porate bonds because corporations regularly publish ... Livent and Fine Host Corporation show. In short ..... of default rates is the Moody's percentage-of-issuers.
Lessons from the Rise in Risk Premiums Martin S. Fridson, CFA Chief High Yield Analyst Merrill Lynch & Company, Inc.
The increase in risk premiums had profound effects on fixed-income markets in late 1998. As yield spreads increased, many firms-notably, Long-Term Capital Managementexperienced significant losses. Although learning from past mistakes is useful for avoiding the same mistakes in the future, capitalizing on the circumstances that led to the mistakes, should they happen again, is more worthwhile. Various analytical models are available to help analysts identify when yield spreads deviate from appropriate levels.
he somewhat optimistic title of this presentation implies that investors can learn from whatever mistakes they made prior to the huge decline in the financial markets that followed the Russian default on August 17, 1998. My research on stock and bond returns over the past century provides no evidence that investors learn from past mistakes made in financial markets. Nevertheless, volatility should enhance understanding of the markets. When nothing is going on except statistical noise, explaining anything is difficult. But when risk premiums double over a short period, the reason is clear, at least in retrospect. The debacle in 1998 thus helps fill in more of the picture of cause and effect in the markets. This presentation examines whether the quantifiable increase in risk in late 1998 justified the extent of the rise in risk premiums in emerging market debt. It also explores how the increase in risk premiums spread to the investment-grade and the high-yield sectors of the u.s. corporate bond market. The discussion addresses important factors that explain changes in default rates and yield spreads and, because hedge funds were on the front line during the debacle in late 1998, the key agency problems associated with hedge funds.
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Emerging Market Risk Premiums The most direct effect of the Asian crisis, which culminated in Russia's default on domestic debt, was the sharp rise in yield spreads on Brady bonds. These bonds are sovereign debt payable in Ll.S. dollars and are partly collateralized by u.s. T-bonds. Brady bonds arose from a previous crisis, namely, the debt crisis in the developing countries in the 1970s. The
©1999, Merrill Lynch, Pierce, Fenner & Smith Incorporated
lending spree of the 1970s culminated in a debt crisis in the early 1980s, and Brady bond securities were created out of the original bank debt. Figure 1 shows that the yield on Brady bonds shot up from about 400 basis points above Ll.S. 10-year Treasuries in March 1998 to about 1,600 bps at the peak in August 1998. The yield spread averaged lower than the peak for the year, but it has been up and down since then, partly because of another crisis, of sorts, in Brazil. One result of the rise in risk premiums, specifically in the emerging markets, has been the renewed asking of fundamental questions about Brady bonds as an asset class. I believe that sovereign bonds of emerging market countries are valid as an asset class and that, as a practical matter, they will continue to be part of the capital markets. But questions are raised every time these bonds demonstrate the kind of volatility experienced in March 1998.For example, Benjamin Graham was skeptical of this asset class because he knew it was nothing new. In many previous periods in which emerging market countries got into financial trouble, financing by various countries equivalent to today's G-7 group arose. Graham wrote about his skepticism of emerging market bonds in both The Intelligent Investor (1986) and Security Analysis (Graham, Dodd, and Cottle 1962). He thought emerging market bonds were the kind of security that comes around after people have forgotten how volatile such assets were the last time they appeared. Specialists in corporate bonds are also generally skeptical of giving credibility to emerging market bonds as an asset class, perhaps partly because they must compete for assets with emerging market
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Frontiers in Credit-Risk Analysis Figure 1. Yield Spreads: Brady Bonds versus 10-Year Treasuries, 1998 Spread (bps) 2,000,..-------------------------------,
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money managers. Most pension plan sponsors do not have the knowledge and resources to analyze every possible asset class, so a contest develops among managers to see which kind of debt they can get the client interested in. High-yield bonds sometimes wind up in direct competition with emerging market debt. Whatever the reason for managers' judgments, emerging market debt involves sovereign risk. Investors in these assets have to consider political events, which in the view of many market participants inherently cannot be analyzed. In contrast, say those who are wary of sovereign risk, investors can analyze corporate bonds because corporations regularly publish financial reports. These documents are concrete and useful in analyzing credit risk. Of course, those who follow financial reporting closely may take a skeptical view of the numbers the issuers report. Having numbers is fine; the question is whether the numbers are at all valid. The corporate earnings record of a company may be true or not, as the recent bankruptcies of Livent and Fine Host Corporation show. In short, for every disaster in emerging market debt, several equally horrendous debacles occur in the corporate bond area. The corporate sector is in some ways not much different from the emerging market sector. When a corporate debtor is close to a possible default, there are a lot of imponderables that cannot be reduced to numbers: A chemistry is going on between the lenders and the borrowers, the payment of the next coupon hangs in the balance, negotiations are under way, and the company mayor may not make it. So, corporate debt as well as emerging market debt can be unanalyzable at times. When people talk about sovereign risk being unanalyzable, however, I wonder what they mean. If there is no basis for discriminating among sovereign credits, then Venezuela must be just as good a credit 18
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as the United States. In fact, however, no investors in their right minds would trade all their U'S, Treasury securities for Venezuelan debt at a yield pickup just sufficient to cover the transaction costs plus 1 bp. But that is what they should do if they truly believe one cannot discriminate among sovereign credits. People do acknowledge the existence of certain standards. For example, the United States has not had any attempted coups in the past 10 years, has never elected a president who was the architect of a failed coup, and has a well-diversified economy (in contrast to Venezuela, where the economy is concentrated in one commodity, oil). So, in fact, some well-accepted standards exist for discriminating among the supposedly unanalyzable sovereign credits.
