Category: finance

The Lingaraj Effect and Financial Regulation

Lingaraj was a driver who used to work for my father. He had a unique way of dealing with traffic jams on two-lane roads without a divider down the middle. He would instinctively swing the ambassador into the right lane – meant for traffic in the opposite direction (the jam ahead meant there was little traffic flow in that direction).

I remember both my father and I abusing him (Lingaraj) for this method which would only make the jam worse. However, he would persist. And we soon found that he wasn’t unique in his methods. It is the favoured method of most Bangalore drivers. Thus, whenever there is a minor jam somewhere, thousands of Lingarajs clog the “return lane” in all directions, and end up making it worse.

The funny thing about Lingaraj’s method was that it was “too big to fail”. Having switched to the right lane, we would progress much faster (till the site of the jam, of course) than our law-abiding brethren stuck in the left lane. There, someone who had taken responsibility of clearing the jam (not necessarily a cop) would realize that a necessary condition to clear the jam was to get our ambassador out of the right lane. And we would be given passage to shift to the left lane, and past the jam site, much ahead of those suckers who stuck to the law.

For drivers like Lingaraj, moving to the right lane in the wake of a jam is seen as “arbitrage”. And a necessary condition for it to be an arbitrage is that the offending vehicle is “too big to fail”, as I mentioned earlier. And given that in Bangalore, measures like traffic tickets sent by post aren’t that effective, this continues to be an arbitrage, and hence you still see so many drivers use this “method”.

While stuck in a traffic jam like that one last weekend (I was driving, and I consider myself socially responsible so stuck to the left lane), I realized how similar this was to the financial crisis of three years ago.

Traders noticed an “arbitrage” that didn’t really exist (namely, some AAA rated bonds traded at higher yields than other AAA rated bonds) and proceeded to trade on it. When they got into trouble the regulators realized that they had to be bailed out in order to clear the larger mess. The resemblance is uncanny.

So what should the regulators have done? Basically, drivers should’ve been prevented from getting to the right lane in the first place. Then there would have been no requirement to bail them out. In some places, this is done by installing road dividers, but in my experience I’ve seen that doesn’t help, too. People use whatever gaps are available in the divider to go to the right lane, and contribute to the jam.

The only option I can think of is some variation of postal tickets – having bailed out the drivers for going to the right lane, they need to be made to pay for it. Yeah, postal tickets (sending tickets by post for traffic violations) may not be effective, but that seems like the best we can do to regulate this problem. The upshot is that once we figure out how to solve this problem on the road, we can extend the solution to financial regulation, too!

Letting the rupee float

I’m midway through Shankar Acharya’s Op-Ed in today’s Business Standard, and I realize that along with the interest rate, the exchange rate (USD/INR) is another instrument that the RBI could possibly use in order to control money supply and the level of economic activity in India. Let me explain.

Given that mad growth in petroleum prices have been fundamental to growth in inflation, and that high petroleum prices also impact the oil marketing companies and the government negatively, and that we import most of our petroleum needs, letting the rupee rise above its current level is a mechanism of reining in “realized petroleum prices”. If we were to let the rupee rise, inflation would get tamed (due to imports becoming cheaper), the government’s fiscal deficit would come down (subsidy will be reduced), but exporters will get shoved, and that can depress economic activity in the country. So letting the rupee rise is similar to increasing interest rates.

There are people who question whether the RBI should be controlling exchange rates at all, and wonder if it would be better if it were to float freely. I’ve also taken that view on several occasions in the past, but now that I think of it, there are liquidity concerns. USD/INR, EUR/INR, GBP/INR, etc. have no way near the kind of liquidity that exchange rates between two “developed currencies” (USD/EUR or USD/JPY) have. In other words, the amount of trade that happens in USD/INR is much lower than that of say USD/JPY.

Given this lack of liquidity, if let to float fully, there is a danger that the USD/INR rates can fluctuate wildly. Higher volatility in rates means higher hedging costs for both exporters and importers, and given that our foreign trade is fairly high, a wildly fluctuating exchange rate does no good in policy formulation. From this point of view, it is important that short-term volatility in the exchange rates is curbed, and to that extent I support the RBI’s decision to intervene in the FX markets.

However, if there is a sustained pressure on either side  (say the exchange rate trades for a sustained period at the edge of the “band” that the RBI is allowing the rupee to float in), the RBI should buckle and shift their bands, and let the markets have their way. While short-term volatility is not great, distorting market signals is worse.

