Asset allocation for a DC pension fund under regime switching environment

Ralf Korn, Tak Kuen Siu, Aihua Zhang

Research output: Contribution to journalConference paperResearchpeer-review

Abstract

We consider the portfolio selection problem of a member of a defined contribution pension plan in a hidden Markov-modulated economy modulated by a continuous-time, finite-state, hidden Markov chain whose states represent different hidden states of the underlying economy. The evolution of the chain over time is not observable by the member. We consider the situation that the member aims to maximize the expected utility from terminal wealth. This utility maximization problem of the member is a stochastic optimal control problem with partial observations. We adopt the innovations approach in filtering theory to transform the problem into one with complete observations. We develop a robust filter for the hidden state of the economy and present a robust-filter-based EM algorithm for estimating the unknown parameters.

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Pension funds
Asset allocation
Regime switching
Filter
Expected utility
Utility maximization
Innovation
Stochastic optimal control
Wealth
Continuous time
Defined contribution pension plan
Markov chain
EM algorithm
Portfolio selection

Keywords

  • Defined contribution pension
  • Portfolio selection
  • Regime switching
  • Hidden Markov chain
  • Partial observations
  • Innovation approach
  • Filtering
  • EM algorithm
  • Estimation
  • Control

Cite this

@article{831cfb85353b4bb09a3c09d9ccf29161,
title = "Asset allocation for a DC pension fund under regime switching environment",
abstract = "We consider the portfolio selection problem of a member of a defined contribution pension plan in a hidden Markov-modulated economy modulated by a continuous-time, finite-state, hidden Markov chain whose states represent different hidden states of the underlying economy. The evolution of the chain over time is not observable by the member. We consider the situation that the member aims to maximize the expected utility from terminal wealth. This utility maximization problem of the member is a stochastic optimal control problem with partial observations. We adopt the innovations approach in filtering theory to transform the problem into one with complete observations. We develop a robust filter for the hidden state of the economy and present a robust-filter-based EM algorithm for estimating the unknown parameters.",
keywords = "Defined contribution pension, Portfolio selection, Regime switching, Hidden Markov chain, Partial observations, Innovation approach, Filtering, EM algorithm, Estimation, Control",
author = "Ralf Korn and Siu, {Tak Kuen} and Aihua Zhang",
year = "2011",
doi = "10.1007/s13385-011-0021-5",
language = "English",
volume = "1",
pages = "S361--S377",
journal = "European actuarial journal : Selected papers presented during the 19th IAA AFIR Colloquium in Munich, Germany, 2009",
issn = "2190-9741",
publisher = "Springer, Springer Nature",
number = "Suppl. 2",

}

Asset allocation for a DC pension fund under regime switching environment. / Korn, Ralf; Siu, Tak Kuen; Zhang, Aihua.

In: European actuarial journal : Selected papers presented during the 19th IAA AFIR Colloquium in Munich, Germany, 2009, Vol. 1, No. Suppl. 2, 2011, p. S361-S377.

Research output: Contribution to journalConference paperResearchpeer-review

TY - JOUR

T1 - Asset allocation for a DC pension fund under regime switching environment

AU - Korn, Ralf

AU - Siu, Tak Kuen

AU - Zhang, Aihua

PY - 2011

Y1 - 2011

N2 - We consider the portfolio selection problem of a member of a defined contribution pension plan in a hidden Markov-modulated economy modulated by a continuous-time, finite-state, hidden Markov chain whose states represent different hidden states of the underlying economy. The evolution of the chain over time is not observable by the member. We consider the situation that the member aims to maximize the expected utility from terminal wealth. This utility maximization problem of the member is a stochastic optimal control problem with partial observations. We adopt the innovations approach in filtering theory to transform the problem into one with complete observations. We develop a robust filter for the hidden state of the economy and present a robust-filter-based EM algorithm for estimating the unknown parameters.

AB - We consider the portfolio selection problem of a member of a defined contribution pension plan in a hidden Markov-modulated economy modulated by a continuous-time, finite-state, hidden Markov chain whose states represent different hidden states of the underlying economy. The evolution of the chain over time is not observable by the member. We consider the situation that the member aims to maximize the expected utility from terminal wealth. This utility maximization problem of the member is a stochastic optimal control problem with partial observations. We adopt the innovations approach in filtering theory to transform the problem into one with complete observations. We develop a robust filter for the hidden state of the economy and present a robust-filter-based EM algorithm for estimating the unknown parameters.

KW - Defined contribution pension

KW - Portfolio selection

KW - Regime switching

KW - Hidden Markov chain

KW - Partial observations

KW - Innovation approach

KW - Filtering

KW - EM algorithm

KW - Estimation

KW - Control

U2 - 10.1007/s13385-011-0021-5

DO - 10.1007/s13385-011-0021-5

M3 - Conference paper

VL - 1

SP - S361-S377

JO - European actuarial journal : Selected papers presented during the 19th IAA AFIR Colloquium in Munich, Germany, 2009

T2 - European actuarial journal : Selected papers presented during the 19th IAA AFIR Colloquium in Munich, Germany, 2009

JF - European actuarial journal : Selected papers presented during the 19th IAA AFIR Colloquium in Munich, Germany, 2009

SN - 2190-9741

IS - Suppl. 2

ER -