Donald L Kohn: Asset-pricing puzzles, credit risk, and credit derivatives
Remarks by Mr Donald L Kohn, Vice Chairman of the Board of Governors of the US Federal Reserve
System, at the Conference on Credit Risk and Credit Derivatives, Washington DC, 22 March 2007.
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Good afternoon. I am pleased to participate in the Board's conference on credit risk and credit
derivatives. Song Han, Matt Pritsker, and Hao Zhou have worked hard to put together a stimulating
program of cutting-edge research in this area.1 Your conference focuses on improving our
understanding of credit risk and credit derivatives, but I will begin my talk by taking a step back and
discussing a wider range of asset markets, in which our understanding is also limited. Then I will
examine how the research in this conference can help sharpen our focus on this broader range of
asset markets.
At the Federal Reserve, we have considerable interest in credit risk and credit derivatives. As these
markets develop and become more complete, they facilitate risk transfer and diversification, thereby
increasing the resilience of our financial system. With participants coming to rely more on these
markets to manage risk, we have focused increasingly on their liquidity and structure. We have worked
closely with the private sector to strengthen the clearing and settlement infrastructure and to
understand how these markets will function under stress.
But my emphasis today will be not the structure or mechanics of credit markets but rather the
information contained in the prices we observe in these markets. We at the Federal Reserve use this
information in nearly every area of our responsibility. For example, in our roles as bank supervisors
and protectors of financial stability, we monitor the credit spreads of financial institutions as early
warning signs of possible financial stress. In our role as monetary policy makers, we analyze
information from credit-risk markets to get readings on the cost of capital to businesses and on
forward-looking indicators of the health of the corporate sector that can have implications for future
macroeconomic developments.
Extracting information from asset prices
As a consequence, the staff at the Federal Reserve puts considerable effort into research on asset
prices and into reporting the results of that research to policymakers. One reason we do so is to try to
understand the expectations that households, businesses, and market participants have about the
future. Expectations are critical to understanding the economy and developments in the financial
system. Of course, we look at a great deal of data from the nonfinancial side of the economy, such as
gross domestic product (GDP) growth, the unemployment rate, and changes in the prices of goods
and services. These data certainly reflect expectations but not always in a transparent way. And, these
data take some time to compile and so are never available in real time.
Because financial asset prices embody expectations about the future, they also contain
forwardlooking information about prospective developments, and many are available continuously and
instantaneously. We pay attention to an extensive range of asset prices, including those of Treasury
securities (both nominal and real), corporate debt and equities, and derivatives. Although it is not easy,
we use these asset prices to tease out information about expectations that help us to interpret and
predict the pace of economic activity and prices.
The price of an asset reflects the future cash flows that investors expect to receive from owning that
asset. The price also reflects a risk premium, which is the excess expected return over the risk-free
rate that investors require for holding risky assets in their portfolios. Each asset's risk premium
depends on the asset's risk - as measured by the possible variability of its cash flows from their
expected level - and on investors' risk aversion, which represents the extent of investors' appetite for
risk. And we try to measure and understand the elements of the risk premium, in addition to the
embedded expectations.
In equity markets, corporate earnings are the future cash flows that affect equity prices. Given the
market's outlook for corporate earnings - as embodied, for example, in the predictions of market
analysts - we make a crude estimate of the risk premium on equities as the difference between the
ratio of trend earnings to price and a real long-term Treasury yield. On occasion, we go further and
use structural economic models to decompose the risk premium into components related to risk and to
investors' risk appetite.
In the credit market, the relevant future cash flows are the coupons on corporate debt, less an
allowance for expected losses from future defaults. In one exercise, we forecast future defaults with a
simple regression model and estimate the credit-risk premium as the difference between corporate
yields and Treasury yields that is in excess of what would be required to compensate investors for
their estimates of expected credit losses. We also estimate a term structure of credit-risk premiums by
repeating this analysis using debt that has different maturities. To judge what market prices of risk
might be telling us, we try to understand how the resulting credit-risk premiums relate to other sources
of information, such as the strength of business balance sheets, historical levels of risk premiums, and
premiums observed in related markets, like that for equities. This approach helps us to assess the
current attitudes and expectations of market participants as well as possible future movements in risk
premiums under alternative scenarios.
We look to prices in Treasury markets and in markets for interest rate options and futures to infer
investors' expected future path of monetary policy and their uncertainty about that path. To do so, we
need to model term premiums to tease out the links between long-term interest rates and investors'
expectations of future short-term rates. We also compare the Treasury yield curve with the prices on
Treasury inflation-protected securities to infer expected inflation, a key variable tracked by monetary
policy makers.
