Optimal Investment Strategy for DC Pension Plan with Deposit Loan Spread under the CEV Model

Wang, Yang; Xiaoli, Xu; Zhang, Jizhou

doi:10.3390/axioms11080382

Cited by 2 publications

(1 citation statement)

References 44 publications

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“…We face this stochastic control problem using dynamic programming. This approach is standard in applications of Economics and Finance (see, e.g., [15]). For the stochastic optimal control problem ( 4) and ( 5), the value function has the following form:…”

Section: The Hjb Equation and The Evolution Of M Tmentioning

confidence: 99%

A Binary-State Continuous-Time Markov Chain Model for Offshoring and Reshoring

Brambilla,

Grosset,

Sartori

2024

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We present a two-country model (North and South) that describes the phenomenon of offshoring and reshoring. The model is a continuous time-controlled Markov chain with binary states. The main trade-off involves production costs and transaction costs between one country and another. In the first part of this paper, we identify the key parameters of the model: the difference in unit production costs between the two countries considered, the marginal cost of transitioning between countries, and the incentive paid by the North country to all companies that have not relocated at the end of the planning interval. The final goal of our paper is to understand how national tax incentives can influence this process.

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Section: The Hjb Equation and The Evolution Of M Tmentioning

confidence: 99%

A Binary-State Continuous-Time Markov Chain Model for Offshoring and Reshoring

Brambilla,

Grosset,

Sartori

2024

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Optimal Investment Strategy for DC Pension Plan with Stochastic Salary and Value at Risk Constraint in Stochastic Volatility Model

Liu,

Zhang,

Wang

et al. 2024

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This paper studies the optimal asset allocation problem of a defined contribution (DC) pension plan with a stochastic salary and value under a constraint within a stochastic volatility model. It is assumed that the financial market contains a risk-free asset and a risky asset whose price process satisfies the Stein–Stein stochastic volatility model. To comply with regulatory standards and offer a risk management tool, we integrate the dynamic versions of Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and worst-case CVaR (wcCVaR) constraints into the DC pension fund management model. The salary is assumed to be stochastic and characterized by geometric Brownian motion. In the dynamic setting, a CVaR/wcCVaR constraint is equivalent to a VaR constraint under a higher confidence level. By using the Lagrange multiplier method and the dynamic programming method to maximize the constant absolute risk aversion (CARA) utility of terminal wealth, we obtain closed-form expressions of optimal investment strategies with and without a VaR constraint. Several numerical examples are provided to illustrate the impact of a dynamic VaR/CVaR/wcCVaR constraint and other parameters on the optimal strategy.

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Optimal Investment Strategy for DC Pension Plan with Deposit Loan Spread under the CEV Model

Cited by 2 publications

References 44 publications

A Binary-State Continuous-Time Markov Chain Model for Offshoring and Reshoring

A Binary-State Continuous-Time Markov Chain Model for Offshoring and Reshoring

Optimal Investment Strategy for DC Pension Plan with Stochastic Salary and Value at Risk Constraint in Stochastic Volatility Model

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