Pertinent observations on liquidity in startup markets

“Liquidity” was one of those words Wall Street people threw around when they wanted the conversation to end, and for brains to go dead, and for all questioning to cease

– Michael Lewis in Flash Boys

The quote that begins this blog post is also the quote that begins my book, which was released exactly a year ago. Despite its utility in everyday markets and economics, the concept of liquidity has not been explored too much outside of financial markets. In fact, one reason I wrote my book was that it appeared as if there was a gap in the market for material using the concept of liquidity to analyse everyday markets.

From this perspective, I was pleasantly surprised to come across a bunch of blog posts written by investors and tech analysts and startup fellows about the concept of “liquidity”. Most of these posts I came across by way of this excellent blog post by Andrew Chen of Andreessen Horowitz. It is always good to see others analysing topics in the same way as you are, so I thought I’ll share some insights from these posts here – some quotes, some pertinent observations. This is best done in bullet points. If you want to know more, I urge you to click through and read the blog posts in full. They’re all excellent.

  • You wonder why some startups make a big deal of how many cities they are in. This is because they usually function as within-city marketplaces, and so they need to be launched one city at a time. Uber famously started operations in San Francisco and remained there for a while.
  • “The best way to measure liquidity in the marketplace is to track the % of items or services that get sold/booked, and within what period of time. The higher the % and shorter period of time, the more sellers are making money and buyers are becoming loyal customers” – from here
  • “Where absolute pricing management makes most sense (i.e., where the marketplace operator sets prices) is where there isn’t a proper barometer for what the supply side should be charging and when the software can leverage systems should to optimize for liquidity” – from this excellent post
  • “In a zero sum game there, it’s most likely the marketplace with the most demand wins”. This was in the context of delivery marketplaces, and why Uber was likely to win that game (though it’s not clear if they’ve “won” it yet)
  • Trust is critical in building marketplaces. Both sides of the market need to trust the intermediary, and this can make marketplaces fragile. I had a recent incident where I appreciated the value of AirBnB landlord insurance (a lamp at a property I stayed at broke just after my stay, and the landlord wanted compensation). This post talks about how this insurance was critical to AirBnB’s growth
  • The same post talks about why even early stage businesses often make acquisitions – usually earlier stage businesses. “Marketplaces are normally winner-take-all markets. If we had lost ground to European competitors in 2012, we may have never gotten it back”
  • Ratings are a critical measure to build trust in a marketplace. And two-way ratings can help establish trust on both sides of the market
  • During the book launch function last year, there was a question on how marketplaces should build liquidity. I had given an example of the Practo/OpenTable model where you first sell a standalone service to one side of the market and then develop a marketplace. Another method (something I helped put in place for one of my current clients) is for the marketplace itself to become a “proprietary supplier”. The third, as this blog post describes, is about building markets where buyers are also sellers and the other way round (classic financial markets, for example).

For more on liquidity, and how it affects just about every market that you participate in on a daily basis, read my book!

We’ll miss sushi

One food item that my daughter and I will really miss when we move back to India is sushi. It is not that it is not available in Bangalore – restaurants such as Matsuri and Harima make excellent quality sushi, just that the transaction cost of procuring it will be far higher.

I grew up vegetarian, and didn’t eat meat until I was twenty eight. The decision to try meat was ad hoc – at a restaurant in Monastiraki square in Athens, the meat looked fantastic and the vegetables looked sad. And I decided that if I were losing my religion, I would lose it all the way and started my meat-eating career by eating beef souvlaki.

It wasn’t until a year later that I tasted fish, though – from childhood the smell of fish had put me off. As it happened, I first ate fish at a restaurant in Karwar, en route to Goa. Then, a consulting project in Mumbai happened, with a fish-loving client who took me to the best fish restaurants in that city (sometime during this time, I discovered I’m allergic to prawns).

It would take another year or two before I would have raw fish, though, in the form of sushi and sashimi. The first time was a trip to Matsuri, where my wife was treating me. I quickly grew fond of it, and would have a Japanese meal (at either Harima or Matsuri) at least once in six months (these are easily the best and most authentic Japanese restaurants in Bangalore. Edo is good but overpriced).

My love for sushi really took off during the three months I spent in Barcelona in 2016. That city has loads of sushi shops (it helped we were living in a dense district), mostly run by Korean immigrants. it is not too expensive either, which meant I would have it once a week at least (I might have eaten more often, but the wife was pregnant then, and hence off raw fish).

London doesn’t have the same density of sushi shops as Barcelona, but there are some chains that make pretty good sushi (Wasabi and Itsu, though I prefer the latter). Like other things London, it is not cheap, but we end up eating it reasonably often (it helps that the daughter loves sushi as well, though she only eats salmon nigiri – which also happens to be my favourite kind of sushi).

While craving sushi and planning a sushi run for dinner earlier this evening (finally we ended up eating at a Korean restaurant), it hit me that I won’t be able to have sushi so regularly in Bangalore. I started wondering what it would take for the likes of Freshmenu to be offering sushi on their menu. And I remembered a chapter in my book on specialty food.