Contagion Because the United States is far away from Asia and Russia, Ll.S. investors may think disaster in the overseas markets will not affect them. My favorite example of this attitude came after the Mexican peso crisis in late 1994, when the so-called Tequila Effect spread and markets throughout Latin America and other developing countries experienced significant declines in security prices. The Wall Street Journal quoted a Brazilian engineer saying, "I do not know why they are worrying about us. We do not even speak Spanish." Contagion does take place, and basing decisions on the concept is not irrational. If every single time a crisis of major proportions occurs in one emerging market, the bonds of all the other emerging markets go down, it is not irrational for an investor to behave on the expectation that the same will happen the next time a crisis occurs. Analysts may not be able to explain perfectly why contagion occurs, but that failure does not alter
Lessons from the Rise in Risk Premiums the investor's conclusion. The link may be through a strain that is put on the world banking system as it tries to arrest the problem in many countries at a time. That stress genuinely increases risk through all the other countries. Alternatively, the link may be simply through a moral hazard-a risk resulting from questionable strategies or objectives of the debtor. Moral hazard arises when the International Monetary Fund (IMF) bails out a country: Doing so may encourage every other country to take the easy way out when it faces the difficult choice between enacting the politically unpopular austerity measures required to remain current on its debt payments or asking the IMF for another $70 billion or so to help it through a crisis. If international lenders, other agencies, and the IMF continuously act as enablers to emerging market debt addicts by simply "slapping their wrists" and giving them more money, one can easily predict what the other countries will do when they are in a similar situation. Of course, to change the pattern and address the moral hazard would be difficult for international lenders. If they decide to make an example of the next country that comes begging simply to teach them all a lesson in fiscal responsibility, they could set off a worldwide financial crisis that might be worse than the impact of the moral hazard. High-Grade Bonds. Through contagion, the
Russian debacle not only affected other emerging markets, it also brought about a sharp rise in risk premiums for high-grade u.s. corporate bonds. Figure 2 shows how the yield spread between U.S. investmentgrade corporate bonds and 10-year 'l-bonds shot up between July 1998 and August 1998, about the same time the Russian crisis occurred. Despite such evidence, many analysts have trotted out the predictable
arguments to deny that there was a connection. (One argument is the tiny percentage of Ll.S. trade with Russia.) Part of the reason for the rise in U.S. corporate bond spreads was that the Russian crisis accelerated the growing concern that certain countries were dumping various industrial commodities onto the world markets in order to generate foreign exchange to pay their debts. In addition, as investors pulled back from emerging markets and many brokerage houses experienced large trading losses, commercial banks became quite frightened about events, and liquidity in the markets dropped sharply. In such circumstances, distinguishing between default risk and liquidity concerns that affect overall spreads becomes difficult because the risks are not explicitly differentiated. Clearly, however, lenders become more conservative in such circumstances, and if they are not lending on securities to the same extent as they were previously, prices are affected. High~ Yield Bonds. The yield spread between Ll.S, high-yield corporate bonds and 10-year T-bonds also spiked between July 1998 and October 1998. Figure 3 shows how the spread to Treasuries for high-yield bonds jumped from about 380 bps to about 650bps in October 1998.The high-yield market is more closely related than the investment-grade market to emerging market debt. The two asset classes have similar interest rates and returns over time, so investors tend to look at one as an alternative for the other and try to carry out a relative valuation of the two. The high-yield market did not rebound as dramatically as the equity market or, as a comparison of Figure 3 with Figures 1 and 2 shows, the Brady bond market or the investment-grade corporate bond market. Spreads to T-bonds remained significantly
Figure 2. Yield Spreads: Investment-Grade Corporate Bonds versus 10-Year Treasuries, 1998 Spread (bps) 180r--------------------------------,
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Frontiers in Credit-Risk Analysis Figure 3. Yield Spreads: High-Yield Corporate Bonds versus 10-Year Treasuries, 1998 Spread (bps) 800,----------------------------..
