scholarly journals Optimal Portfolios for Different Anticipating Integrals under Insider Information

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 75
Author(s):  
Carlos Escudero ◽  
Sandra Ranilla-Cortina
Keyword(s):  
Portfolio Optimization ◽  
Financial Market ◽  
Investment Strategy ◽  
Stochastic Calculus ◽  
Optimal Portfolio ◽  
Simple Problem ◽  
Optimal Portfolios ◽  
Insider Information ◽  
Anticipating Stochastic Calculus ◽  
Potential Use

We consider the non-adapted version of a simple problem of portfolio optimization in a financial market that results from the presence of insider information. We analyze it via anticipating stochastic calculus and compare the results obtained by means of the Russo-Vallois forward, the Ayed-Kuo, and the Hitsuda-Skorokhod integrals. We compute the optimal portfolio for each of these cases with the aim of establishing a comparison between these integrals in order to clarify their potential use in this type of problem. Our results give a partial indication that, while the forward integral yields a portfolio that is financially meaningful, the Ayed-Kuo and the Hitsuda-Skorokhod integrals do not provide an appropriate investment strategy for this problem.

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.

OPTIMAL LOGARITHMIC UTILITY AND OPTIMAL PORTFOLIOS FOR AN INSIDER IN A STOCHASTIC VOLATILITY MARKET

2005 ◽  
Vol 08 (03) ◽  
pp. 301-319 ◽  
Author(s):  
CHRISTIAN-OLIVER EWALD
Keyword(s):  
Portfolio Optimization ◽  
Stochastic Volatility ◽  
Incomplete Markets ◽  
Insider Trading ◽  
Malliavin Calculus ◽  
Optimal Portfolio ◽  
Stochastic Volatility Model ◽  
Heston Model ◽  
Optimal Portfolios ◽  
Volatility Model

We combine methods for portfolio optimization in incomplete markets which are due to Karatzas et al. [6] with methods proposed by Nualart based on Malliavin Calculus to model insider trading within a stochastic volatility model. We compute the optimal portfolio within a certain set of insider strategies for a general stochastic volatility model but also apply the methods to explicit examples. We further discuss how the Heston model fits into this context.

scholarly journals Portfolio Optimization under Correlation Constraint

Risks ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 15
Author(s):  
Aditya Maheshwari ◽  
Traian A. Pirvu
Keyword(s):  
Portfolio Optimization ◽  
Financial Market ◽  
Lower Risk ◽  
Time Horizon ◽  
Optimal Portfolio ◽  
Exponential Utility ◽  
Portfolio Strategies ◽  
Utility Loss ◽  
The Cost ◽  
Analytical Expressions

We consider the problem of portfolio optimization with a correlation constraint. The framework is the multi-period stochastic financial market setting with one tradable stock, stochastic income, and a non-tradable index. The correlation constraint is imposed on the portfolio and the non-tradable index at some benchmark time horizon. The goal is to maximize a portofolio’s expected exponential utility subject to the correlation constraint. Two types of optimal portfolio strategies are considered: the subgame perfect and the precommitment ones. We find analytical expressions for the constrained subgame perfect (CSGP) and the constrained precommitment (CPC) portfolio strategies. Both these portfolio strategies yield significantly lower risk when compared to the unconstrained setting, at the cost of a small utility loss. The performance of the CSGP and CPC portfolio strategies is similar.

scholarly journals Inclusão de Custos de Transação Não-Lineares na Otimização Média-Variância

2005 ◽  
Vol 3 (2) ◽  
pp. 195
Author(s):  
José Euclides De Melo Ferraz ◽  
Christian Johannes Zimmer
Keyword(s):  
Approximation Algorithm ◽  
Transaction Costs ◽  
Portfolio Optimization ◽  
Financial Market ◽  
Optimal Portfolio ◽  
Market Impact ◽  
Market Data ◽  
Bid Ask Spread ◽  
Mean Variance Portfolio ◽  
Mean Variance

In this article we propose a new way to include transaction costs into a mean-variance portfolio optimization. We consider brokerage fees, bid/ask spread and the market impact of the trade. A pragmatic algorithm is proposed, which approximates the optimal portfolio, and we can show that is converges in the absence of restrictions. Using Brazilian financial market data we compare our approximation algorithm with the results of a non-linear optimizer.

