my cash flows would be structured quite differently. Given that the firm would have a reasonable number of professionals working together, it would be easier to manage the pipeline – the chances of all professionals being occupied at any point in time is low, and the incoming work could be assigned to one of the free professionals. The same process would also mean that gaps in workflow would be low – if my marketing is going bad, marketing of one of my busy colleagues might result in work I might end up doing.

What is more interesting is the way in which cash flows would change. I would no longer have to wait for the periods when I was doing billable work in order to get paid – my firm would instead pay me a regular salary. On the other hand, when I did win business and get paid, the proceeds would entirely go to my firm. The fees that my firm would charge its clients would be significantly higher than what the firm paid me, like it happened with my employer in 2006.

There would be multiple reasons for this discrepancy in fees, the most straightforward being administrative costs (though that is unlikely to account for too much of the fee gap). There would be a further discount on account of the firm paying me a regular salary while I only worked intermittently. That, too, would be insufficient to explain the difference. Most of the difference would be explained by the economic value that the firm would add by means of its structure.

The problem with being a freelance professional is that times when potential clients might demand your services need not coincide with the times when you are willing to provide such services. Looking at it another way, the amount of services you supply at any point in time might not match the amount of services demanded at that point in time, with deviations going either way (sometimes you might be willing to supply much more than what is demanded, and vice versa).

Freelance professionals have another problem finding clients – as individual professionals, it is hard for them to advertise and let all possible potential clients know about their existence and the kind of services they may provide. Potential clients have the same problem too – when they want a piece of work done by a freelance professional, it is hard for them to identify and contact all possible professionals who might be able and willing to carry out that piece of work. In other words, the market for services of freelance professionals is highly illiquid.

Professional services firms help solve this illiquidity problem through a series of measures. Firstly, they acquire the time of professionals by promising to pay them a regular income. Secondly, as a firm, they are able to advertise and market the services of these professionals to potential clients. When these potential clients respond in the affirmative, the professional services firms sell them the time of professionals that they had earlier acquired.

These activities suggest that professional services firms can be considered to be market makers in the market for professional services. Firstly, they satisfy the conditions for market making – they actually buy and take on to their books the time of the professionals they hire, giving them a virtual “inventory” which they try to sign on. Secondly, they match demand and supply that might occur at different points in time – recruitment of employees occurs asynchronously with the sale of business to clients. In other words, they take both sides of the market – buying employees’ time from employees and selling this employees’ time to clients! Apart from this, firms also use their marketing and promotional activities that their size affords them to attract both employees and clients, thus improving liquidity in the market.

And like good market makers, firms make their money on the spread between what clients pay them and what they pay their employees. Earlier on in this chapter, we had mentioned that market making is risky business thanks to its inventory led model. It is clear to see that professional services firms are also risky operations, given that it is possible that they may either not be able to find professionals to execute on contracts won from clients, or not be able to find enough clients to provide sufficient work for all their employees.

In other words, when a professional joins a professional services firm, the spread they are letting go of (between what clients of their firms pay the firms, and what professionals draw as salaries) can be largely explained in terms of market making fees. It is the same case for a client who has pays a firm much more than what could have been paid had the professional been engaged directly – the extra fees is for the market making services that the firm is providing.

From the point of view of a professional, joining a firm might result in lower average long-term income compared to being freelance, but that more than compensates for the non-monetary volatility of not being able to find business in an otherwise illiquid market. For a potential client of such services also, the premium paid to the firm is a monetisation of the risk of being unable to find a professional in an illiquid market.

You might wonder, then, as to why I continue to be a freelance professional rather than taking a discount for my risks and joining a firm. For the answer, we have to turn back to Coase – I consider the costs of transacting in the open market, including the risk and uncertainty of transactions, far lower than the cost of entering into a long-term transaction with a firm!

Old preface

So my book will be released on the 8th of September. You can pre-order here. In the next 10 days leading up to the book’s release I thought I’ll publish some bootleg stuff here. This is basically chapters or sections that were in one of the earlier drafts but didn’t make it to the final cut.

What this means, of course, is that in the eyes of me and my publishers, what I’ll be putting here is inferior to what has actually gone into the book. So this post (and the ones I’ll put in subsequent days) put a floor on the quality of my book.

We’ll start with what was supposed to be the preface of my book. This was written back in November 2014, when I had little clue of what would finally go into the book. But I sat down one chilly evening on the outskirts of Bangalore and wrote this off in one stretch. Pasting it here verbatim without editing.