An analogy that comes to mind is circuit breakers in the Indian stock market. Earlier, these circuit breakers were in place for all stocks (basically, they dictate that if the stock price fluctuates by more than a certain amount in a certain time period, trading in the stock will be halted for a certain amount of time). However, recent regulations have removed these circuit breakers for stocks on which derivatives are traded, which are the more liquid stocks. The circuit breakers, however, are still in place for the less liquid stocks

It’s a similar story in the FX markets. Given that USD/INR is still not too liquid (in terms of volumes), it is important that we have circuit breakers (i.e. RBI intervention). Once it reaches a certain “critical mass” (in terms of volumes ), however, the RBI can step away and let the rupee float.

(I haven’t looked at any data while writing this. All judgments are based on my perception of how certain numbers shape up)

S&P’s Responsibilities

Reading through some of the reactions from “experts” to the S&P’s downgrade of US debt, I see words such as “irresponsible”, “misguided” and “inappropriate” being bandied around. These experts seem to be of the view that in view of all that the US is already going through (given the debt crisis et al) it was not correct for the S&P to push it further down into the abyss by downgrading its debt.

Now, the S&P is a rating agency. Its job is to rate debt, categorizing it in terms of how likely an issuer is to honour the debt it issues. It is a privately held firm and it is not the job of the S&P to prevent global crises and save the world. In this case, the S&P has just done its job. And having been following the crisis for a while I’m of the opinion that it’s done the right thing (check Felix Salmon’s article on this; he says the downgrade is more due to the risk of the US’s willingness to not default, rather than its ability; given that there is no permanent solution yet to the debt ceiling and it issues all debt in its native currency).

If a simple move like this by a private company is going to bring down the world, it is because of screwed up regulations (read Basel 2 and Basel 3) that ended up giving way too much importance to firms such as this. And I’m sure the US had adequate representation at that meeting in Basel where the accord was adopted, so it can be partially held responsible for the enormous power that rating agencies currently wield.

The bottom line is that excessive regulations based on dodgy parameters have been responsible for a lot of the mess that we see today. #thatzwhy we need strong regulations.

Ratings and Regulations

So the S&P has finally bitten the bullet and downgraded US federal debt to AA+ from its forever rating as AAA. While this signals that according to the S&P US Treasuries are no longer the least-risky investments, what surprises me is the reaction of the markets.

So far, since the rating change was announced after US market hours on Friday evening, only one stock exchange has traded – the one in Saudi Arabia, and that has lost about 5%. While it can be argued that it is an extension of severe drops in the markets elsewhere in the second half of last week, at least a part of the drop can be explained by the US debt downgrade. Now, when markets elsewhere open tomorrow after the weekend, we can expect a similar bloodbath, with the biggest drop to be expected in the US markets.

Now, the whole purpose of ratings was supposed to be a quick indicator to lenders about credit risk of lending to a particular entity, and help them with marking up their loan rates appropriately. It was basically outsourcing and centralization of the creditworthiness process, so that each lender need not do the whole due diligence himself. You can argue in favour of ratings as a logical extension of Division of Labour. If lending is akin to making shoes, you can think of rating agencies analogous to leather tanners, to save each shoe maker the job of tanning the leather himself.

However, over the course of time, there have been two consequences. The first was dealt with sufficiently during the global crisis of 2008. That it is the debt issuer who pays for the ratings. It clearly points out to an agency problem, especially when the “debt issuers” were dodgy SPVs set up to create CDOs. The second is about ratings being brought into the regulatory ambit. The biggest culprit, if I’ve done my homework right, in this regard was the much-acclaimed Basel II norms for capital requirements in banking, which tied up capital requirements to the ratings of the loans that the banks had given out. This had disastrous consequences with respect to the mortgage crisis, but I’ll not touch upon that here.

What this rating-based regulation has done is to take away the wisdom of crowds in pricing the debt issued by a particular issuer. Normally, the way stock and bond prices work is by way of wisdom of crowds, since they represent the aggregate information possessed by all market participants. Different participants have different assumptions, and at each instant (or tick), they all come together in the form of one “market clearing price”.

In the absence of ratings, the cost of debt would be decided by the markets, with (figuratively) each participant doing his own analysis on the issuer’s creditworthiness and then deciding upon an interest yield that he is willing to accept to lend out to this issuer. Now, however, with ratings linked to capital requirements, the equation completely changes. If the rating of the debt increases, for the same amount of capital, the cap on the amount the banker can lend to this particular issuer jumps. And that means he is willing to accept a lower yield on the debt itself (think about it in terms of leverage).

