The Advanced Fixed Income and Derivatives Management Guide. Saied Simozar

2.6 Components of US yield curve for September 30, 2010

      2.7 Level of yield curve shifted by 50 bps.

      2.8 Slope of yield curve shifted by 50 bps.

      2.9 Bend of yield curve shifted by 50 bps.

      2.10 Yield curve on December 11, 2008

      2.11 Comparison of ISM manufacturing index and bend of the TSIR

      2.12 Implied historical decay coefficient

      2.13 Implied historical decay coefficient from treasury market

      3.1 Orthogonal term structure components in τ space

      3.2 Orthogonal term structure and principal components in τ space, 1992–2012

      3.3 Term structure and volatility adjusted principal components in τ space, 1992–2012

      3.4 Historical bend of the Chebyshev basis function

      4.1 Eurodollar futures contracts VBP

      4.2 Key rate contribution to duration, time space

      6.1 Term structure of swap curve, May 25, 2012

      6.2 Spread of repo and Libor over treasury bills

      7.1 Historical term structures of euro swaps

      7.2 Historical term structures of USD swaps

      7.3 AUD and NZD swap curves, May 24, 2012

      7.4 AUD and NZD instantaneous forward swap curves, May, 24, 2012

      7.5 AUD and NZD swap curves, December, 18, 2012

      8.1 Portfolio optimization example

      9.1 Selected cross-sections of relative Libor volatility, June 30, 2012

      9.2 Selected cross-sections of absolute Libor volatility, June 30, 2012

      10.1 Convexity adjusted yield curve, May 28, 1999

      10.2 Yield curve without convexity adjustment, May 28, 1999

      10.3 Convexity adjusted long zero curves

      10.4 Treasury and swap curves for calculations of EDFC, July 30, 2012

      11.1 Spot real (Rts) and nominal (Tsy) rates, July 30, 2012

      11.2 Term structure of inflation expectations, July 30, 2012

      11.3 Average monthly inflation rates

      11.4 Standard deviation of monthly inflation in the US

      11.5 Cumulative seasonal inflation adjustment for US

      11.6 Implied and market inflation rates, July 31, 2012

      12.1 Credit spread of Brazil, May 25, 2012

      12.2 Term structures of rates in France and Germany, July 31, 2012

      12.3 Contribution to partial yield

      13.1 TSCS and TSDP for Ford Motor Co., July 31, 2012

      15.1 European at-the-money call swaption, July 8, 2011

      15.2 Log-normal probability distribution

      15.3 American at-the-money call swaption, July 8, 2011

      15.4 American at-the-money put swaption, July 8, 2011

      15.5 Correlation functions

      17.1 Fraction of homes sold per year

      17.2 Natural log of mortgage factor due to incentive

      18.1 Conventional 30-year mortgage rates

      18.2 Calculation error for 30-year conventional mortgages

      18.3 Conventional 15-year mortgage rates

      20.1 Newton's optimization method

      21.1 Propagation from bucket j to bucket k

      Abbreviations

      Notation

      For notational convenience most variable names have been limited to a single character. Subscripts have been used to differentiate related variables. Subscripts i, j, and k have been used exclusively as running integers and are interchangeable. Other subscript letters are used to differentiate closely related names. For example, p_m and p_c are used for the market price and calculated price of a security, respectively. When these subscripts are mixed with running subscripts, a comma is inserted between them (e.g. p_m,i or p_c,k).

      SUBSCRIPTS

      VARIABLE NAMES

      Preface

      Fixed income management has become significantly more quantitative and competitive over the last 20 years or so, and the days where fund managers could make very large duration bets are mostly over. Most clients prefer portfolios with diversified sources of alpha and duration targets that are comparable to the risk profiles of their liabilities or their intended risk/return expectations. Developments of strategies that are quantifiable and repeatable are essential for the success of fixed income business.

      Understanding the factors that contribute to risk and return are essential, in order to structure a sound portfolio. Risk management and return attribution require the quantification of sources of risk and return and thus are math intensive. A portfolio manager who is familiar with