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Remarks by Vice Chairman Donald L. Kohn
At the Conference on Credit Risk and Credit Derivatives, Washington, D.C.
March 22, 2007

Asset-Pricing Puzzles, Credit Risk, and Credit Derivatives

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 forward-looking 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.

Footnotes

1. Mike Gibson, Song Han, Matt Pritsker, and Hao Zhou, of the Board's staff, contributed to these remarks.

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프로야구 삼성, 12년 만에 한국시리즈 우승 *AI를 활용해 정리한 경기 내용입니다. 상단의 'AI MY 뉴스' 로그인을 통해 뉴스핌의 차세대 AI 콘텐츠 서비스를 활용해보기 바랍니다. [서울=뉴스핌] 유다연 기자=12년의 기다림이 끝났다. 삼성이 정규시즌 1위 KT 위즈를 꺾고 2014년 이후 12년 만에 한국시리즈(KS·7전 4선승제) 정상에 복귀했다. 삼성은 8일 대구삼성라이온즈파크에서 열린 KT와의 2026 KBO KS 5차전에서 12-1로 대승을 거뒀다. [서울=뉴스핌] 유다연 기자= 삼성 라이온즈가 8일 대구 삼성라이온즈파크에서 열린 2026 KBO 한국시리즈 5차전에서 12-1로 이겼다. 이날 우승으로 삼성은 12년 만에 KS 정상자리에 올랐다. 그래픽은 독자의 이해를 돕기 위해 삼성 선수들 사진과 함께 만든 AI그래픽. (명령어: 삼성 라이온즈 12년 만의 우승을 AI그래픽으로 제작해줘.)[사진=삼성 라이온즈][그래픽=챗 GPT] 2026.11.08 willowdy@newspim.com 지난 3일 수원에서 열린 1차전에서 7-8로 패했던 삼성은 2차전 연장 12회 혈투 끝에 승리하며 시리즈 균형을 맞췄다. 이후 안방에서 열린 3~5차전을 모두 쓸어 담으며 시리즈 전적 4승 1패로 우승을 확정했다. 이로써 삼성은 2002년, 2005년, 2006년, 2011~2014년에 이어 통산 8번째 KS 우승을 차지했다. 1985년 전·후기 통합우승까지 포함하면 구단 통산 9번째 우승이다. 특히 정규시즌 2위였던 삼성은 1위 KT를 제압하면서 2018년 SK(현 SSG) 이후 8년 만에 '업셋 우승'을 달성했다. 반면 KT는 2021년 창단 첫 통합우승 이후 5년 만에 두 번째 통합우승을 노렸으나 삼성의 기세를 넘지 못했다. 삼성의 주장 구자욱은 KS 최우수선수(MVP)에 선정되며 우승의 기쁨을 더했다. [서울=뉴스핌] 삼성 구자욱이 8일 대구 삼성 라이온즈파크에서 열린 KT와 2026 KBO 한국시리즈 5차전 득점을 기록해 포효하고 있다. [사진=삼성 라이온즈] 2026.11.08 willowdy@newspim.com 이날 선취점은 KT의 몫이었다. KT는 2회초 1사 1, 2루 기회를 놓쳤지만 3회초 선제점을 뽑아냈다. 선두타자 한승택이 유격수를 맞고 외야로 빠져나가는 안타로 출루했고, 권동진의 좌중간 안타와 최원준의 희생번트를 묶어 1사 2, 3루 기회를 잡았다. 이어 장진혁이 중견수 희생플라이를 날려 1-0으로 앞서갔다. 하지만 삼성은 곧바로 승부를 뒤집었다. 3회말 1사 후 김지찬이 스트레이트 볼넷으로 출루했다. 2사 후 타석에 들어선 구자욱이 우익선상 1타점 2루타를 터뜨리며 1-1 동점을 만들었다. 이어 르윈 디아즈가 오른쪽 담장을 직격하는 1타점 적시타를 날려 2-1로 역전했다. 계속된 공격에서 최형우의 우전 안타로 기회를 이어간 삼성은 김영웅의 좌중간 적시타까지 터지면서 3-1로 달아났다. 디아즈의 적시타는 이날 결승타가 됐다. KT는 4회초 1사 2루, 5회초 1사 1, 2루 기회를 잡았지만 후속타 불발로 추격에 실패했다. 위기를 넘긴 삼성은 5회말 타선이 폭발하며 사실상 승부를 결정지었다. 삼성은 5회말 박승규가 상대 유격수의 포구 실책으로 출루하며 공격의 물꼬를 텄다. 이후 구자욱의 우전 안타로 1사 1, 2루 기회를 잡았다. 