Tag Archives: Finance

A New Measure of Financial Intermediary Constraints

Hui Chen teaches 15.433 Investments at MIT Sloan

The ability to measure the degree of financial intermediary constraint is of crucial importance for regulators and investors. Standard measures of intermediary constraint often focus directly on the riskiness of the financial institutions themselves, such as their level of credit risk, volatility, or leverage ratio. One such example is the TED spread, which is the difference between LIBOR, a short-term interest rate for uncollateralized interbank loans, and the yield for Treasury bills. Large TED spreads indicate that banks, and hence uncollateralized interbank lending, are risky, which is the case during the financial crisis of 2008-09 (see in the picture below). However, safe banks are not the same as unconstrained banks. In fact, a period of low TED spreads could be precisely because of the tight constraints that limit the banks’ ability to take on risky investment.

In a recent research paper with Professor Scott Joslin at the University of Southern California and Sophie Ni at the Hong Kong University of Science and Technology, we propose a different approach to measure the tightness of intermediary constraint by observing how financial intermediaries manage their tail risk exposures. Specifically, we focus on financial intermediaries’ trading activities in the market of deep out-of-the-money put options on the S&P 500 index.

Our measure is motivated by theory. I will sketch out the main ingredients of the model here. We consider a general equilibrium setting where two types of agents, public investors and financial intermediaries, have different beliefs about the chances of major market crashes. Such disagreements lead to trading in the crash insurance market, with the more optimistic financial intermediaries selling crash insurance to the public investors during normal times. The assumption of financial intermediaries being more optimistic about tail risks is a shortcut to capture their superior ability to manage tail risks, or agency problems such as government guarantees and compensation schemes that encourage financial institutions to take on tail risks.

As in practice, financial intermediaries in our model face risk constraints, which limit the amount of tail risks they can take on relative to their net worth. If the intermediary risk constraint starts to tighten, which could be due to higher levels of tail risks in the economy or trading losses that reduce the net worth, the financial intermediaries will effectively become more risk averse, and their ability to provide risk sharing with the public investors will be reduced. As a result, the amount of crash insurance sold by the financial intermediaries becomes lower and can even turn negative (as the financial intermediaries become net buyers of crash insurance). In addition, the tighter constraint and reduced risk sharing will also make crash insurance more expensive and lead public investors to demand a higher risk premium for the aggregate stock market.

The deep out-of-the-money put options on the S&P 500 index (DOTM SPX puts) are effectively insurances against major market crashes and are well suited to test our theory. The figure below plots the net amount of DOTM SPX puts that public investors acquire each month (henceforth referred to as PNBO). This also reflects the net amount of the same options that broker-dealers and market-makers (financial intermediaries) sell in that month. The net public purchase of DOTM index puts was positive for the majority of the months prior to the recent financial crisis in 2008, suggesting that the financial intermediaries (public investors) were mainly net sellers (buyers) of crash insurance. A few exceptions include the Asian financial crisis (December 1997), the Russian default, the financial crisis in Latin America (November 1998 to January 1999), and the Iraq War (April 2003). However, starting in 2007, PNBO became significantly more volatile. It turned negative during the quant crisis in August 2007, and then rose significantly and peaked in October 2008, following the bankruptcy of Lehman Brothers. Afterwards, PNBO plunged rapidly and turned significantly negative in the following months. Following a series of government actions, PNBO first bottomed in April 2009, rebounded briefly, and then dropped again in December 2009 as the European sovereign debt crisis escalated.We find that PNBO is negatively related to the expensiveness of the DOTM SPX puts relative to the at-the-money options. This result is the opposite of the prediction of the demand pressure theory for option pricing, whereby exogenous demand shocks push up both the amount of options public investors buy and the price of the options, thus inducing a positive correlation between the public demand for an option and its expensiveness. Instead, the result is consistent with time variation in the tightness of intermediary constraints driving the pricing of the options and the endogenous public demand simultaneously.

Moreover, we find that PNBO significantly predicts future market excess returns. During the period from 1991 to 2012, a one-standard deviation decrease in PNBO is associated with a 3.4% increase in the subsequent 3-month market excess return. The R-square of the return-forecasting regression is 17.4%. The return predictability of PNBO is, again, consistent with the prediction of a tightened intermediary constraint driving up aggregate market risk premium.