Although we use a variety of techniques for extracting information from asset prices, what we can
learn has limits. First, asset prices are tough to work with. They change rapidly and are subject to
short-run technical factors - swings in prices that are not related to fundamental and persistent shifts
in supply and demand. Second, and perhaps even more important, how asset prices embody risk and
investors' risk attitudes is complicated and varies over time. We must use models to extract
information on risk and risk preferences from prices, and because all models are simplifications of
reality, we have to recognize that the results are only approximations of the underlying attitudes and
circumstances and thus are subject to error.
Asset-pricing puzzles
Researchers are well aware of the difficulties of decomposing an asset's required return into
components that are related to expected future cash flows, risk aversion, and risk. Moreover, risk
preferences that should be related in a predictable way across markets often do not appear to be so.
For example, the risk preferences required to fit consumption data from the goods market are
inconsistent with the risk preferences implied by prices in the equity market.
This problem is well known to most economists and to everyone in this room and is known as the
"equity-premium puzzle." The equity premium is defined as the return that an investor expects to earn
on a broad equity index in excess of the return on a U.S. Treasury security. Although theory suggests
that the equity premium should be related to investors' risk preferences as well as the fundamental
volatility of the corporate sector, it is difficult to find plausible risk preferences that can rationalize the
high level of the historical equity premium. Also, we observe that required returns appear to vary over
time, but we do not understand all the reasons for the fluctuation. Both of these problems complicate
our interpretation of what implications, if any, movements in equity markets have for the
macroeconomy.
The equity-premium puzzle is not the only aspect of the behavior of financial asset prices that is
difficult to reconcile with economic theory or experience in related markets. A second puzzle is the
"credit-spread puzzle." The spread between a corporate bond and a similar-maturity Treasury bond
compensates an investor for the risk that the bond's issuer will default and recoveries on the defaulted
bond will be low. Credit-risk spreads vary substantially over the cycle, and right now they are on the
low side of historical experience. However, over long periods, actual percentage losses on corporate
bonds have been well below historical averages of credit spreads at all maturities, especially in the
high-grade, short-maturity segment of the market. Again, it is difficult to reconcile this observation with
standard models of investor preferences. Other explanatory factors, such as the different tax treatment
of corporate and Treasury bonds, appear to explain only part of the puzzle.
A third puzzle concerns the behavior of financial market volatility. Volatility and measures of expected
volatility derived from options prices vary over time but not in ways that are easy to link to economic
fundamentals or to the variation of expected returns in asset markets. Moreover, the relationship
between financial market volatility and the volatility of macroeconomic variables such as GDP is not
well understood.
A fourth puzzle related to the pricing of risk concerns the term premium, which is the additional
compensation that investors require to hold longer-term securities. We estimate from the Treasury
market that the term premium has declined substantially in recent years to unusually low levels, which
has contributed to the inversion of the yield curve. But we do not understand why, and consequently
we do not know to what extent we are seeing a permanent decline in the term premium - perhaps due
to a general reduction in the volatility of economic activity and inflation over the past twenty-five years.
Or we may be seeing a temporary decline due to the influence of recent macroeconomic conditions or
special factors affecting the demand for long-term bonds.
In addition to these well-known puzzles, are also a large number of puzzles across all asset markets
that I will group under the common theme of risk harmonization. Risk-harmonization puzzles concern
whether a given risk is priced the same way in all markets in which that risk is traded. In the absence
of transaction costs, broadly defined, the law of one price should hold - there should be no risk-free
arbitrage - and all risks should be priced the same way in all markets.
In fact, risk harmonization is limited because transaction costs, viewed in a broad way, are quite
material in many markets. A broad notion of transaction costs includes not only the direct fees paid
when transacting and trading but also the full set of risks that are involved when arbitraging among
markets. These include various types of basis risk, which is the risk that long and short positions
exposed to the same risk in different markets might not offset each other. Another important risk is
model risk, which is the risk of misjudging an apparent price anomaly when trading owing to not having
the correct model. Some of the conference papers focus on markets in which risk harmonization
appears to be incomplete.
How the common lens of credit risk improves our understanding
Papers in this conference contribute to our overall understanding of how credit risk, as well as other
risks such as those associated with volatility and liquidity, are priced in financial markets. One of the
contributions of the conference is that it views many of the asset-pricing puzzles through the common
lens of credit risk. This approach holds the hope of addressing the various puzzles in an internally
consistent way that helps us to understand how the puzzles may be related.
One strand of the literature on the equity-premium puzzle attempts to explain the puzzle with a
somewhat controversial refinement of standard risk preferences. The first paper in the conference
examines the plausibility of these preferences by analyzing whether they can also explain the average
pattern of credit spreads in the bond market. The results are mixed. Part of the credit-spread puzzle is
explained, lending some credence to these preferences, and suggesting the two puzzles are related,
but a part remains unexplained. And the paper identifies better modeling of the situation in which firms
are forced into default as one research direction that may help to explain the remaining part of the
credit-spread puzzle. This research direction is pursued in a separate paper in the conference.