디아즈가 3루수 뜬공으로 물러났지만 최형우가 우익선상 1타점 적시타를 날리며 4-1로 달아났다. 이어 김영웅의 타구가 상대 2루수의 몸을 맞고 굴절되면서 내야안타가 됐고, 2루 주자 구자욱이 홈을 밟아 5-1을 만들었다. [서울=뉴스핌] 삼성 강민호가 8일 대구 삼성라이온즈파크에서 열린 KT와 2026 KBO KS 5차전에서 적시타를 기록 후 환호하고 있다. [사진=삼성 라이온즈] 2026.11.08 willowdy@newspim.com 삼성의 공세는 멈추지 않았다. 이재현이 좌익선상 1타점 2루타를 터뜨리며 점수 차를 5점으로 벌렸다. KT는 류지혁을 자동 고의4구로 내보내며 만루 작전을 선택했다. 그러나 수비 실책이 뼈아팠다. 강민호가 2루수 앞으로 병살타성 땅볼을 쳤지만 KT의 2루수와 유격수 사이에서 송구와 포구가 제대로 이뤄지지 않았다. 그 사이 주자 2명이 홈을 밟으며 점수는 8-1까지 벌어졌다. 기세가 오른 삼성은 계속된 1, 3루에서 김지찬이 우중간을 가르는 2타점 3루타를 터뜨려 두 자릿수 득점을 완성했다. 이어 상대 투수 손동현의 폭투로 1점을 추가했다. 삼성은 5회말에만 8점을 몰아치며 11-1로 달아났다. 반면 KT는 연이은 수비 실책과 마운드 붕괴로 추격 동력을 잃었다. 삼성은 8회말에도 추가점을 뽑았다. 박승규의 투수 오른쪽 내야안타와 구자욱의 중전 안타로 만든 1사 1, 3루에서 김영웅의 타구가 유격수 권동진의 몸을 맞고 외야로 빠져나가면서 12-1을 만들었다. 이 과정에서 타구에 맞은 권동진은 구급차로 이송됐다. 마운드에서는 선발 원태인과 크리스 페덱이 KT 타선을 1점으로 묶으며 우승을 합작했다. [서울=뉴스핌] 삼성 원태인과 강민호가 8일 대구 삼성 라이온즈파크에서 열린 2026 KBO KS 5차전에서 마운드를 내려오며 대화하고 있다. [사진=삼성 라이온즈] 2026.11.08 willowdy@newspim.com 원태인은 5이닝 동안 4피안타 2사사구 5탈삼진 1실점을 기록하며 승리투수가 됐다. 3회 선취점을 허용했지만 추가 실점 없이 5회까지 마운드를 지키며 팀의 역전승에 발판을 마련했다. 삼성은 6회부터 선발 자원인 페덱을 투입하며 굳히기에 나섰다. 페덱은 4이닝 동안 안타와 사사구를 단 한 개도 허용하지 않는 퍼펙트 투구를 펼쳤다. 탈삼진 4개를 곁들이며 KT의 반격을 원천 봉쇄하고 우승을 확정했다. 반면 KT 선발 데이비스 대니엘은 3이닝 5피안타 2사사구 4탈삼진 3실점으로 패전투수가 됐다. 뒤이어 등판한 고영표도 1.1이닝 5피안타 1사사구 1탈삼진 8실점(2자책점)으로 무너지면서 팀의 패배를 막지 못했다. 정규시즌 1위로 KS에 직행했던 KT는 1차전 승리 이후 4연패를 당하며 안방에서 우승 트로피를 들어 올리겠다는 목표를 이루지 못했다. 반면 정규시즌 2위로 플레이오프부터 가을야구를 시작한 삼성은 KIA를 꺾고 KS에 진출한 데 이어 KT까지 제압했다. 12년 만에 다시 정상에 오른 삼성은 대구 홈팬들 앞에서 통산 9번째 우승의 기쁨을 만끽했다. *위 내용은 생성형 AI로 작성한 경기 상보 [명령어 : 11월 8일 대구 KT-삼성 KS 5차전 경기 내용을 정리해줘=CHAT GPT] willowdy@newspim.com 2026-11-08 17:21
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엔비디아 '젠슨 황 장녀' 방한 돌연 취소? [서울=뉴스핌] 백승은 기자 = 젠슨 황 엔비디아 최고경영자(CEO)의 장녀 매디슨 황 엔비디아 수석이사가 한국 방문 계획을 돌연 취소했다. 9일 IT업계에 따르면 매디슨 황 엔비디아 옴니버스·로보틱스 제품 마케팅 수석이사는 방한 일정을 취소했다. 단 구체적인 사유는 공개되지 않았다. 지난 8월 LG 데이터팩토리를 방문한 매디슨 황 엔비디아 수석이사 [사진=뉴스핌DB] 이번 방한은 9~10일 열리는 '엔비디아 AI 데이 서울 2026' 행사에 참석하기 위함이었다. 그렇지만 방한 일정이 취소되며 배경훈 부총리 겸 과학기술정보통신부 장관과의 면담 등 국내 주요 일정이 모두 무산됐다. 단 행사는 예정대로 진행된다. 국내 기업 협력 행사에는 엔비디아의 다른 임원이 대신 참석할 예정이다. 업계에서는 젠슨 황 CEO 주변 인물의 '중국 스파이' 연루 의혹이 방한 취소에 영향을 미친 게 아니냐는 관측이 제기된다.  100wins@newspim.com 2026-11-08 11:39
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