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A good working knowledge of the three bond measures de ned can aid the investment manager analyst in the evaluation of xed income managers, but the body of knowledge needed to properly assess xed income managers and put their track records and investment processes in perspective is far more expansive As the previous section states, this book is not a tutorial on the assets classes reviewed within Instead, it is assumed that the reader has the basic knowledge to understand the securities discussed In this section, we are discussing bonds, so I make the assumption that you, the reader, already possess a basic understanding of xed income instruments While the underlying fundamental characteristics may be different, the formulas, methods and analytical techniques remain the same When analyzing a xed income portfolio, we look to see if the portfolio is concentrated in any broad categories, such as investment type (US.

On September 23, senior of cers of 16 banks and brokerage rms met at the Fed s headquarters in New York At the end of the day (having rejected an interim offer from Buffett, allied with American International Group and Goldman Sachs), Meriwether and LTCM accepted the buyout offer that came from 14 of the institutions represented at the Fed s of ces $36 billion in exchange for 90% of LTCM s assets This left the old investors with about $400 million, less than onetenth of the value of their assets at the beginning of 1998 Effective control of the rm was turned over to a six-man oversight committee composed of managers put in place by Merrill Lynch, Salomon Smith Barney, JP Morgan, UBS, Morgan Stanley, and Goldman Sachs The oversight committee identi ed LTCM s biggest problems to be its UK swaps and its equity options.

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Treasuries, corporate bonds, investment-grade bonds, non-investment-grade bonds, etc) When looking at a portfolio s duration, it is important to assess the underlying risk based on our initial risk assumptions and, if appropriate, compared to some benchmark For example, a xed income portfolio with a signi cantly higher exposure to zero-coupon bonds than its peers or relevant benchmarks should be viewed as potentially carrying with it heightened interest rate risk Contrast that portfolio example with a portfolio of high-grade corporate and Treasury bonds with maturities on a par with the rst example Assuming no derivatives are being used to hedge out interest rate risk, the second portfolio would likely exhibit less interest rate risk.

5 6 7 8 9

line having C -paths and satisfying the nondegeneracy condition Var(X(t)) > 0 for every t [0, T ], all the moments of crossings of any level are nite Rice formulas for random elds are considered in 6 Proofs are new and self-contained except for the aforementioned co-area formula In all cases, formulas for the moments of weighted (or marked ) crossings are stated and proved They are used in the sequel for various applications and, moreover, are important by themselves 4 consists of two parts In Sections 41 to 43, X is a Gaussian process de ned on a bounded interval of the real line, and some initial estimates for P(M > u) are given, based on computations of the rst two moments of the number of crossings In Sections 44 and 4.

LTCM had huge positions in both strategies The committee arranged for regular public auctions to unwind the positions gradually It also continued to consolidate the offsetting sides of LTCM s trades by pairing up the counterparties and.

5, two statistical applications are considered: the rst to genomics and the second to statistical inference on mixtures of populations The common feature of these two applications is that the relevant statistic for hypothesis testing is the maximum of a certain Gaussian process, so that the calculation of its distribution appears to be naturally related to the methods in the earlier sections 5 establishes a bridge between the distribution of the maximum on an interval of a one-parameter process and the factorial moments of up-crossings of the paths The main result is the general formula (52), which expresses the tail of the distribution of the maximum as the sum of a series (the Rice series) de ned in terms of certain factorial moments of the up-crossings of the given process.

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