I need to see real growth in metrics like customer acquisition and trading volume before making a deeper commitment. From what I can tell, the news about EDXM will only be positive for Coinbase if it helps to expand the pie for the crypto industry as a whole. That's right -- they think these 10 stocks are even better buys. Independent nature of EDXM would also restrain the firm from the possibility of conflicts of interest. EDXM needed to prove its utility to stay relevant within the crypto space though. For now, I'm taking a wait-and-see backed crypto exchange with Coinbase. Meanwhile, the EDX exchange would work to accommodate both private and institutional investors.
Harperbusiness 1991 investing
Condition: Fine. Dust Jacket Condition: Fine. First edition, first printing in Classic book on value investing. Octavo, original half. Fine in a fine dust jacket. No writing. Appears to be an unread copy. Klarman Investors are all too often lured by the prospect of instant millions and fall prey to the many fads of Wall Street. New York: The Cunningham Group, Shareholder Letters, Cialdini, Robert B.
Influence: The Psychology of Persuasion. Revised Ed. New York: Harper, Fisher, Philip A. Common Stocks and Uncommon Profits. Conservative Investors Sleep Well. Graham, Benjamin, and David L. Security Analysis: Principles and Technique. New York: McGraw-Hill, Greenblatt, Joel.
Hagstrom, Robert G. Investing: The Last Liberal Art. Latticework: The New Investing. New York: Texere, The Warren Buffett Way. Hoboken, NJ: John Wiley, Kahneman, Daniel. Thinking, Fast and Slow. New York: Farrar, Strauss and Giroux, Klarman, Seth A.
New York: Harper Business, Loomis, Carol. New York: Portfolio, Lowe, Janet. Damn Right! New York: John Wiley, Lowenstein, Roger. Buffett: The Making of an American Capitalist.
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Note the average annual return spread was 1. New high-yield bond issues all but disappeared in Exhibit 1 and there was considerable concern about the very survival of the market as the year commenced. Most analysts and knowledgeable commentators expected continued high default rates. With additional pressure exerted by liquidity concerns, the market's average yield spread over ten-year U.
Treasurys by The high return spread over Treasurys continued for the first half of , when junk bonds had a return of One type of junk bond that has increased of late is original issue investment grade bonds which have fallen to noninvestment grade. By far, the main use of these proceeds was to reduce debt. The Default Rate Controversy Ever since the classic study of corporate bonds published by Hickman [31], economists have been measuring and reporting default rates.
Despite this considerable scholarly lineage, early in , well-established methods for measuring default rates suddenly became the subject of intense controversy in the financial press and later in academic journals. Articles appeared announcing the results of supposedly "new" research that led to a more negative view of junk bonds than that projected by existing works. In this paper, I will attempt to shed some light on the lingering debate over the proper measurement of default rates.
I will start by explaining the traditional method for measuring defaults of junk bond portfolios and then compare the results of using this method with the default rates produced by the more recent "mortality" or "aging" concepts. The bottom line here is that the new default studies, however much their differences with the old have been exaggerated by the press, are really quite consistent in their findings with existing, more traditional work.
And, finally, I will attempt to use the existing research on junk bonds as a basis for speculating about future default rates and investor returns in the high-yield market. Traditional Measures of Default Rates and Losses Accurate measurement of default risk is, of course, critical to the task of determining the required risk premiums on bonds of different credit quality and evaluating the returns on those securities.
The traditional method of measuring annual default rates is based on comparing the dollar amount of all issues defaulting in a given year divided by the dollar value of all bonds outstanding as of some point during that year. For any given category of bonds, the annual default rates are then added and averaged over some longer time horizon to provide an estimate of the average yearly rate of default.
Historical Default Rates Exhibit 4 shows the average annual default rate, calculated using the method described above, for below-investment-grade debt for the period to , as well as for selected intervals within that year period. The arithmetic average annual default rate for the period to is 3. In the most recent nine years to , however, the average default rate increased to 4. These average rates give equal weights to each year.