Whereas in the absence of ratings, the full information known to all market participants would go into the price of debt, the presence of ratings and their role in regulation prevents all this information flowing out to the market in terms of the price of debt. And thus the actual health of the issuer cannot be logically determined by its bond price alone – which is a measure that is continuously updated (every tick, as we say it). And that prevents free flow of information, which results in gross mispricing, and large losses when mistakes are discovered.

I don’t have anything against ratings per se. I think they are a good mechanism for a lay investor to get an estimate of  the credit risk of lending to a particular issuer. What has made ratings dangerous, though, is its link to banking regulation. The sooner that gets dismantled the better it is to prevent future crises.

Models

This is my first ever handwritten post. Wrote this using a Natraj 621 pencil in a notebook while involved in an otherwise painful activity for which I thankfully didn’t have to pay much attention to. I’m now typing it out verbatim from what I’d written. There might be inaccuracies because I have a lousy handwriting. I begin

People like models. People like models because it gives them a feeling of being in control. When you observe a completely random phenomenon, financial or otherwise, it causes a feeling of unease. You feel uncomfortable that there is something that is beyond the realm of your understanding, which is inherently uncontrollable. And so, in order to get a better handle of what is happening, you resort to a model.

The basic feature of models is that they need not be exact. They need not be precise. They are basically a broad representation of what is actually happening, in a form that is easily understood. As I explained above, the objective is to describe and understand something that we weren’t able to fundamentally comprehend.

All this is okay but the problem starts when we ignore the assumptions that were made while building the model, and instead treat the model as completely representative of the phenomenon it is supposed to represent. While this may allow us to build on these models using easily tractable and precise mathematics, what this leads to is that a lot of the information that went into the initial formulation is lost.

Mathematicians are known for their affinity towards precision and rigour. They like to have things precisely defined, and measurable. You are likely to find them going into a tizzy when faced with something “grey”, or something not precisely measurable. Faced with a problem, the first thing the mathematician will want to do is to define it precisely, and eliminate as much of the greyness as possible. What they ideally like is a model.

From the point of view of the mathematician, with his fondness for precision, it makes complete sense to assume that the model is precise and complete. This allows them to bringing all their beautiful math without dealing with ugly “greyness”. Actual phenomena are now irrelevant.The model reigns supreme.

Now you can imagine what happens when you put a bunch of mathematically minded people on this kind of a problem. And maybe even create an organization full of them. I guess it is not hard to guess what happens here – with a bunch of similar thinking people, their thinking becomes the orthodoxy. Their thinking becomes fact. Models reign supreme. The actual phenomenon becomes a four-letter word. And this kind of thinking gets propagated.

Soon the people fail to  see beyond the models. They refuse to accept that the phenomenon cannot obey their models. The model, they think, should drive the phenomenon, rather than the other way around. The tails wagging the dog, basically.

I’m not going into the specifics here, but this might give you an idea as to why the financial crisis happened. This might give you an insight into why obvious mistakes were made, even when the incentives were loaded in favour of the bankers getting it right. This might give you an insight as to why internal models in Moody’s even assumed that housing prices can never decrease.

I think there is a lot more that can be explained due to this love for models and ignorance of phenomena. I’ll leave them as an exercise to the reader.

Apart from commenting about the content of this post, I also want your feedback on how I write when I write with pencil-on-paper, rather than on a computer.

 


The Impact of Wall Street on Grad School

I don’t need to be an insider to tell you that Wall Street employs lots of PhDs. PhDs of various denominations, but mostly those with backgrounds in Math, Physics and Engineering are employed by various Wall Street firms by the thousand. I don’t think too many of them exactly work on the kind of stuff that they were doing in grad school, but certain general skills that they pick up and hone through their multiple years in grad school are found extremely useful by banks.

So while scores of older scientists and economists and policymakers lament the “loss” of so many bright minds to science, has anyone at all considered the reverse possibility? Of the impact that Wall Street has had on grad schools in the US?

One thing you need to face is that there are not a lot of academic jobs going around. The number of people finishing with PhDs each year is far more than the number of academic jobs that open up each year. I’m mostly talking about “assistant professor” kind of jobs here, and assuming that becoming a post-doc just delays your entry into the job market rather than removing you from the market altogether.