Two alternative explanations of our predictability results are: (1) PNBO is merely a proxy for standard macro or financial factors that drive the aggregate risk premium; (2) the predictability captures the direct impact of intermediaries’ constraints on the aggregate risk premium. Consistent with the second view, we find that the predictive power of PNBO is unaffected by the inclusion of a long list of return predictors in the literature, including price-earnings ratio, dividend yield, net payout yield, consumption-wealth ratio, variance risk premium, default spread, term spread, and various tail risk measures.

In addition, we also compare PNBO with a list of funding constraint measures (including the VIX index, the growth rate of broker-dealer leverage, and liquidity measures in the Treasury market). We find that financial intermediaries tend to reduce their supply of market crash insurances when these measures of funding constraints tighten. When regressing market excess returns on lagged PNBO and other funding constraint measures jointly, only the coefficient on PNBO remains significant, which suggests that PNBO contains unique information about the aggregate risk premium relative to the other measures of funding constraints.

Our study sheds new light on a specific channel, the crash insurance market, through which intermediary constraints affect aggregate risk sharing and asset prices. Our measure of financial intermediary constraint has several advantages compared to the existing measures. Compared to the accounting-based measures such as the leverage for financial institutions, our measure has the advantage of being forward-looking and available at higher (daily) frequency. Unlike price-based measures such as the TED spread, our measure moves the focus away from whether the financial institutions themselves are risky and instead onto whether they behave as constrained in the financial markets.

For details of this research, see Hui Chen, Scott Joslin, and Sophie Ni, “Demand for Crash Insurance, Intermediary Constraints, and Stock Return Predictability.”

Early Peek Advantage?

From 2007 to June 2013, a small group of fee-paying, high-speed traders received the bi-monthly results of the Michigan Index of Consumer Sentiment (ICS) from Thomson Reuters at 9:54:58, two seconds before the broader release at 9:55:00. This arrangement was initially reported on April 5, 2013 by Financial Times regarding a complaint by a former Thomson Reuters employee for his dismissal after telling US federal agent about this arrangement of tiered distribution of information. Wider media coverage followed in June and July as well as a review by the office of New York Attorney General (see, for example, “Thomson Reuters Gives Elite Traders Early Advantage” by CNBC and “Traders Pay for an Early Peek at Key Data” by Wall Street Journal on June 12, “Seconds Out” by Economists on July 13, 2013). In July 2013, Thomson Reuters decided to suspend the program.

Despite the negative “optics” projected by this practice of tiered information release, a series of questions were raised: To what extent does it give an advantage to those with early information? Does it hurt general investors and hence damage the integrity of the financial market? How does it affect the efficiency of the price discovery process in the market? More careful analysis is needed in order to answer these questions.

In a recent research paper with Professor Xing Hu at University of Hong Kong and Professor Jun Pan at MIT, we have examined in detail the price dynamics and trading activity in E-mini S&P 500 futures around ICS releases during this episode. We focus on S&P 500 futures because ICS, reflecting consumer opinions of the overall economy, is likely to move the entire market instead of individual stocks. Being highly liquid and unaffected by short-sale constraints, E-mini S&P 500 futures is an ideal instrument to trade on both positive and negative market-wide information.

During the period when Thomson Reuters offers early peek advantage, we find abnormally high trading activity in E-mini S&P 500 futures at 9:54:58 on ICS announcement days. On average, the trading volume jumps to 1,473 contracts per second at 9:54:58, well above the sample average of 124 contracts per second, which reflects the trading volume of general investors. One second later at 9:54:59, the abnormal volume drops to 261 contracts, still well above the sample average but sharply down from the trading volume at 9:54:58. The volume pattern makes two points: First, early peek by high-frequency traders does generate high volume of trading, but mostly among themselves. (There is no reason be believe that general investors will choose to trade more at the time when they have an information disadvantage.) Second, the first second at 9:54:58 is disproportionally more meaningful to them.