If, however, one weights the individual year results by the amount of high-yield debt outstanding, then the weighted average default rates are considerably higher, since the last three years to have been relatively high default years with greater amounts outstanding. Indeed, the weighted average annual rate for the period to increased to 5.
Recently Altman [5], I have calculated "traditional" default rates in a slightly modified fashion by subtracting, from the population base, those issues which are already in default. For the years prior to , this modification made little difference, since defaulting issues were small relative to the total market size. With the huge increase in defaults of late, this differential is now material.
For example, the modified default rates for and are I believe the modified method is more representative of default incidence since the reduced population base represents the portfolio of high-yield bonds that could default. During the first quarter of , default amounts and rates have fallen considerably from the record levels of and The more relevant default statistic for most investors is not the rate of default, but rather the amount lost from defaults.
The use of default rates alone effectively assumes that the value of defaulting bonds turns out to be zero. And, the ability to sell defaulting debt at nontrivial levels signifies a positive liquidity aspect of publicly traded corporate debt that, until recently, was not evident in privately placed debt.
Altman and Nammacher [9] and [10] published studies that attempted to measure the amount lost from defaults. In making these calculations, we assumed investors had purchased each defaulting issue at par value and sold it at the end of the month in which the default occured, losing one coupon payment as well as any capital depreciation. The default loss calculation for is shown in Exhibit 6.
The loss was 7. Over the period to , the weighted average default loss was 4. Exhibit 8 breaks down the recovery rate by seniority of the bond issues. The breakdown of recovery rates by seniority is extremely relevant to investors who hold different tranches of debt and also to analysts who attempt to assess expected default loss rates on nonpublic debt issues and on commercial loans.
Finally, it is relevant to corporate issuers in their negotiations with advisors, bond raters and debtholders as to the seniority of new debt offerings. Rating Drift of Defaulted Bonds Altman and Kao [11] and [12] explored the phenomenon that we call rating drift or credit quality changes over time.
We observed the ten-year post-issuance bond rating change experience of all new issues from to In Exhibit 9, we can observe that of the issues that defaulted from to , Therefore, On the other hand, the fact that the proportion of defaults that were still investment-grade is smaller as default approaches, and almost none were still in this category at the time of default, could lead the rating agencies and perhaps others to comment that these percentages vindicate the accuracy of their overall ratings.
Obviously, these statistics have relevance to high-grade as well as low-grade debt securities investors. Finally, it is important to mention that bondholders lose not only from defaults, but also in cases of financial distress that do not result in a legal default but rather in distressed exchange arrangements. Of late, these distressed exchange, out-of-court arrangements are being replaced in many cases by so-called "prepackaged Chapter 11 bankruptcies," where the exchange takes place under the less stringent voting requirements of the Bankruptcy Code.
Because of such biases, the most recent default history -- while immensely useful to portfolio managers and other investment officers in projecting near-term expected losses and setting aside adequate reserves to cover such losses -- may turn out to have been an unreliable basis for assessing longer-term losses. Why is that so? First of all, as with all historical studies, it could be suggested that the future is not likely to repeat the past.
Both the numerator that is, the amount of annual defaults and the denominator the amount of bonds outstanding in the default rate ratio will surely change in the future. And, if the amount of "junk" bonds outstanding that could defaults does not increase as it has in the past or even falls, as it has in the last two years while the amount of defaults continues to grow, then default rates and investor losses will rise above the historical levels reported using the traditional approach.
I have also argued Altman [7] , howevr, that the opposite trend will take place in the near future. That is,in and beyond, as new issues begin to rise from depressed levels and as the defaults arising from past excesses are purged from the market, default rates for and measured traditionally are likely to be overestimates owing to this same bias. Indeed, this appears to be occurring, and Fons [22] is now predicting a lower default rate for A related criticism of the traditional method for calculating default rates -- and the one that was seized upon by the press -- is its failure to consider the possibility that the likelihood of default rises with the age of the bond.