A second paper at the conference also studies the relationship between equity prices and credit risk
but does so from a different perspective by asking whether credit risk is appropriately priced in the
stock markets. To address this question, it focuses on companies that are heavily exposed to
systematic risk of financial distress - that is, they are relatively likely to experience financial distress
during future downturns - and then studies whether the stocks earn a positive premium for this risk.
The main finding is that investors in those companies do not earn a premium for distress risk in the
stock market. This result suggests a possible failure of risk harmonization in the stock market, which in
turn raises the deeper question of identifying why this failure in risk harmonization is not arbitraged
away.
In short, papers in the conference deepen our knowledge of some of the asset-pricing puzzles, but
they also highlight new aspects of the puzzles that remain to be explained.
How credit derivatives markets can improve our understanding
This leads to my last topic, which is how credit derivatives markets provide new ways for us to uncover
market perceptions of risk. Like all derivatives (such as options and swaps), credit derivatives allow for
credit risk to be unbundled and traded independently from other types of risk, which makes it easier to
price and measure the different types of risk. Here I will focus on two examples.
The first involves our ability to infer the market's perception of default risk. In the bad old days, about
ten years ago, the best way to infer credit risk was from the prices of corporate bonds, but bond prices
are contaminated by differences in coupons, taxes, option-like features, bond covenants, and the
illiquidity of the corporate bond market itself. All of these features meant that the modeling error
involved in the process resulted in credit-risk measures that were noisy and potentially biased.
Now, instead of looking to the bond market to measure default risk, we are increasingly turning to the
market for credit default swaps, or CDS. CDS are more standardized than corporate bonds, and, over
time, they have also become more liquid. They therefore provide us with new, and in many cases
more precise, measures of credit risk. These measures in turn can sharpen our measures of the
pricing puzzles. In addition, because the CDS market helps us to strip out the credit-risk component
from bond prices, that market also gives us a clearer picture of how important non-credit-risk
components of bond prices, such as liquidity, are priced.
The second example involves the pricing of default correlation. Default correlation measures the
tendency of firms to default at the same time. Suppose a bank makes a set of loans that appear to be
safe when looked at individually. Whether the loans are likely to default at nearly the same time can
represent the difference between whether the bank remains healthy or has the potential to become
insolvent. For this reason, the modeling of default correlations, and how correlations change with
economic conditions, is one of the most important inputs into measures of portfolio credit risk at banks.
Default correlations and how they are modeled are also important to bank regulators and are heavily
emphasized within the Basel II capital standards.
Collateralized debt obligations, or CDOs, are one of a number of financial instruments whose prices
are sensitive to the pattern of default correlations. As a result, the prices of these instruments provide
us with a forward-looking picture of the market's perception of default correlations and an indication of
how the risks of changes in correlation are priced. Of course, as some of the papers in the conference
demonstrate, the pricing of correlation-sensitive instruments is, putting it generously, somewhat less
than straightforward. For that reason, there is substantial model risk involved in making inferences
from these prices. Nevertheless, the prices of these instruments provide a blurry view of default
correlations that I expect will improve through time as credit derivatives markets continue to grow and
mature.
Credit derivatives, like all derivatives, are in zero net supply, and, abstracting from the very important
issue of counterparty credit risk, they neither add to nor subtract from the stock of financial risk in the
economy. They do, however, provide new and more-efficient ways for sharing and hedging the risks
that do exist, and they facilitate the transfer of those risks to those who are most willing to evaluate
and bear them.
As a consequence, as the credit derivatives market continues to develop and deepen, my guess, and
it is just a guess, is that cleaner measures of credit risk will, all else being equal, reduce the costs of
arbitraging between markets and will improve the harmonization of risk across markets - one of the
asset-pricing puzzles I highlighted.
Two of the other puzzles I described earlier are the credit-spread and equity-premium puzzles. At least
a part of these puzzles may be due to imperfect risk sharing among active market participants. If this is
indeed part of the puzzle, then financial innovations such as credit derivatives may, again, all else
being equal, reduce long-run average risk premiums in both the equity and credit markets, over time,
by facilitating risk sharing among currently active market participants, provided that participants
adequately understand and manage the risk of these products. That said, time will tell whether my
speculations on this point are correct.
Conclusion
My message to you today has been that the Federal Reserve places a lot of emphasis on
understanding financial asset prices to help it meet its public policy objectives. But in doing so, we are
handicapped by the extent to which we do not understand important aspects of how financial assets
are priced. Your work as researchers in this field - a portion of which is show-cased at this conference
- has been helpful in beginning to explain some of the puzzles, and more recent techniques and ideas
together with the data series being generated in new markets hold the promise of more progress in the
future.
So, I will not keep you from your work any longer. Your contributions are important to the nation's
central bank. Please, go solve some puzzles.