scholarly journals Optimal Portfolio Strategy with Discounted Stochastic Cash Inflows When the Stock Price Is a Semimartingale

2016 ◽  
Vol 06 (04) ◽  
pp. 660-684
Author(s):  
Onthusitse Baraedi ◽  
Elias Offen
Keyword(s):  
Stock Price ◽  
Optimal Portfolio ◽  
Portfolio Strategy

scholarly journals Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
Hui-qiang Ma
Keyword(s):  
Portfolio Selection ◽  
Continuous Time ◽  
Stock Price ◽  
Efficient Frontier ◽  
Optimal Portfolio ◽  
Portfolio Strategy ◽  
Cev Process ◽  
The Mean ◽  
Mean Variance Portfolio ◽  
Mean Variance

We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.

Taming Large Events: Optimal Portfolio Theory for Strongly Fluctuating Assets

1998 ◽  
Vol 01 (01) ◽  
pp. 25-41 ◽  
Author(s):  
J. P. Bouchaud ◽  
D. Sornette ◽  
C. Walter ◽  
J. P. Aguilar
Keyword(s):  
Asset Allocation ◽  
Value At Risk ◽  
Stock Price ◽  
Power Laws ◽  
Optimal Portfolio ◽  
Fat Tails ◽  
Financial Activity ◽  
Explicit Formulae ◽  
Asset Allocations ◽  
Different Parts

We propose a method of optimization of asset allocation in the case where the stock price variations are supposed to have "fat" tails represented by power laws. Generalizing over previous works using stable Lévy distributions, we distinguish three distinct components of risk described by three different parts of the distributions of price variations: unexpected gains (to be kept), harmless noise inherent to financial activity, and unpleasant losses, which is the only component one would like to minimize. The independent treatment of the tails of distributions for positive and negative variations and the generalization to large events of the notion of covariance of two random variables provide explicit formulae for the optimal portfolio. The use of the probability of loss (or equivalently the Value-at-Risk), as the key quantity to study and minimize, provides a simple solution to the problem of optimization of asset allocations in the general case where the characteristic exponents are different for each asset.

scholarly journals Desain Portofolio Optimal untuk Keputusan Investasi pada Fase Krisis Keuangan

2017 ◽  
Vol 16 (1) ◽  
pp. 68
Author(s):  
Deddy Saptomo ◽  
Insannul Kamil ◽  
Elita Amrina ◽  
Mego Plamonia
Keyword(s):  
Stock Price ◽  
Global Financial Crisis ◽  
Stock Exchange ◽  
Optimal Portfolio ◽  
Arbitrage Pricing Theory ◽  
Expected Return ◽  
Macroeconomic Factors ◽  
The Us ◽  
Pricing Theory ◽  
The Global Financial Crisis

This research aims to design optimal portfolio with a case study of stocks listed on the Indonesia Stock Exchange (IDX) that conduct transactions in the period 2011-2015. The sample used were 396 companies listed on nine sectors in BEI. Arbitrage Pricing Theory (APT) method is used to determine the realized return, expected return, and efficient portfolio involving four macroeconomic factors (Stock Price Index (IHSG), interest rate of Indonesian Bank Certificates (SBI), Inflation and Exchange Rate of Rupiah against the US Dollar). Efficient portfolio is formed by 231 undervalued companies. While the optimal portfolio with the Excess Return to Beta (ERB) approach was formed by 42 companies with a ERB value greater than (or equal to) cut-off point (0,1912). Under the uncertainty of the investment climate due to the global financial crisis, the decision to make investments needs to be done carefully and consider various factors, including macroeconomic factors. This research has succeeded in designing an optimal portfolio that can be a guide for investors to determine investment decisions.

Optimal portfolio in the presence of transaction costs and convex risk measure

2017 ◽  
Vol 04 (04) ◽  
pp. 1750041
Author(s):  
O. Doctor ◽  
E. R. Offen ◽  
E. M. Lungu
Keyword(s):  
Transaction Costs ◽  
Stock Price ◽  
Risk Measure ◽  
Optimal Portfolio ◽  
Relative Risk Aversion ◽  
Convex Risk Measure ◽  
Geometric Process ◽  
Optimal Portfolio Selection ◽  
Hamilton Jacobi Bellman ◽  
Zero Sum

We analyze the optimal portfolio selection problem of maximizing the utility of an agent who invests in a stock and a money market account in the presence of transaction costs. The stock price follows a geometric process. The preference of the investor is assumed to follow the constant relative risk aversion (CRRA). We further investigate the risk minimizing portfolio through a zero-sum stochastic differential game (SDG). To solve this two-player SDG we use the Hamilton–Jacobi–Bellman–Isaacs (HJBI) for general zero-sum SDG in a jump setting.

scholarly journals Portfolio optimization under mean-CVaR simulation with copulas on the Vietnamese stock exchange

2021 ◽  
Vol 18 (2) ◽  
pp. 273-286
Author(s):  
Le Tuan Anh ◽  
Dao Thi Thanh Binh
Keyword(s):  
Stock Market ◽  
Portfolio Optimization ◽  
Stock Exchange ◽  
Optimal Portfolio ◽  
Gaussian Copula ◽  
Optimal Portfolios ◽  
Empirical Results ◽  
Portfolio Strategy ◽  
T Copula ◽  
Mean Variance

This paper studies how to construct and compare various optimal portfolio frameworks for investors in the context of the Vietnamese stock market. The aim of the study is to help investors to find solutions for constructing an optimal portfolio strategy using modern investment frameworks in the Vietnamese stock market. The study contains a census of the top 43 companies listed on the Ho Chi Minh stock exchange (HOSE) over the ten-year period from July 2010 to January 2021. Optimal portfolios are constructed using Mean-Variance Framework, Mean-CVaR Framework under different copula simulations. Two-thirds of the data from 26/03/2014 to 27/1/2021 consists of the data of Vietnamese stocks during the COVID-19 recession, which caused depression globally; however, the results obtained during this period still provide a consistent outcome with the results for other periods. Furthermore, by randomly attempting different stocks in the research sample, the results also perform the same outcome as previous analyses. At about the same CvaR level of about 2.1%, for example, the Gaussian copula portfolio has daily Mean Return of 0.121%, the t copula portfolio has 0.12% Mean Return, while Mean-CvaR with the Raw Return portfolio has a lower Return at 0.103%, and the last portfolio of Mean-Variance with Raw Return has 0.102% Mean Return. Empirical results for all 10 portfolio levels showed that CVaR copula simulations significantly outperform the historical Mean-CVaR framework and Mean-Variance framework in the context of the Vietnamese stock exchange.

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