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wider than previous levels for high-yield bonds. As the Fed eased interest rates, three drops occurred in the Federal funds rate and one in the discount rate from the end of September through the middle of October 1998. The spreads dropped by close to 100 bps on the high-yield index, flattened out, and have not changed much since then. Investors had some hope at the end of the year, after dealers' bonus pools had all been settled, that the dealers would resume market making and that liquidity would improve. The high-yield corporate market (and to a great extent the high-grade market) is not an exchange-based market; some high-yield bonds are traded on exchanges, but this market has little to do with the institutional round-lot market. Unless a buyer and a seller happen to appear in the market at the exact same instant and some intermediary happens to know that they have, the only way transactions occur is for a dealer to "open-end" the transaction-that is, take bonds into inventory on the expectation of being able to sell them to another institution before prices move much. The willingness to take open-ended positions decreased as a result of the trading losses that brokerage houses experienced in August and September of 1998, and the brokers had not changed their stance as of February 1999.The dealers were still wary of losses, so there was a rise in "roach motel risk"-the risk that one will be able to get into a bond but will not be able to get out. This risk is directly related to the current highyield bond premiums. A senior Bcompany has about a 1 in 11 chance of going bankrupt within the next year. Given those odds, if you own Brated bonds and you start to see the company going downhill, you want to be able to get out and cut your losses; if you are concerned that you will not be able to sell the bonds, you will require a large risk premium to own them-which goes a long way toward explaining the spreads in yields on high-yield bonds in 1998. 20
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Yield-Spread Determinants The yield spread on high-yield bonds in late 1998 was wider than the historical average, which has been 375-400 bps (depending on the time period). At the end of 1998, the spread was about 550 bps, and it has fluctuated some since then. The usual conclusion drawn from this evidence is that the high-yield market was cheap because the spread was wider than the historical average spread; therefore, high-yield bonds must have represented good value. Fridson and Bersh (1994), however, demonstrated in the [ournal afFixedIncome that if an investor bought high-yield bonds when the spread was narrower than average, the return was the same as if the investor had bought them when the spread was wider than average; thus, the historical average method was totally useless as a timing mechanism. Sometimes spreads are wide and get wider. The editor of the [ournal of Fixed Income wrote in the introduction to that issue, "This is a disturbing finding," which delighted us because we agree with the late Abby Hoffman that our job is not only to comfort the afflicted but also to afflict the comfortable. A truly disturbing finding, however, would have been that the historical average method does work. It assumes that the average spread is always the correct spread; anything wider is too cheap, and anything narrower is too rich. But the spread is a risk premium, and risk is not constant over time. The only valid way of concluding that a spread is too wide is if it is wider than the risk at that time warrants; so, an investor has to measure the risk in the system, which is easier said than done. To predict yield spreads, one need not rely on unquantifiable phantoms, such as market psychology. Chris Garman and I followed a time-honored method and looked at many possible explanatory variables for the spread of high-yield bonds over
Lessons from the Rise in Risk Premiums Treasuries. We tested which of those variables had an empirical correlation with the yield spread and developed a model (the Garman model) that consists of seven specific variables within three general categories that help explain the variation in yield spreads between high-yield bonds and T-bonds: 2 • Default risk The trailing 12-month default rate (percentageof-issuers basis) provided by Moody's Investors Service and Capacity utilization • Illiquidity risk Mutual fund flows as a percentage of fund assets and Cash as a percentage of high-yield mutual fund assets • Monetary conditions U.S. Consumer Price Index (year-aver-year change), Money supply (M2 minus Ml, year-aver-year change), and Treasury yield curve (lO-year bond minus 3month note) Using a multivariate regression model, we showed that those factors explain about 89 percent of the historical variance in the spread of high-yield 2Pordetails, contact us. Wecan send you the write-up of this model or the model itself in electronic form, together with the underlying data. You may be able to improve on the model; we encourage anyone to work further with it, and we would welcome a report of the results from those who are willing to share that information with us.
bonds over Treasuries. We time-tested the data by dividing the historical period into two subperiods and found that the results did not change substantially. The variables tracked reality well in most periods, as Figure 4 shows. (Keep in mind that this model is not by itself a forecast of the high-yield spread, for which one would have to forecast the underlying variables.) Note the sustained divergence of the model from the actual spread for the first time beginning in mid-1998. At the low point in the market toward the end of September and early October 1998, we issued a bullish statement saying that the highyield spread is generally overdone and presents a buying opportunity. Fortunately, with the help of Federal Reserve Chair Alan Greenspan, that judgment was vindicated fairly quickly. It could have gone the other way, but with the easing of interest rates, spreads narrowed much more quickly than we expected. So, the high-yield market did appear to be good value. Part of the reason for our bullish recommendation was that we could work with a model like the one presented here and solve for the default rate expected by the market. After all, one could have argued that the market was expecting a huge rise in the default rate, and that was why the spread was so wide. In fact, when we worked it out backward, we found that the implied default rate was 12-13 percent. We did not believe anyone seriously thought the default rate was going that high, although during the great debacle of 1990, it got as high as 10 percent.
