Bond Ladders and Optimal Portfolios (original) (raw)
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This paper describes a new method of bond portfolio optimization based on stochastic string models of correlation structure in bond returns. The paper shows how to approximate correlation function of bond returns, compute the optimal portfolio allocation using Wiener-Hopf factorization, and check whether a collection of bonds presents arbitrage opportunities.
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Canadian Parliamentary Review, 2007
Hence, the endowment process is characterized by a parameter vector φx,φv,θx,θv,σv . There is a representative agent with EpsteinZin preferences. The advantages of this preference structure, with its property of separating relative risk aversion from the elasticity of intertemporal substitution, are well known. The preference parameter vector is β,ρ,α . The pricing kernel is the intertemporal marginal rate of substitution in consumption, denoted log mt+1 . The price of default-free discount bonds can be determined recursively through an arbitrage-free restriction of the form
The Bond Risk Premium and the Cross-Section of Equity Returns
2008
Abstract The cross-section of returns of stock portfolios sorted along the book-to-market dimension can be understood with a one-factor model. The factor is the nominal bond risk premium, best measured as the Cochrane-Piazzesi (2005, CP) factor. This paper ties the pricing of stocks in the cross-section to the pricing of bonds of various maturities, two literatures that have been developed largely in isolation. A parsimonious stochastic discount factor model can price both the cross-section of stock and bond returns.