In putting all junk bonds outstanding at a given point in time in the same basket, the average annual method effectively assumes that the probability of default for a newly issued bond is identical with that of a bond that has been outstanding for, say, five years. But if it is true that the probability of default rises with age -- especially in the case of junk bonds which are often "called" after the early years -- then default rates on currently outstanding issues will begin to rise.
And if the rate of new issuance is expected to fall, then current annual default rates would provide a misleadingly low predictor of future expected default rates. Briefly stated, the basic contention is this: because of the rapid growth of the junk bond market during the s, use of the traditional methods for measuring defaults could have blinded investors to the reality that effective default rates were rising well above reported levels.
While the aging argument has some intuitive appeal, the more important reason for the considerable rise in default rates in and was the debt excesses of to caused by the incredibly high premium paid for corporate acquisitions and restructings. The combination of increased cash-flow-multiplier transaction prices and the consequent excessive debt necessary to finance these high price transactions of questionable LBO firms to start with, resulted in a large number of distress situations.
And, as Altman and Smith [13] demonstrate, unless the firm can pay down that considerable debt burden rather quickly, the probability of distress increases. Combined with declining asset sales and the lack of refinancing opportunities, the highly leveraged, e. Two Recent Studies -- And Much Confusion Two recent academic studies explored the aging issue by attempting to determine whether the probability of default of individual high-yield issues increases with time after issuance. The first of these was a working paper I produced at NYU in which was later published, Altman [3].
The second study -- and the one whose circulation in early aroused such intense interest in the press -- was a study by Paul Asquith, David Mullins, and Eric Wolff [15]. Now, what exactly did these studies set out to do? And what did they find? In my working paper, I examined all corporate bonds issued between and updated in this paper through in an attempt to determine whether the probability of default increases with age a trait I referred to as bond "mortality".
In so doing, I classified all bonds into one of seven individual bond rating cohort groups, including the four investment-grade as well as the three noninvestment-grade ratings. I then sought to estimate what proportion of the par value of bonds originally issued in a given year and in a given rating were still outstanding after the lapse of different periods of time.
The original group of bonds was therefore reduced by calls, sinking funds, and maturation, as well as by defaults and exchanges. These results cover new issues from to and defaults through Before elaborating on the results of my own study, let me mention the approach taken by Asquith, et al [15]. They too calculated cumulative default rates by tracking the "aging process" in specific year cohort groups. They focused almost exclusively on junk bonds without attempting to distinguish among the three different classes of low-grade bonds nor do they treat investment-grade bonds.
Comparison of the Results As compared in Exhibit 11, the results of the two studies are quite similar. For example, in calculating the default rates five years after issuance of all B-rated bonds, I found the cumulative mortality on default through for this dominant junk bond category to have been The ten-year cumulative default rates reported by the two studies are also very similar.
Whereas Asquith, et al reported that Asquith, et al also found that roughly a third of the bonds had been called. Also summarized in Exhibit 11 are the results of one other recent study of junk bond mortality, by Lucas and Lonski of Moody's [37]. The Moody's study, which focused on default rates among issuers rather than issue, came up with results pretty much consistent with the others.
For example, although Moody's does find somewhat higher five-year cumulative defaults for single-B and double-B issuers, the total weighted average rate of And, Asquith, et al do not attempt to measure default losses, to which we now turn. Mortality Losses We can measure mortality losses in a manner similar to the earlier default loss calculation. By considering recovery rates and lost coupon payments on all defaults in our mortality database, we can calculate mortality losses in Exhibit As in Exhibit 10, the results are listed for data through The five-year cumulative mortality loss increased to The average annual loss calculated from the five-year cumulative rate is very similar to the average rate of 4.