Figure 4. Actual Spreads and Garman Model Spreads of Merrill Lynch HighYield Master Index versus 10~Year Treasuries, January 1992December 1998 Spread (bps) 700,-------------------------------,
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Frontiers in Credit-Risk Analysis Money Flows. In late 1998, the spread stalled at a level that continued to look much wider than it should be. That gap probably reflected greatly reduced market making. We would be delighted to incorporate statistics into the model on market making, but nothing is published about how much capital dealers are putting to work. Simple observation of the market reveals whether dealers are more or less active, but bid-ask spreads are not available. In most periods, that information is not essential. Ordinarily, the level of market making is subsumed by two variables that are in the model-the flow of money into the market, which is captured by one of the liquidity measures (namely, the inflows or outflows from high-yield bond mutual funds), and the slope of the yield curve. If the yield curve is positively sloped, the dealers are making money by holding inventory. They are borrowing in the short end and holding longer-dated, higher-yielding securities. They are eager to carry inventory because by doing so they earn positive carry. Once money starts flowing out of these mutual funds and the yield curve becomes negatively sloped, dealers stop answering the telephone, and the macho market-maker of a few weeks ago suddenly becomes not quite so aggressive. Ordinarily, if inflows to the high-yield mutual funds are good, the yield curve is not inordinately steep but is positive. Apparently, because they were smarting from the pain of the losses in 1998, dealers continued to be reluctant to jump into the fray. Calculating Default Rates. Comparing alternative methods of calculating default rates is extremely difficult. You can calculate them over a one-year period or over a multiyear period; you can
do it in terms of percentage of issues or percentage of issuers; and you can do it on a principal-amount basis. If you see discrepancies, do not assume that someone is trying to pull something on you. They are probably simply using different, equally valid, methods of calculating the default rate. Percentage-oj-issuers basis. Our primary gauge of default rates is the Moody's percentage-of-issuers series. This method has become subject to some controversy because Moody's includes all the bond default rates everywhere in the world and a lot of defaults have occurred in emerging market countries in the last several years. The defaults on that basis are thus higher than they would be if the emerging market countries were excluded from the sample. The default rate for 1998calculated on a principal-amount basis without the emerging markets was 1.60 percent, only about half the comparable figure for Moody's. Another measurement issue is whether one considers a default to have occurred at the time the company misses the coupon or at the end of the grace period. But the big difference is whether or not emerging markets are included. A lot of money managers say emerging markets should not be included, but if they invest in emerging market corporate bonds, they should include that debt when measuring the default rate. Both methods of calculation are useful. Figure 5, calculated on the percentage-of-issuers basis, shows that despite the Fed's reliquification in mid-October 1998, defaults continued to escalate in 1998, although not alarmingly. !II Quality oj pastissuance. One of the factors we used in another model that we created to predict
Figure 5. Moody's Trailing 12-Month Default Rate: Percentage-at-Issuers Basis, 1998 Rate (%)
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lL-..---"-----'-----'------'----'-------'----'---.l...------'----'------' Feb Mar Apr May [un Aug Sep Oct Nov Dec Jan Jul Source: Moody's Investors Service.