Continue reading “Old preface”

Platform as a platform

This afternoon, as I was getting off the tube, I looked at the railway platform, and wondered how it compared to “platforms” as we now know in the context of “platform economics“. For those of you under a rock, platform economics talks about the economics of “platforms” that bring together two sides of a market to interact.

In that sense, Uber is a platform connecting drivers to passengers. Ebay is a platform connecting buyers and sellers of used goods. Paypal is a platform connecting people who want to pay and those who want to receive payment. And so forth (these are all textbook examples nowadays).

So is the railway platform a platform? And if not, is it correct that we refer to entities that run two-sided markets as platforms (arguably, the most intuitive meaning of the word “platform” in the last hundred or so years has been in the railway context)? These were some of the questions I grappled with as I walked along the length of the platform at Ealing Broadway.

For those of you who’re not in the know, I’ve written a book on market design. The Takshashila Institution is publishing it, and the book should be out fairly soon (manuscript is complete, but there’s still plenty to do). In that book, I have a chapter on taxi marketplaces such as Uber/Lyft/Ola, and how they’ve transformed the efficiency of the taxi market. Before I introduce these characters, though, I draw the history of the taxi market.

In that, I talk about taxi stands. Taxi stands work in the way of Thomas Schelling’s focal points. Passengers go there because they know empty taxis will go there. Taxi drivers looking for passengers go there because they know passengers looking for taxis will go there. This way, rather than waiting at a random place looking for either a passenger or a ride, going to the taxi stand is rational. And in that sense, taxi stands are a platforms.

In a way, railway platforms are platform in the same sense. Think of a train that wants to pick up passengers, and passengers who want to travel on a train. If there were no designated pick up points, trains would stop at random places, which passengers would have to guess. While engine drivers could see passengers waiting by the side, stopping at random places might have meant that the train would have had to go empty.

From this perspective, railway platforms act as platforms – they are focal points where trains and passengers come together. Passengers wait there because they know trains stop there, and vice versa. And helpfully, there is an actual physical platform that elevates passengers to the height of the train door so they can get on and off easily!

Isn’t this a wonderful way to have complicated a rather simple concept?

Upside down pricing in payment services

Some Indian banks charge for services that are cheap to execute, and offer for free expensive services 

Last week I enddd up spending some time waiting at a teller counter at a bank. This was due to some mess up with a cheque I had received. During my time at the teller counter I had the opportunity to observe other people at the same counter. 

There were a few people depositing cash into their business accounts. A few others were depositing cheques. What caught my attention, however, was this guy from a nearby business who came to deposit a large number of cheques. 

He had an entire book of challan leaves (banks regularly issue those to business customers), to each of which was stapled a cheque. As I watched, the teller would put a seal on a cheque, its corresponding challan and another seal on the counter foil. This process was repeated for each challan in the book. 

And this process was only to accept the cheques. Later on there would’ve been further effort on behalf of the bank to cash the cheque and actually execute the fund transfer. And then add in the effort of writing out all those cheques, writing out all those challans (they’re hard to print) and then take them to the bank. 

It was a rather laborious process all round, on behalf of all parties involved. Yet, banks mostly execute this function for free for most customers. 

On the other hand, they charge for account to account transfers, and the amount isn’t particularly small. Like this morning I was moving money from one account  to another, a process that took me a minute and that wouldn’t have cost the bank any human minutes. And icici bank decided to charge me for it. 

It seems like banks have their pricing and the valuation of their own effort all wrong. For electronic payments the cost is direct – what the banks have to pay the payments systems and any per use software costs. And this makes it easier to value and charge for such services. 

The effort in transacting through cheques, on the other hand, is not directly measurable (though by no means an impossible exercise). There are back offices that do the job whose cost is easy to measure, but several employees who also do other things spend time processing cheques. And this difficulty in measurement means that most banks just don’t charge for cheques. 

Around 2000 when foreign banks expanded their branch networks in india there was an attempt to charge customers for walking into the branch – customers were encouraged to do their business at ATMs or over the phone, instead. This was in recognition of the costs of customer walkins into branches.  

Banks would do well now to do something similar for cheques as well – despite the cheque truncation system (CTS), the effort involved in organising payments through cheques is massive for the bank. 

There is only one upside to cheques – and this is a downside for customers. Cheques result in money going into limbo. The payer doesn’t know when the funds will leave his account and can’t use the funds. The recipient can’t use it either until he has got it. So for the duration that the amount is “in transit” (and this duration can vary significantly) banks can happily use these funds without them being called. 

It’s possible that the benefit to the banks from this float more than compensates for the pain of processing cheques. If not, cheques have no business existing any more!