More detailed study of price dynamics after the early peek reveals a clearer picture: We find that the prices are fully adjusted to the ICS news after the first 10% of the trades during 9:54:58, which lasts about 14 to 16 milliseconds. There is no evidence of further price drift after the initial price discovery. This implies that most of the transactions during 9:54:58 and all the transactions afterwards, including the public announcement at 9:55:00, are traded at the fully adjusted market prices. The scope of the early peek advantage is therefore narrowly contained and limited to high-speed traders trading amongst themselves. Outside of this narrow time window, general investors, as well as high-speed traders, trade at fully adjusted prices and are not disadvantaged by the early peek of a few.

The initiation and later suspension of the early peek program by Thomson Reuters also provides a natural experiment for us to examine how different mechanisms of information release might impact the speed of price discovery. Associated with the early peek program is highly concentrated trading amongst those fee-paying, high-speed traders over a span of two seconds. As a result of this intense and coordinated trading, we see a superfast price discovery in the order of 14 to 16 milliseconds. After the suspension of the early peek program, however, we do not see the same level of trading intensity and we find that the price discovery takes much longer. From this perspective, one might argue that, as a mechanism of information release, the tiered program provides a venue to facilitate concentrated and coordinated trading among informed high-speed traders and therefore makes price discovery more efficient.

How information actually transmits and impounds into market prices remain a central question in our understanding of how the financial market functions. Empirical investigations aimed at tackling this question are always hindered by the fact that most information is private in nature and hence unobservable to researchers, even ex post. The multi-tiered process adapted by data vendors in feeding market-moving information to their different clients, as in the case of Thomson Reuters when releasing CSI data, offers a rare instance where we know precisely what information is transmitted, when and to what subset of market participants. This situation allows us to examine with more clarity how information, private to some traders, drives their trading behavior and influences the market. It may also help us to better design and regulate the information dissemination process in the market.

For details of this research, see Grace Xing Hu, Jun Pan and Jiang Wang, “Early Peek Advantage?”

Is Bitcoin a viable currency?

The media and blogosphere have been full of Bitcoin discussions recently and almost everyone has an opinion, but most of these opinions are tied to the technology of Bitcoin, that is, whether this new currency represents a major technological revolution in money.  So, most commentary has focused on questions about Bitcoin’s technological advantages: Is it really secure?  Is it truly anonymous?  Can it be counterfeited?  Are transaction costs actually lower?   Here, here and here are a few of examples and they contain comments like “Bitcoin is the first practical solution to a longstanding problem in computer science called the Byzantine Generals Problem.”  That is, they focus on the technology of Bitcoin.

But what of the finance and economics of Bitcoin?  Does it have the economic properties to be a viable currency?  I don’t think so.

Good money had three economic properties and uses.  It is a unit of account, used to measure and write contracts for things like income, wealth, and prices of goods.  It is a means of payment, used to avoid barter.  And it is a store of value, held to be able to make transactions in the future.  Of these three properties the third is the most important.  Unless money has a stable value, it does not serve the purposes that it should.  People will be wary of accepting something that might lose lots of value, and something with a volatile price makes a bad unit of account.

And my argument is not just that Bitcoin has had wild fluctuations in value that undermine its role as a viable currency, but deeper, that Bitcoin is destined to have wild fluctuations – it is poorly designed and conceived and so is likely to fail as a currency.  Why?

First, and primarily, Bitcoin lacks a mechanism for setting the supply of Bitcoin equal to the demand for Bitcoin to maintain its value.  History is replete with examples of governments that tied their hands in the supply of their currencies, much like Bitcoin has done.  What happens?  The value of the currency fluctuates.  Often a lot.  Before the founding of the Fed in the US, the dollar was backed by gold, and gold discoveries lead to inflations, and collapses in the price of gold to recessions and even financial crises.  Since the end of the Great Depression in the US, the Fed has actively managed the money supply to achieve price stability (at some times better than others).

