scholarly journals Portfolio Selection Based on Bayesian Theory

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Daping Zhao ◽  
Yong Fang ◽  
Chaoliang Zhang ◽  
Zongrun Wang
Keyword(s):  
Markov Chain ◽  
Stock Market ◽  
Portfolio Selection ◽  
Regime Switching ◽  
Numerical Experiments ◽  
Bayesian Theory ◽  
Selection Model ◽  
Portfolio Performance ◽  
State Transfer ◽  
Portfolio Selection Model

The traditional portfolio selection model seriously overestimates its theoretic optimal return. Aiming at this problem, two portfolio selection models are proposed to modify the parameters and enhance portfolio performance based on Bayesian theory. Firstly, a Bayesian-GARCH(1,1) model is built. Secondly, Markov Chain is applied to curve the parameters’ state transfer, and a Bayesian Markov regime-Switching-GARCH(1,1) model is constructed. Both the two models can handle the overestimation problem and can obtain self-financing portfolios. In the numerical experiments, both the models are examined with data from China stock market, and their performances are compared and analyzed. The results show that BMS-GARCH(1,1) model is superior to the Bayesian-GARCH(1,1) model.

scholarly journals A New Adaptive Entropy Portfolio Selection Model

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 951
Author(s):  
Ruidi Song ◽  
Yue Chan
Keyword(s):  
Portfolio Selection ◽  
Stock Exchange ◽  
Selection Model ◽  
Portfolio Performance ◽  
Entropy Model ◽  
Data Set ◽  
Entropy Measurement ◽  
Self Adaptation ◽  
Portfolio Selection Model ◽  
Mean Variance

In this paper, we propose an adaptive entropy model (AEM), which incorporates the entropy measurement and the adaptability into the conventional Markowitz’s mean-variance model (MVM). We evaluate the performance of AEM, based on several portfolio performance indicators using the five-year Shanghai Stock Exchange 50 (SSE50) index constituent stocks data set. Our outcomes show, compared with the traditional portfolio selection model, that AEM tends to make our investments more decentralized and hence helps to neutralize unsystematic risks. Due to the existence of self-adaptation, AEM turns out to be more adaptable to market fluctuations and helps to maintain the balance between the decentralized and concentrated investments in order to meet investors’ expectations. Our model applies equally well to portfolio optimizations for other financial markets.

scholarly journals Portfolio Selection with Jumps under Regime Switching

2010 ◽  
Vol 2010 ◽  
pp. 1-22 ◽  
Author(s):  
Lin Zhao
Keyword(s):  
Markov Chain ◽  
Portfolio Selection ◽  
Continuous Time ◽  
Regime Switching ◽  
Jump Processes ◽  
Bank Account ◽  
The Mean ◽  
Mean Variance Portfolio ◽  
Portfolio Selection Model ◽  
Mean Variance

We investigate a continuous-time version of the mean-variance portfolio selection model with jumps under regime switching. The portfolio selection is proposed and analyzed for a market consisting of one bank account and multiple stocks. The random regime switching is assumed to be independent of the underlying Brownian motion and jump processes. A Markov chain modulated diffusion formulation is employed to model the problem.

scholarly journals Multiperiod Telser’s Safety-First Portfolio Selection with Regime Switching

2018 ◽  
Vol 2018 ◽  
pp. 1-18
Author(s):  
Chuangwei Lin ◽  
Huiling Wu
Keyword(s):  
Markov Chain ◽  
Portfolio Selection ◽  
Optimal Strategy ◽  
Regime Switching ◽  
Risk Control ◽  
Control Level ◽  
Terminal Wealth ◽  
Lagrange Multiplier Technique ◽  
Portfolio Selection Model ◽  
Safety First

This paper investigates a multiperiod Telser’s safety-first portfolio selection model with regime switching where the returns of the assets are assumed to depend on the market states modulated by a discrete-time Markov chain. The investor aims to maximize the expected terminal wealth and does not want the probability of the terminal wealth to fall short of a disaster level to exceed a predetermined number called the risk control level. Referring to Tchebycheff inequality, we modify Telser’s safety-first model to the case that aims to maximize the expected terminal wealth subject to a constraint where the upper bound of the disaster probability is less than the risk control level. By the Lagrange multiplier technique and the embedding method, we study in detail the existence of the optimal strategy and derive the closed-form optimal strategy. Finally, by mathematical and numerical analysis, we analyze the effects of the disaster level, the risk control level, the transition matrix of the Markov chain, the expected excess return, and the variance of the risky return.

scholarly journals A CREDIBILISTIC MEAN-SEMIVARIANCE-PER PORTFOLIO SELECTION MODEL FOR LATIN AMERICA

2019 ◽  
Vol 20 (2) ◽  
pp. 225-243 ◽  
Author(s):  
Fernando García ◽  
Jairo González-Bueno ◽  
Javier Oliver ◽  
Rima Tamošiūnienė
Keyword(s):  
Portfolio Selection ◽  
Latin American ◽  
Risk Measures ◽  
Good Alternative ◽  
Selection Model ◽  
Portfolio Performance ◽  
Cardinality Constraints ◽  
Nsga Ii ◽  
Portfolio Optimization Problem ◽  
Portfolio Selection Model

Many real-world problems in the financial sector have to consider different objectives which are conflicting, for example portfolio selection. Markowitz proposed an approach to determine the optimal composition of a portfolio analysing the trade-off between return and risk. Nevertheless, this approach has been criticized for unrealistic assumptions and several changes have been proposed to incorporate investors’ constraints and more realistic risk measures. In this line of research, our proposal extends the mean-semivariance portfolio selection model to a multiobjective credibilistic model that besides risk and return, also considers the price-to-earnings ratio to measure portfolio performance. Uncertain future returns and PER ratio of each asset are approximated using L-R power fuzzy numbers. Furthermore, we consider budget, bound and cardinality constraints. To solve the constrained portfolio optimization problem, we use the algorithm NSGA-II. We assess the proposed approach generating a portfolio with shares included in the Latin American Integrated Market. Results show that this new approach is a good alternative to solve the portfolio selection problem when multiple objectives are considered.

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