In certain fields such as engineering, there are plenty of jobs in the industry for PhDs who don’t get academic jobs, for whatever reason. Given this, it is “cheaper” to do a PhD in these subjects, since it is very likely that you will end up with a “good job”. Hence, there is more incentive to do a PhD in subjects like this, and universities usually never have a problem in finding suitable candidates for their PhD programs. However, there is no such cushion in the pure sciences (math/physics). There are few “industry employers” who take on the slack after all the academic positions have been filled up. And that is where Wall Street steps in.

The presence of Wall street jobs offers a good backstop to potential Math and Physics PhD candidates. If they aren’t able to do the research that they so cherish, they needn’t despair since there exists a career path which will enable them to make lots of money. And knowing the existence of this career option means more people will be willing to take the risk of doing a PhD in these subjects (since the worst case isn’t so bad now). Which in turn enhances the candidate pool available to grad schools.

So even if you were to believe that complex derivatives are financial “weapons of mass destruction”, there is reason for them to exist, to encourage the financial sector to pick up PhDs. For if PhDs were kept out of these jobs, it is real academic research in “real subjects” such as the pure sciences that will suffer. By picking up PhDs in large numbers, the financial sector is making its own little contribution to research in pure sciences.

Issuing in stages

I apologise for this morning’s post on IPOs. It was one of those posts I’d thought up in my head a long time ago, and got down to writing only today, because of which I wasn’t able to get the flow in writing.

So after I’d written that, I started thinking – so if IPO managers turn out to be devious/incompetent, like LinkedIn’s bankers have, how can a company really trust them to raise the amount of money they want? What is the guarantee that the banker will price the company at the appropriate price?

One way of doing that is to get the views of a larger section of people before the IPO price is set. How would you achieve that? By having a little IPO. Let me explain.

You want to raise money for expansion, or whatever, but you don’t need all the money now. However, you are also concerned about dilution of your stake, so would like to price the IPO appropriately. So why don’t you take advantage of the fact that you don’t need all the money now, and do it in stages?

You do a small IPO up front, with the sole purpose of getting listed on the country’s big exchanges. After that the discovery of the value of your company will fall into the hands of a larger set of people – all the stock market participants. And now that the market’s willingness to pay is established, you can do a follow on offer in due course of time, and raise the money you want.

However, I don’t know any company that has followed this route, so I don’t know if there’s any flaw with this plan. I know that if you do a small IPO you can’t get the big bankers to carry you, but knowing that some big bankers don’t really take care of you (for whatever reason) it’s not unreasonable to ditch them and go with smaller guys.

What do you think of this plan?

IPOs Revisited

I’ve commented earlier on this blog about investment bankers shafting companies that want to raise money from the market, by pricing the IPO too low. While a large share price appreciation on the day of listing might be “successful” from the point of view of the IPO investors, it’s anything but that from the point of view of the issuing companies.

The IPO pricing issue is in the news again now, with LinkedIn listing at close to 100% appreciation of its IPO price. The IPO was sold to investors at $45 a share, and within minutes of listing it was trading at close to $90. I haven’t really followed the trajectory of the stock after that, but assume it’s still closer to $90 than to $45.

Unlike in the Makemytrip case (maybe that got ignored since it’s an Indian company and not many commentators know about it), the LinkedIn IPO has got a lot of footage among both the mainstream media and the blogosphere. There have been views on both sides – that the i-banks shafted LinkedIn, and that this appreciation is only part of the price discovery mechanism, so it’s fair.

One of my favourite financial commentators Felix Salmon has written a rather large piece on this, in which he quotes some of the other prominent commentators also. After giving a summary of all the views, Salmon says that LinkedIn investors haven’t really lost out too much due to the way the IPO has been priced (I’ve reproduced a quote here but I’d encourage you to go read Salmon’s article in full):

But the fact is that if I own 1% of LinkedIn, and I just saw the company getting valued on the stock market at a valuation of $9 billion or so, then I’m just ecstatic that my stake is worth $90 million, and that I haven’t sold any shares below that level. The main interest that I have in an IPO like this is as a price-discovery mechanism, rather than as a cash-raising mechanism. As TED says, LinkedIn has no particular need for any cash at all, let alone $300 million; if it had an extra $200 million in the bank, earning some fraction of 1% per annum, that wouldn’t increase the value of my stake by any measurable amount, because it wouldn’t affect the share price at all.

