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Journal ArticleDOI

Mean-absolute deviation portfolio optimization for mortgage-backed securities

Stavros A. Zenios, +1 more
- 01 Dec 1993 - 
- Vol. 45, Iss: 1, pp 433-450
TLDR
An integrated simulation/optimization model for managing portfolios of mortgage-backed securities using amean-absolute deviation model which is consistent with the asymmetric distribution of returns of mortgage securities and derivative products is developed.
Abstract
We develop an integrated simulation/optimization model for managing portfolios of mortgage-backed securities. The mortgage portfolio problem is viewed in the same spirit of models used for the management of portfolios of equities. That is, it trades off rates of return with a suitable measure of risk. In this respect we employ amean-absolute deviation model which is consistent with the asymmetric distribution of returns of mortgage securities and derivative products. We develop a simulation procedure to compute holding period returns of the mortgage securities under a range of interest rate scenarios. The simulation explicitly takes into account the stylized facts of mortgage securities: the propensity of homeowners to prepay their mortgages, and theoption adjusted premia associated with these securities. Details of both the simulation and optimization models are presented. The model is then applied to the funding of a typical insurance liability stream, and it is shown to generate superior results than the standardportfolio immunization approach.

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Citations
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From stochastic dominance to mean-risk models: Semideviations as risk measures

TL;DR: It is shown that the standard semideviation (square root of the semivariance) as the risk measure makes the mean-risk model consistent with the second degree stochastic dominance, provided that the trade-off coefficient is bounded by a certain constant.
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Markowitz Revisited: Mean-Variance Models in Financial Portfolio Analysis

TL;DR: The interplay between objective and constraints in a number of single-period variants, including semivariance models are described, revealing the possibility of removing surplus money in future decisions, yielding approximate downside risk minimization.
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Heuristic algorithms for the portfolio selection problem with minimum transaction lots

TL;DR: This paper shows that in this case the problem of finding a feasible solution to the portfolio problem with minimum transaction lots is NP-complete, independently of the risk function.
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Twenty years of linear programming based portfolio optimization

TL;DR: This paper reviews the variety of LP solvable portfolio optimization models presented in the literature, the real features that have been modeled and the solution approaches to the resulting models, in most of the cases mixed integer linear programming (MILP) models.
References
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Journal ArticleDOI

A Theory of the Term Structure of Interest Rates.

TL;DR: In this paper, the authors use an intertemporal general equilibrium asset pricing model to study the term structure of interest rates and find that anticipations, risk aversion, investment alternatives, and preferences about the timing of consumption all play a role in determining bond prices.
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Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market

TL;DR: In this article, a portfolio optimization model using the L1 risk (mean absolute deviation risk) function can remove most of the difficulties associated with the classical Markowitz's model while maintaining its advantages over equilibrium models.
Journal ArticleDOI

A One-Factor Model of Interest Rates and Its Application to Treasury Bond Options

TL;DR: In this article, a one-factor model of interest rates and its application to Treasury bond options is presented, with a focus on the use of options as an alternative to bonds.
Journal ArticleDOI

Prepayment and the Valuation of Mortgage-Backed Securities

TL;DR: In this article, the authors put forward a valuation framework for mortgage-backed securities consistent with these stylized facts associated with mortgage prepayments, but they do not impose an optimal, value-minimizing call condition to price these securities.
Journal ArticleDOI

Mean-Absolute-Deviation Characteristic Lines for Securities and Portfolios

TL;DR: In this paper, the authors presented a new algorithm for minimizing the sum of the absolute deviations of a security portfolio rather than the squared deviations around the characteristic line of the portfolio, which produces useful information as a byproduct of the solution process.