Consider the example of the Y2K scare.  Before January 1, 2000, people were concerned that the change from the year 1999 to the year 2000 could lead to serious errors in computer systems, and in particular that it might become hard to use credit cards or get money out of a bank (or worse, bank deposits might even get lost).  As a result, people withdrew cash before New Year’s, lots of it. (These types of cautionary actions were widespread: governments grounded all airline flights overnight.).  These withdrawals were increased demand for cash that might have driven up the price of dollars – ie. led to deflation and changed interest rates.  But the large increase in the demand for cash did not cause any such real economic effects.  Why?  Because when demand increased the Fed simply expanded the amount of currency in circulation.  When New Year’s came and went without serious incident, people re-deposited their cash and the Fed reduced the money supply. The US price level remained stable.

Similar examples abound.  Prior to the founding of the Fed, the seasonal agricultural cycle lead to big seasonal swings in the demand for credit and currency which lead to seasonal swings in nominal interest rates (that is, the usual interest rate we think of which is the real interest rates plus changes in the value of money, that is, plus inflation).  If Bitcoin gains traction, will it have a seasonal fluctuations in its value that track the seasonal spending patterns of the world.  Will Bitcoins be more valuable in early December and comparably cheap in January?

Every day, central banks supply their currencies in proportion to the needs of the users of their currencies, so as to maintain a stable value for their currencies.  Bitcoin does not have a central bank.  It has a relatively inflexible supply mechanism (known as Bitcoin mining).  As a result, Bitcoin is destined not to have a stable value.  And a volatile price is bad for Bitcoin’s usefulness as a currency.  Central banks are an enormous competitive advantage for traditional currencies that the Bitcoin supply process completely lacks.

A second problem with maintaining a stable value is that digital currency is not really in limited supply. Its proponents will argue that it is.  The Bitcoin technology is carefully, maybe even brilliantly, designed to ensure that the supply grows slowly and it ultimately limited. But what happens when Bitcoin 2.0 comes out?  What if it has slightly better properties than the old technology?  Do people stop using Bitcoin 1.0 entirely leading it to become worthless?  Probably.  Is such a scenario likely?  Well,  think about the potential profits that one could make introducing Bitcoin 2.0, just by keeping a share of the initial number of coins.  These potential profits provide an incentive for the hi-tech business that comes up with a better Bitcoin to take over the digital currency market through advertising, lobbying, payments to businesses and so forth.  Or consider this alternative scenario.  Global banks start to provide currency transfers within their institutions but across borders that are as safe rapid, and low cost as Bitcoin payments.  There is no technological advantage to Bitcoin relative to a global bank with branches in many countries.  The point: while Bitcoin is in limited supply, digital currencies are not and neither are inexpensive ways to transfer money and make payments.

There are several other important cards stacked against Bitcoin.  But I will conclude with only one more., The “money supply” in the every country in the world is actually hard currency times the money multiplier – the ramping up of the hard currency into deposits in banks and lines of credit and gift cards and so forth.  In the US, the money supply – counting all of these money-like assets – is about twenty times the supply of hard currency.  And Bitcoin banking is developing and could go one of two ways.  First, it could be significantly private and unregulated.  The history of unregulated banking is that it is a disaster full of bank runs, volatile price levels currency collapses and so on.  The banking sector’s volatility becomes the volatility of the supply of Bitcoins which becomes price volatility.  Look just recently how the collapse of a single Bitcoin exchange affected the price of Bitcoins.  The second way Bitcoin banking could go would be as a regulated banking sector, becoming part of the tradition banking sector.  But then several claimed benefits of Bitcoin go out the window.  The true, large supply of Bitcoin is governed by banking regulation (but in every country in the world – what a mess!).  And while a Bitcoin is anonymous, a Bitcoin deposit is not anonymous. Once a bank gives you a credit for a Bitcoin and knows who you are, can it see in the Bitcoin chain how it was spent?  Not sure, but I would worry about it.

In sum, I am not worried about the technology – I have complete confidence that people at the other end of the MIT campus can solve almost all of the technological problems.  But the finance is suspect.  I am guessing that Bitcoin either remains small and volatile, with only transactions of suspect legality willing to accept the volatility as the price of true anonymity, or that Bitcoin goes down in history as a bubble, ultimately as worthless as the sequence of zeroes and ones that make up each coin.