Now, let us look at this in another way. Currently Salmon seems to be looking at it from the point of view of the client going up to the bank and saying “I want to sell 100,000 shares in my company. Sell it at the best price you can”. Intuitively, this is not how things are supposed to work. At least, if the client is sensible, he would rather go the bank and say “I want to raise 5 million dollars. Raise it by diluting my current shareholders by as little as possible”.

Now you can see why the existing shareholders can be shafted. Suppose I owned one share of LinkedIn, out of a total 100 shares outstanding. Suppose I wanted to raise 9000 rupees. The banker valued the current value at $4500, and thus priced the IPO at $45 a share, thus making me end up with 1/300 of the company.

However, in hindsight, we know that the broad market values the company at $90 a share, implying that before the IPO the company was worth $9000. If the banker had realized this, he would have sold only 100 fresh shares of the company, rather than 200. The balance sheet would have looked exactly the same as it does now, with the difference that I would have owned 1/200 of the company then, rather than 1/300 now!

1/200 and 1/300 seem like small numbers without much difference, but if you understand that the total value of LinkedIn is $9 billion (approx) and if you think about pre-IPO shareholders who held much larger stakes, you know who has been shafted.

I’m not passing a comment here on whether the bankers were devious or incompetent, but I guess in terms of clients wanting to give them future business, both are enough grounds for disqualification.

Cab guys’ tales

I travel to and from work in the company-provided cab. It’s a fairly convenient system, offering you flexible timings, and routings that aren’t too bad. The overhead in terms of time of traveling by cab is about 15-20 minutes for a 40-minute journey, so I take it on most days.

Given a choice, I try to sit next to the driver – maybe that’s the most comfortable seat in an Indica, and it definitely is the best seat in a Sumo. On most occasions, I chat with the driver as he drives me, but sometimes I don’t have the opportunity – since the driver is too busy chatting on his mobile phone. Yeah, company rules forbid that, but I guess no one really complains, so these guys get away with being on the phone a lot of the time.

Most of the time, the conversation is about loans, and repayment. Most of it is about informal loans that people have lent each other. The amounts these guys lend each other – seen as a percentage of their income (which I’m guessing based on what one cab guy told me last year) is humongous! They make loans to each other of the order of a few months’ salaries, and it seems like these loans are in perpetual transition – between the cabbies and their friends.

I hear them shout, strategise, pacify, ideate, about these issues. And sometimes after they’ve hung up I talk to them about this. One conversation comes to mind. So there was this cabbie whose family had lost a lot of money by “investing” it in a chit fund. It was an “informal” (i.e. unregistered fund), and in the previous “round”, his family had invested and made a good return. So in this “round”, more members of the family invested in the fund. And the fund manager decamped with the money!

I remember telling him that it was a bad strategy putting all their investments with the same guy, and tried to explain to him the benefits of diversification. He replied saying that he didn’t want to invest in the chit fund (the one he lost money in) but family members forced him to invest along with them, calling him a “traitor” when he tried to diversify!! Strange.

Back then, I didn’t know how exactly chit funds work else I would’ve also told him that it was an especially bad idea for people from the same family to invest in the same chit fund. If you think about how a chit fund works, you are basically betting on the desperation for money among the other “members” of the fund. You are betting that someone else in the pool needs money so badly that they’re willing to forego a higher “discount” which will then come into your kitty. So with members of the family all putting money in the same fund, they were just betting against each other! So even if the fund “manager” hadn’t decamped, it’s unlikely they would’ve got a particularly significant return on their investment.

 

Addition to the Model Makers Oath

Paul Wilmott and Emanuel Derman, in an article in Business Week a couple of years back (at the height of the financial crisis) came up with a model-makers oath. It goes:

• I will remember that I didn’t make the world and that it doesn’t satisfy my equations.

• Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.

• I will never sacrifice reality for elegance without explaining why I have done so. Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.

• I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension.

While I like this, and try to abide by it, I want to add another point to the oath:

As a quant, it is part of my responsibility that my fellow-quants don’t misuse quantitative models in finance and bring disrepute to my profession. It is my responsibility that I’ll put in my best efforts to be on the lookout for deviant behavour on the part of other quants, and try my best to ensure that they too adhere to these principles.

Go read the full article in the link above (by Wilmott and Derman). It’s a great read. And coming back to the additional point I’ve suggested here, I’m not sure I’ve drafted it concisely enough. Help in editing and making it more concise and precise is welcome.