Optimal portfolio trading subject to stochastic dominance constraints under second‐order autoregressive price dynamics

This paper studies the optimal portfolio trading problem under the generalized second‐order autoregressive execution price model. The problem of minimizing expected execution cost under the proposed price model is formulated as a quadratic programming (QP) problem. For a risk‐averse trader, problem...

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Published inInternational transactions in operational research Vol. 27; no. 3; pp. 1771 - 1803
Main Authors Singh, Arti, Dharmaraja, Selvamuthu
Format Journal Article
LanguageEnglish
Published Oxford Blackwell Publishing Ltd 01.05.2020
Subjects
autoregressive behavior
Autoregressive models
Computational geometry
Constraints
convex programming
Convexity
Economic models
execution cost
Mathematical programming
Mutual funds
Operations research
optimal trading
Optimization
Quadratic programming
Risk
risk aversion
stochastic dominance
Online AccessGet full text
ISSN0969-6016
1475-3995
DOI10.1111/itor.12435

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Abstract This paper studies the optimal portfolio trading problem under the generalized second‐order autoregressive execution price model. The problem of minimizing expected execution cost under the proposed price model is formulated as a quadratic programming (QP) problem. For a risk‐averse trader, problem formulation under the second‐order stochastic dominance constraints results in a quadratically constrained QP problem. Under some conditions on the execution price model, it is proved that the portfolio trading problems for risk‐neutral and risk‐averse traders become convex programming problems, which have many theoretical and computational advantages over the general class of optimization problems. Extensive numerical illustrations are provided, which render the practical significance of the proposed execution price model and the portfolio trading problems.
AbstractList This paper studies the optimal portfolio trading problem under the generalized second‐order autoregressive execution price model. The problem of minimizing expected execution cost under the proposed price model is formulated as a quadratic programming (QP) problem. For a risk‐averse trader, problem formulation under the second‐order stochastic dominance constraints results in a quadratically constrained QP problem. Under some conditions on the execution price model, it is proved that the portfolio trading problems for risk‐neutral and risk‐averse traders become convex programming problems, which have many theoretical and computational advantages over the general class of optimization problems. Extensive numerical illustrations are provided, which render the practical significance of the proposed execution price model and the portfolio trading problems.
Author Singh, Arti
Dharmaraja, Selvamuthu
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CitedBy_id crossref_primary_10_1111_itor_12629
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crossref_primary_10_1007_s10898_021_01113_z
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10.1016/S1386-4181(97)00012-8
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Snippet This paper studies the optimal portfolio trading problem under the generalized second‐order autoregressive execution price model. The problem of minimizing...
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SubjectTerms autoregressive behavior
Autoregressive models
Computational geometry
Constraints
convex programming
Convexity
Economic models
execution cost
Mathematical programming
Mutual funds
Operations research
optimal trading
Optimization
Quadratic programming
Risk
risk aversion
stochastic dominance
Title Optimal portfolio trading subject to stochastic dominance constraints under second‐order autoregressive price dynamics
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