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Lessons from the Rise in Risk Premiums historical default rates was the quality of past issuance, which takes into account not only the mix of bonds outstanding (by rating) but also an aging effect-that is, when the particular BBsor Bs came to market. Both of those aspects are important, and the quality variable considers both. Some people believe ratings and defaults are not connected. They say the rating agencies do not know what they are doing and only look backward. This kind of comment generally comes from people who do not get the answer they want to hear when they ask what rating a company's debt has. They attempt to discredit the whole process on the argument that 25 years ago a certain BBB rated company defaulted while it had a BBB rating so the entire rating process is invalid. Any fair-minded person who looks at the data will find, however, that CCCs default at a higher rate than Bs, Bs default at a higher rate than BBs, and so on in a monotonic fashion. So, if underwriters produce a lot of junky debt, we will see a rise in the default rate. The bankers are clever enough to bring companies to market when their numbers look good, so the increase in defaults may not be immediate, but the connection clearly exists. Thus, quality of past issues is an important variable in the model. II Real interest rates. Another important variable is real interest rates with about a two-year lag. Nominal interest rates, as far as we can tell, have no correlation with default rates. That answer may be surprising, but a meaningful correlation occurs only when the inflation rate is removed. II Large-cap versus small-cap PIEs. The relationship of large-cap and small-cap companies' PIEs is important because the ease of equity financing in the last of couple of years has meant that shaky companies, instead of going bankrupt, go public. When the PIEs of large-cap companies and small-cap companies are close together, raising new equity at the margin is fairly easy, which allows some companies to escape default by virtue of adding some equity. III Macroeconomic conditions. Contrary to what one often reads, although the economy has some bearing on default rates, it does not determine default rates. An even worse mistake is the assumption that the default rate goes up when a recession arrives. The data do not support that assumption. The portions of time series that indicate recessions do not, in fact, coincide with the peaks in the default rate. Logically, they should, but researchers at the New York Federal Reserve have found that the inflection point at which the default rate begins to surge is not the point of recession (that is, negative GOP growth) but simply the point of slowing growth-in the range of 1.5-2.0 percent. The relationship between GOP and the default rate is not linear; the economy slowing from
4 percent to 3 percent does not make much difference, but the economy falling into the 1.5-2.0 percent range correlates with a rise in defaults. The probable reason is that banks have on their books at any given time loans to some struggling companies. If the economy is growing at 3-4 percent, their inclination is to roll those debts over in the hope that those companies will grow their way out of their problems. When the whole economy slows to less than 2 percent growth, however, the banks figure that a struggling company is much less likely to grow its way out of its problems. That is when they pull the plug. Banks are an important part of the picture because of that disparity I mentioned between the default model and the actual default rate for 1997 and 1998. In those years, the default rate ran substantially below what our four-factor model estimated it should be. The reason might have been that the model is time dependent, but because the model's estimate and the model came back in line, I am not inclined to think so. The reason might have been, as market buzz had it at the time, that structural changes have occurred in the economy. Some even implied that because of Baby Boomers' spending and because of changing microchip technology, perhaps no defaults would occur in the future. However, default rates have recently, in fact, been on the rise. I believe the discrepancy was that the banks were being forbearing. Practically all the capital in the world was flowing into the United States, resulting in tremendous liquidity in the U.S. financial system, including the banks. Stories were circulating about companies that were clearly bankrupt, but even as the lenders would be writing off the loans in their minds, another group would be coming in and miraculously replacing the whole loan facility. Lenders were so eager to put money to work that it was almost impossible for companies to fail. Now, the banks have changed. We hope to refine our model in the future. Despite all the regulation of banks, we previously were not able to find a data series that went back far enough to capture the forbearance on the part of the banks. One series goes back to 1990, but that date is not distant enough for us to incorporate the information in our model. That series is the survey conducted by the Fed once a quarter in which it asks senior bank lenders whether they are tightening or easing their standards for making loans at the moment. The Fed reports the difference between the percentage tightening and the percentage easing. In the third quarter of 1998, the difference changed from about 10percent more banks tightening to about 30 percent. At the same time, sure enough, a definite surge in defaults occurred. u.s. company defaults had been running at about 5 a month throughout 1998 and, in Decem-
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Frontiers in Credit-Risk Analysis ber, surged to 15. That pace did not continue, probably because the Fed survey done in November showed that the ratio was falling. About 7 percent more were tightening than were easing. The actions by the Fed in September and October apparently changed the attitude of the commercial banks. Although a stream of defaults continued in the steel industry, the energy industry, and a few other isolated pockets of the economy, there was not an overall surge in defaults. • Contingent claims. The contingent claims model does not perform well in connection with the question of default rates. My colleague Jon Jonsson and I (1997) found that a contingent claims model is a useful tool for analyzing the relationship between the equity price and the bond price for companies, but anomalies can arise if the contingent claims model is accepted as a complete explanation of reality. For example, when the Marriott Corporation decided to break into two pieces, it did the logical thing: Take the worst assets and give them to the portion of the company where the bondholders will be and, of course, keep the good assets in the part where the equityholders will be. Not surprisingly, the bonds decreased in price and the stock price increased, which is not supposed to happen in a world fully described by the contingent claims model. Not only did the bond and stock prices move in opposite directions when this move was carried out, but the CEO of the company then went to Hilton Corporation. The day his hiring was announced, the bonds of Hilton went down and the stock went up. He had not even sat down at his desk yet, but investors (correctly) anticipated that he would do essentially the same thing at Hilton that he had done at Marriott. Another example involves the referendums held in several states in November 1994 on whether to legalize casino gambling. The majority of the referendums were defeated. The following year, the casino stocks underperformed the S&P 500 Index whereas the casino bonds outperformed the high-yield bond indexes. Such an outcome should not happen in a contingent claims world, but it did, and there is a simple, logical explanation: From the casino equityholders' standpoint, the defeat of the referendums meant that the casinos had much less opportunity for growth than people had envisioned prior to the votes. From the standpoint of bondholders who were lending to the casinos in areas threatened by new potentially competing legalized-gambling jurisdictions, the defeat of the referendums postponed the possibility of a loss of revenue.
