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This study introduces a dynamic investment framework to enhance portfolio management in volatile markets, offering clear advantages over traditional static strategies. Evaluates four conventional approaches : equal weighted, minimum…

Portfolio Management · Quantitative Finance 2025-04-07 Jinhui Li , Wenjia Xie , Luis Seco

This paper studies a continuous-time market {under stochastic environment} where an agent, having specified an investment horizon and a target terminal mean return, seeks to minimize the variance of the return with multiple stocks and a…

Portfolio Management · Quantitative Finance 2013-02-28 Wan-Kai Pang , Yuan-Hua Ni , Xun Li , Ka-Fai Cedric Yiu

We consider a time-consistent mean-variance portfolio selection problem of an insurer and allow for the incorporation of basis (mortality) risk. The optimal solution is identified with a Nash subgame perfect equilibrium. We characterize an…

Portfolio Management · Quantitative Finance 2019-08-16 Frank Bosserhoff , Mitja Stadje

This paper studies a robust continuous-time Markowitz portfolio selection pro\-blem where the model uncertainty carries on the covariance matrix of multiple risky assets. This problem is formulated into a min-max mean-variance problem over…

Portfolio Management · Quantitative Finance 2017-03-14 Amine Ismail , Huyên Pham

The underlying market trends that drive stock price fluctuations are often referred to in terms of bull and bear markets. Optimal stock portfolio selection methods need to take into account these market trends; however, the bull and bear…

Methodology · Statistics 2024-06-05 Reetam Majumder , Qing Ji , Nagaraj K. Neerchal

We study continuous-time portfolio selection under monotone mean-variance (MMV) preferences in a jump-diffusion model, presenting an explicit solution different from that under classical mean-variance (MV) preferences in dynamic settings…

Mathematical Finance · Quantitative Finance 2024-05-14 Yuchen Li , Zongxia Liang , Shunzhi Pang

Jump stochastic volatility models are central to financial econometrics for volatility forecasting, portfolio risk management, and derivatives pricing. Markov Chain Monte Carlo (MCMC) algorithms are computationally unfeasible for the…

Applications · Statistics 2016-11-01 Eric Jacquier , Nicholas Polson , Vadim Sokolov

This study considers an optimal reinsurance, investment, and dividend strategy control problem for insurance companies in a regulated Markov regime-switching environment, intending to maximize long-run average reward. Unlike existing single…

Optimization and Control · Mathematics 2025-12-18 Lingjia Zeng , Manman Li

This paper explores the mean-variance portfolio selection problem in a multi-period financial market characterized by regime-switching dynamics and uncontrollable liabilities. To address the uncertainty in the decision-making process within…

Optimization and Control · Mathematics 2025-09-04 Zhongqin Gao , Ping Chen , Xun Li , Yan Lv , Wenhao Zhang

This paper studies the continuous time mean-variance portfolio selection problem with one kind of non-linear wealth dynamics. To deal the expectation constraint, an auxiliary stochastic control problem is firstly solved by two new…

Mathematical Finance · Quantitative Finance 2022-11-03 Shaolin Ji , Hanqing Jin , Xiaomin Shi

Multi-period mean-variance optimization is a long-standing problem, caused by the failure of dynamic programming principle. This paper studies the mean-variance optimization in a setting of finite-horizon discrete-time Markov decision…

Optimization and Control · Mathematics 2025-07-31 Li Xia , Zhihui Yu

This paper studies a variation of the continuous-time mean-variance portfolio selection where a tracking-error penalization is added to the mean-variance criterion. The tracking error term penalizes the distance between the allocation…

Computational Finance · Quantitative Finance 2020-09-21 William Lefebvre , Gregoire Loeper , Huyên Pham

The financial crisis of 2008 generated interest in more transparent, rules-based strategies for portfolio construction, with Smart beta strategies emerging as a trend among institutional investors. While they perform well in the long run,…

Computational Engineering, Finance, and Science · Computer Science 2019-03-01 Elizabeth Fons , Paula Dawson , Jeffrey Yau , Xiao-jun Zeng , John Keane

This paper is devoted to study the effects arising from imposing a value-at-risk (VaR) constraint in mean-variance portfolio selection problem for an investor who receives a stochastic cash flow which he/she must then invest in a…

Portfolio Management · Quantitative Finance 2010-11-24 Jun Ye , Tiantian Li

We consider the problem of maximizing expected utility for a power investor who can allocate his wealth in a stock, a defaultable security, and a money market account. The dynamics of these security prices are governed by geometric Brownian…

Portfolio Management · Quantitative Finance 2014-06-04 Agostino Capponi , Jose Enrique Figueroa Lopez , Andrea Pascucci

We consider the problem of selecting a portfolio of assets that provides the investor a suitable balance of expected return and risk. With respect to the seminal mean-variance model of Markowitz, we consider additional constraints on the…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Andrea Schaerf

When we implement a portfolio selection methodology under a mean-risk formulation, it is essential to correctly model investors' risk aversion which may be time-dependent, or even state-dependent during the investment procedure. In this…

Portfolio Management · Quantitative Finance 2015-08-04 Xiangyu Cui , Xun Li , Duan Li , Yun Shi

We investigate discrete-time mean-variance portfolio selection problems viewed as a Markov decision process. We transform the problems into a new model with deterministic transition function for which the Bellman optimality equation holds.…

Optimization and Control · Mathematics 2025-09-23 Nicole Bäuerle , Anna Jaśkiewicz

The portfolio optimisation problem, first raised by Harry Markowitz in 1952, has been a fundamental and central topic to understanding the stock market and making decisions. There has been plenty of works contributing to development of the…

Portfolio Management · Quantitative Finance 2019-07-09 Xiang Meng

This paper develops a new deep learning algorithm to solve a class of finite-horizon mean-field games. The proposed hybrid algorithm uses Markov chain approximation method combined with a stochastic approximation-based iterative deep…

Optimization and Control · Mathematics 2024-12-12 Yu Zhang , Zhuo Jin , Jiaqin Wei , George Yin