The problem with low demand products is that the volatility of demand is high relative to the average demand. This means that for a retailer to stock items with low demand, either the margin needs to be high, or the inventory levels will be so low that customers might be disappointed rather often – neither of which is sustainable.

Making matters worse is the fact that fresh fish is an integral part of sushi, and it has an incredibly short shelf life. So unless demand can be aggregated to a high level (which Harima and Matsuri do, by being located in the middle of town and especially catering to the Japanese population in the city. In fact, I’m told the Chancery (where Matsuri is located) is the hotel of choice for Japanese visitors to Bangalore), it is not feasible to run a sushi restaurant in Bangalore.

Oh, and in the same chapter in the book, I discuss why people like to live with other people like themselves – others demanding the same thing you demand is the only way you can ensure that there is supply to meet your demand.

Information Technology and Large Cities

In my book Between the buyer and the seller, officially released exactly a year ago, I have a chapter on cities. In that I explain why industry clusters form, and certain cities or regions become hubs for certain types of industries.

In that, I spoke about the software industry in California’s Silicon Valley, and in Bangalore. I also mentioned how the Industrial Revolution wasn’t evenly distributed around England, and how it was clustered around textile hubs such as Birmingham and Manchester. I also used that chapter to talk about the problem with government-mandated special economic zones (this podcast with Amit Varma can help you understand the last point).

Back when Silicon Valley was still silicon valley (basically a semiconductor and hardware hub), it wasn’t as concentrated a hub as it is today. It was still fairly common for semiconductor companies to base themselves away from the valley. With the “new silicon valley” and the tech startup scene, though, there is no escaping the valley. It is almost an unwritten rule in US Tech startup circles that if you want to be successful with a tech startup, you better be in the valley.

And this is for good reason, as I explain in the book – Silicon Valley is where the ecosystem for successfully running a tech startup already exists, including access to skilled employees, subcontractors and investors, not to speak of a captive market. This, however, has meant that Silicon Valley is now overcrowded in many respects, with rents being sky high (reflected in high salaries), freeways jammed and other infrastructure under stress.

In fact, it is not just the silicon valley that has got crushed under the weight of being a tech hub – other “secondary hubs” such as Seattle (which also have a few tech majors, and where startups put off by the cost of the valley set up) are seeing their quality of life go down. The traffic and infrastructure woes in Bangalore are also rather similar.

So why is it that information technology has led to hubs that are much larger than historical hubs (based on other industries)? The simple answer lies in investment, or the lack of it.

Setting up an information technology company is “cheap” in terms of the investment in capital expenditure. No land needs to be bought, no plants need to be constructed and no machinery needs to be bought. All one needs is an office space (for which rent is paid monthly), and a set of employees (who again get paid a monthly salary). Even IT infrastructure (such as computing power and storage and communication) can be leased, and paid for periodically.

This implies that there is nothing that stops a startup company from locating itself in one of the existing hubs. This way, the company can avail all the benefits of being in the hub (supplier and customer infrastructure, employee pool, quality of life for employees and investors) without a high upfront cost.

Contrast this to “hard” industries that require manufacturing, where the benefits of being located in hubs is similar but the costs are far higher. As a hub develops, land gets expensive, which puts off further investors from locating themselves in the hub. This puts a natural limit on the size of the hubs, and if you think about it, large cities from earlier era were all “multi-purpose cities”, serving as hubs for several unrelated industries.

With information technology, though, the only impediment to the growth of a hub is the decreasing quality of life, information regarding which gets transmitted in indirect means such as higher rentals and commute times, and poor health. This indirect transmission of costs to investors results in friction, which means information technology hubs will grow larger before they stop growing. And as they go through this process, the quality of life of the hub’s residents suffers!

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!

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!

People are worried about investment banker liquidity 

This was told to me by an investment banker I met a few days back, who obviously doesn’t want to be named. But like Matt Levine writes about people being worried about bond market liquidity, there is also a similar worry about the liquidity of the market for investment bankers as well. 

And once again it has to do with regulations introduced in the aftermath of the 2008 global financial crisis. It has to do with the European requirement that bankers’ bonuses are not all paid immediately, and that they be deferred and amortised over a few years. 

While good in spirit what the regulation has led to is that bankers don’t look to move banks any more. This is because each successful (and thus well paid) banker has a stock of deferred compensation that will be lost in case of a job change. 

This means that any bank looking to hire one such banker will have to compensate for all the deferred compensation in terms of a really fat joining bonus. And banks are seldom willing to pay such a high price. 

And so the rather vibrant and liquid market for investment bankers in Europe has suddenly gone quiet. Interbank moves are few and far in between – with the deferred compensation meaning that banks look to hire internally instead. 

And lesser bankers moving out has had an effect on the number of openings for banker jobs. Which has led to even fewer bankers looking to move. Basically it’s a vicious cycle of falling liquidity! 

Which is not good news for someone like me who’s just moved into London and looking for a banking job!

PS: speaking of liquidity I have a book on market design and liquidity coming out next month or next next month. It’s in the publication process right now. More on that soon!