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Agency Problems in Hedge Funds The final lesson to be learned from the increase in risk premiums can be illustrated by the debacle surrounding Long-Term Capital Management. Some other hedge funds were affected by the rise in risk premiums, but LTCM, in the size of the effect, is very much an outlier. No other firm had done anything as aggressive and extreme in terms of leverage. Wall Street's exposure to LTCM was $1 trillion. Such an extreme case in the presence of so much volatility highlights three particularly important issues-carried interest, moral hazard, and market-maker activities. Carried Interest. The compensation structure of hedge funds creates a great incentive for hedge fund managers, as general partners, to take inordinate risks with other peoples' money. The term "hedge fund" does not have anything to do with hedging. At one time it may have, but today a hedge fund simply involves the creation of a limited partnership. In general, hedge fund managers charge their clients an incentive fee in addition to a standard management fee-the carried interest. The most common formula includes an annual management fee of 1 percent of assets under management and 20 percent of the net annual return-not a 20 percent share of the losses but a 20 percent share of the profits. Inevitably, such a structure skews the manager's attitude toward risk taking because it means that the manager is predominantly not risking his or her money but other peoples' money. The general partner may have some equity investment in the fund (the general partners in LTCM did have a substantial equity investment), but the structure still creates agency problems. Moral Hazard/Systemic Risk. The issue of moral hazard, which was discussed in connection with emerging markets, was also associated with LTCM because the firm was big enough to present systemic risk. As the saying goes, if you make a small loan, you are a creditor, but if you make a large loan, you are a partner. The New York Federal Reserve was careful to say the bailout was not a government bailout, and in a narrow sense, that is true, but the possible systemic risk was clearly a concem-even to the Fed in Washington D.C. The principals of LTCM certainly took full advantage of this fact and managed to obtain, if not a government bailout, then a government-brokered rescue, one that provided them continued control of the firm. This performance was remarkable, especially considering that Warren Buffet was prepared to buyout the whole fund on the condition that the principals be dismissed. Market Maker Doubling as Lender. The third problem with LTCM was that the market makers-
Lessons from the Risein Risk Premiums namely, the brokerage houses-doubled as lenders. Brokerage houses have risk managers who are supposed to manage firmwide risk and are generally unpopular; the traders grumble that the risk managers are always trying to prevent them from doing business. The question when the market makers are also the lenders is whether the risk-management function has any teeth or whether risk-management decisions are overridden by business considerations. For example, suppose a firm offers to buy $1 billion of some derivative security from you and asks you to finance that purchase. When you perform due diligence and ask where the money will be invested, the firm assertively "reminds" you that another firm is willing to do the deal without asking so many annoying questions. LTCM was very astute at playing firms off one another, thus inducing brokerage houses to override their risk-management functions. Firms ended up financing marginal business for LTCM without transparency about how the money was being invested. LTCM,which was adept at this game, was putting the money into risk arbitrage, which is a fairly simple business: If the fund guesses right about whether a takeover will go through, it makes a lot of money; if it guesses wrong, it loses a lot of money. That LTCM was putting money into such businesses ran somewhat counter, however, to its stated business plan. An ironic twist today is that the principals of LTCM are in a position to decide to whom they grant
interviews. A lot of people would like to interview them, but they do not have to talk to anybody. One writer to whom they granted an interview (Michael Lewis, author of Liar's Poker: Risingthrough theWreckage on Wall Street) published a lengthy article in the New York Times Magazine (1999). He quoted them as saying that the cause of their downfall was that the brokerage firms that were lending them money got wind of their trading strategies and began to trade against them. Getting that allegation printed in a reputable publication is another remarkable achievement. The brokerage firms contend that they had no idea what LTCM was doing with the money; they now believe they were probably too lax in not demanding to know more and not tightening up standards.
Conclusion The year 1998 was painful for most in the fixedincome investment management business, but lessons can be learned from the rise in risk premiums. The cynic's view of experience is that it teaches you to recognize the mistake when you make it again. I take a somewhat more constructive view of the 1998 experience. I believe we can apply the lessons learned to future decisions. The challenge is to find the ways to capitalize on those lessons in the context of the institutional constraints under which we all operate.