Given this reasonable amount of scholarly agreement about the historical cumulative default rates on junk bonds, what do these numbers really have to tell us about future expected default rates? Asquith, et al interpret their findings as clear evidence that the probability of junk bond defaults increases with the age of the bonds. And, as mentioned earlier, to the extent that this "aging" interpretation is correct, then a slowdown in the rate of new issuance must lead inevitably to a sharp rise in annual default rates.
My interpretation of the new evidence, however, is considerably more cautious. As I cautioned in my initial working paper, the "modern" junk bond market is still quite new, having gotten its real start only as recently as For this reason, the mortality results for the relatively long say seven- to ten-year horizons are based on relatively few years of original issuance data.
For example, at the time of my original study, ten-year mortality rates could be calculated only for the group of high-yield bonds issued in and , nine-year mortality rates only for bonds issued in , and so forth. For results through , ten-year rates cover bonds issued from to And making generalizations from a sample this small is, needless to say, a questionable practice.
One canot deny that, as you increase the horizon on any investment in risky bonds, the cumulative default rate will rise over time. But that is not the same thing as saying that a six-year bond with a BB rating has a higher probability of default in the next four years than a younger bond in the same risk category.
Having said this, though, I am somewhat sympathetic to the "intuition" behind an aging process for corporate bonds. That argument, as mentioned earlier, holds that because the probability of call increases with a bond's age, and because creditworthy companies are more likely to call than their weaker counterparts, then the remaining group of bonds will have a greater probability of future default than the original population.
The same is true for firms that directly repurchase their debt in the open market when the bond's prices become attractive. The representatives of such agencies, in fact, argue that the age of a bond has no systematic effect on its creditworthiness provided the bond's current rating is the same as its initial rating, and provided the current rating remains an unbiased estimate of the future rating -- that is, neither too high nor too low on average. For example, a BB bond at issuance should have the same probability of default in years 1 and 2 as a five-year-old BB bond in years 6 and 7.
Only if BB bonds in the aggregate have a higher probability of slipping to a lower rating after, say, five years than rising to a higher rating will the expected default rate rise systematically over time. Bond Rating Drift and Aging As stated earlier, such a propensity for bond ratings to drift lower had neither been tested nor demonstrated by scholarly research. Since that time, Altman and Kao [11] analyzed the ten-year junk bond rating drift propensity over the period to and found that, while investment-grade bonds had a much greater likelihood of being downgraded vis-a-vis being upgraded, the same tendency did not exist for junk bonds.
To follow the movie-by-movie results, see Exhibit 2. Significantly, the potential for this profitable performance was not foreseen by financial analysts at the time of the Disney acquisition. These films all share continuity with each other. Noted investor Seth A. What appears to be hidden assets today could turn out to be liabilities tomorrow. A decline in the stock market will reduce the value of pension fund assets; previously overfunded plans may become underfunded.
Overlooked subsidiaries that were once hidden jewels may lose their luster. The assets are really unseen or their value is obscure: Are the assets being generally ignored or has their value not been determined by knowledgeable experts? What is the history of any previous attempts to commercialize the assets?
The assets are really assets: In addition to being hidden, the assets must have a reasonable expectation of value. A focused value realization strategy: Historically, value realization activities for hidden tangible assets such as overfunded pension funds, real estate carried on the balance sheet below market value and profitable subsidiaries that have significant private market values are fairly straightforward and relatively easy to execute.
However, that is generally not the case with hidden intangible assets. Firms that have accomplished this tend to explicitly incorporate execution considerations into their strategies from the start. Operational expertise: It is not enough to have a unique and focused strategy; firms must have the people and capabilities to successfully operationalize the strategy over time.
Disney was uniquely qualified to implement such a strategy given its track-record of translating popular stories into successful motion pictures. For example, Disney became the first studio to produce a full-length animated motion picture with the release of Snow White and the Seven Dwarfs, which was an immediate and critically acclaimed success.
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