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Frontiers in Credit-Risk Analysis
Question and Answer Session Martin S. Fridson, CFA Question: Have you done any empirical analysis of what the profitability or possible return enhancement might be from using models for predicting yield spreads? Fridson: Simply using the average spread over Treasuries provides no advantage. In the tests we ran, we looked at quarters to see whether those quarters when the spread was wider than average produced higher mean returns (of statistical significance) than those quarters that began at narrowerthan-average spreads. Then, we asked: How long a period from that date do you measure? If you measure to some point where the spreads move dramatically in the other direction, you know you probably made money, but then the choice becomes somewhat arbitrary because each of those periods is slightly different. So, we looked one quarter out and six months out. When we started to look beyond those periods, we got too small a sample size (in terms of number of periods) to achieve statistical significance. If you could use the average spread method to genuinely determine exactly the right time to reverse the trade and if you had the staying power to hold even when the market was going against you, perhaps you could make money. Even in the case of looking one quarter out, we ran into the same problem in trying to use the Garman model to determine whether the market is cheap or not. As I mentioned, not many periods that lasted long showed a spread outside the range of ±1 standard deviation from where the model said the spread was supposed to be. Of course, a lot of other things are
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going on, but interest rates going up or down notwithstanding, the spread might go the right way and, in terms of earning a superior return, the interest rates might go against you. So, gauging the results of simply following a trading rule is hard on the basis of a model of spreads versus Treasury yields. The greatest value in using the Garman model is in trying to form a view of the future. Most people managing money, unless they are running a purely passive portfolio, do have some view of the future and have opinions about what the economy and interest rates are going to do. Our model of the spread versus Treasuries is beneficial in that we identified the variables and the factors that matter. For example, you may be trying to relate your economic scenario to future spreads. The change in spreads wilt of course, have a large impact on the total return of the high-yield market between now and that horizon date, but without the use of a model that identifies which factors actually influence spreads, you may be translating your economic forecast incorrectly into those future spreads. So, the contribution of the model, we hope, is that it gives you a more accurate way of translating your expectations about the future into a judgment of today's valuations. Question: Have you recalibrated the model to adjust for the discrepancy in the tracking of the model for 1998? Fridson: A couple of years ago, we did a recalibration, but we wouldn't want to change it every month. At that time, we had a few years of live experience, so the sensible approach was to take
advantage of the additional data. The recalibration didn't change the model much, only a couple of basis points here and there, in terms of the final estimate. Up to that point, it had been a fairly stable gauge of spreads. At present, judging by the impact last time around, recalibration will not make much of a dent on the outcome. What we really need is a way to capture the element representing dealer market making, which although it seemed to have been subsumed by other variables in the past, has recently had an independent effect. In the absence of any data on what dealers are doing, we don't have a way to incorporate that element explicitly. Question: In your model, did you consider sources other than mutual fund data for quantifying liquidity? Fridson: We defined the highyield mutual fund flows as a liquidity variable. You might consider it something else. It has an empirical correlation with the spreads; apparently, if money is coming into the high-yield funds, the effect is a general inflow into the high-yield bond market. Dealers are more willing to make markets when money is flowing in because they tend to be net long in the high-yield market. If money is coming into the market, they have confidence that they will be able to sell what they buy. So, we interpret the mutual fund flows as an indicator of liquidity. We found that the percentage of assets held in cash by mutual funds also has a correlation with liquidity. The mutual funds apparently build up cash reserves when they are uneasy about the outlook.
Lessons from the Rise in Risk Premiums The literature on liquidity in equities advises looking at such factors as bid-ask spreads and volume relative to price moves. For example, if 5 percent of the stock changes hands in a day, how big a percentage price move will result? In corporate bonds, we don't have such data. We have somewhat reliable price data for a portion of the universe, but we have none on trading volume. If we could get our hands on those data, we could clearly improve the model. What are your thoughts on looking at spreads in terms of absolute levels versus percentages of Treasury yields? Question:
Fridson: We thought long and hard aboutthis issue. We tested the spread and what we call the "proportional yield spread" method, and it did not work any better empirically than simply using the absolute spread. Neither approach was effective as a timing tool when the idea was to compare the number with its historical average. The reason analysts give for using proportional rates is that if rates are low, investors need a bigger percentage of the Treasury rate to induce them to buy high-yield bonds. So, using proportional rates seems logical to people. But there is no reason for the proportional spread to be a function of the level of nominal interest rates. My impression is that the investment bankers invented the argument for the proportional spread. They would argue that high-yield bonds might not look attractive right now but they still look great as a percentage of Treasuries. Investment bankers hope that people won't think about it too carefully. The problem I haven't been able to resolve is the lack of connection between default rates and nominal interest rates. We know that the spread versus Treasuries is
primarily a function of the default risk. Liquidity may get a little better or a little worse from quarter to quarter, but spreads are primarily a function of the default rate. We have found no correlation between nominal interest rates and default rates. Suppose Treasury bonds are at 6 percent and highyield bonds are at 10percent, so the spread is 400 bps. Suppose you consider a two-thirds yield premium-that is 400 bps over the 6 percent Treasury return-an attractive level at which to own high-yield bonds. Now, suppose Treasury rates rise to 8 percent and the spread remains 4 percent, so the yield premium is now only 50 percent. If there is no statistical connection between nominal Treasury rates and the default rates, default risk hasn't risen. So, if 400 bps was sufficient before, it should be sufficient now. In the long history of this relationship (in the so-called Hickman Study of 1958, which covers yields and spreads going back to 1900),you will find a remarkable consistency in risk premiums. In periods when Treasury rates were 2-3 percent, the risk premiums on high-yield bonds were not 1 percent or 0.5 percent; they were about what they have been in more recent periods. As far as I can tell, the yield spreads are not sensitive to the level of interest rates. Question: Do you think that there are time-dependent paradigm shifts in analyzing high-yield bonds? For example, the 1980s saw a huge growth in high-yield bond sales, which has not been matched in the 1990s.Can we use 1980s data to analyze the 1990s? Fridson: It depends on the kind of data. We can look at historical default rates in an attempt to project future default rates. One technique is to project the historical default rates by rating. Some
people have pointed out that default rates were only about 1 percent a year in the 1970s, then (according to the argument) in the bizarre period in the late 1980s, they went way up. Now, in more normal times (the reasoning goes), default rates are not going to rise from 1.5 percent. Of course, they already have gone higher than 3 percent, so that argument has already been refuted. We can easily estimate that in that earlier period, 85percent of the high-yield debt was BB quality. So, it's hardly surprising that default rates were very low. That mix is not the mix we have today; it is more like 50 percent BBand 50 percent B with some component of CCC in the picture. If we assume that default rates are constant by rating category over time, default rates are not at all likely to go back to 1980 levels. Of course, whether the criteria for rating categories change over time is an empirical question. The argument has been made that the rating agencies have tightened their standards. By that reasoning, default rates will be lower than you would project based on the historical default rates. Supposedly, the Bof today is better than the Bof the past. On the face of it, however, the stupidest decision the rating agencies could make would be to change their standards. They make a lot of money rating collaterialized bond obligations, and the premise of a CBO is that you can, in fact, project future default rates based on past experience. The rating agencies may have changed standards unconsciously over time. Some evidence exists to support that conclusion. You can make a valid argument that the leveraged buyouts (or overleveraged buyouts) of the late 1980s were somewhat overrated, which would imply that the default rates were too high on many B rated securities. Perhaps some should
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Frontiers in Credit-Risk Analysis have been rated CCC, in which case the default rates would have been higher on the CCC class and lower on the Bclass. It appears that default rates for BBand B bonds were higher for a few years in the early 1990s rather than perfectly consistent over time. That's not surprising, because leveraged buyouts were a new class, and unless you have a long historical record of a type of credit, getting a rating exactly right is difficult. If the result of all this is that we have good historical default rate data by rating for a 20-year period but 3 of those years reveal very high default rates that may have been influenced by an underrating of leveraged buyouts, you'd probably want to scale down those expected default rates somewhat.
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We found, however, that people were making the argument for changing standards at a time when default rates were close to the lowest level they had ever been. The Merrill Lynch High-Yield Master Index sank to 260 bps over Treasuries, about 115bps narrower than its average level historically. Some people were seriously arguing that we were encountering a new paradigm. They thought the spread had found a new level and would never widen from 260 bps because of CBOs; that is, if the spread were to widen to 261 bps, the CBO funds would swoop in and buy up all those bonds. In every crisis since that time, however, the CBO funds have not swooped in to buy the bonds up. They're not run by idiots. They concluded that they didn't have any obligation to bail
out the secondary market and that new issues would come at a considerable price concession to the secondary market, so they filled their needs there. Arguments about"a new paradigm" come along somewhat predictably, but one after another, they fall down under the test of time. In my book that covered the past 100 years in the stock market (1998), I reported only one paradigm shift. Despite all the technological changes and the changes in margin lending standards and everything else, the one shift that made a difference was the one that Peter Bernstein pointed out in Against the Gods: The Remarkable Story of Risk (1996): In 1959, yields on stocks fell below yields on bonds and never changed back.