scholarly journals Optimal portfolios for the DC pension fund with mispricing under the HARA utility framework

2022 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Zilan Liu ◽  
Yijun Wang ◽  
Ya Huang ◽  
Jieming Zhou
Keyword(s):  
Financial Market ◽  
Pension Fund ◽  
Absolute Risk ◽  
Optimal Portfolio ◽  
Programming Approach ◽  
Defined Contribution ◽  
Optimal Portfolios ◽  
Fund Managers ◽  
Dynamic Programming Approach ◽  
Hara Utility

<p style='text-indent:20px;'>This paper studies the optimal portfolio selection for defined contribution (DC) pension fund with mispricing. We adopt the general hyperbolic absolute risk averse (HARA) utility to describe the risk performance of the pension fund managers. The financial market comprises a risk-free asset, a pair of mispriced stocks, and the market index. Using the dynamic programming approach, we construct the Hamilton-Jacobi-Bellman (HJB) equation and obtain the explicit expressions for optimal portfolio choices with two methods. Finally, numerical analysis is presented to illustrate the sensitivity of the optimal portfolios to parameters of the financial market and contribution process. <b>200</b> words.</p>

scholarly journals Closed-Loop Equilibrium Reinsurance-Investment Strategy with Insider Information and Default Risk

2021 ◽  
Vol 2021 ◽  
pp. 1-32
Author(s):  
Peng Yang
Keyword(s):  
Financial Market ◽  
Default Risk ◽  
Closed Loop ◽  
Investment Strategy ◽  
Model Parameters ◽  
Hjb Equations ◽  
Loop Control ◽  
Insider Information ◽  
Control Approach ◽  
Terminal Wealth

This paper studies the closed-loop equilibrium reinsurance-investment problem with insider information and default risk. The financial market consists of one risky asset, one defaultable bond, and one risk-free asset. The surplus process is governed by a jump-diffusion process. Two kinds of dependencies between the insurance market and the financial market are considered. In addition, the insurer has some extra claims information available from the beginning of the trading interval. The objective of the insurer is to choose a time-consistent reinsurance-investment strategy so as to maximize the expected terminal wealth while minimizing the variance of the terminal wealth. Since this problem is time-inconsistent, using closed-loop control approach from the perspective of game theory, we establish the extended Hamilton–Jacobi–Bellman (HJB) equations for the postdefault case and the predefault case, respectively. Closed-form solutions for the closed-loop equilibrium reinsurance-investment strategy and the corresponding value function are obtained. Finally, we provide a series of numerical examples to illustrate the effects of insider information and other some important model parameters on the closed-loop equilibrium reinsurance and investment strategies. The result analyses reveal some interesting phenomena and provide useful guidances for reinsurance and investment in reality.

scholarly journals Optimal portfolio of an investor in a financial market

2021 ◽  
Vol 1734 ◽  
pp. 012050
Author(s):  
Celestine Achudume ◽  
Olabisi O. Ugbebor
Keyword(s):  
Financial Market ◽  
Optimal Portfolio

scholarly journals PENDEKATAN METODE MARKOWITZ UNTUK OPTIMALISASI PORTOFOLIO DENGAN RISIKO EXPECTED SHORTFALL (ES) PADA SAHAM SYARIAH DILENGKAPI GUI MATLAB

2022 ◽  
Vol 10 (4) ◽  
pp. 508-517
Author(s):  
Umiyatun Muthohiroh ◽  
Rita Rahmawati ◽  
Dwi Ispriyanti
Keyword(s):  
At Risk ◽  
Risk Analysis ◽  
Confidence Level ◽  
Value At Risk ◽  
Expected Shortfall ◽  
Optimal Portfolio ◽  
Optimal Portfolios

A portfolio is a combination of two or more securities as investment targets for a certain period of time with certain conditions. The Markowitz method is a method that emphasizes efforts to maximize return expectations and can minimize stock risk. One method that can be used to measure risk is Expected Shortfall (ES). ES is an expected measure of risk whose value is above Value-at-Risk (VaR). To make it easier to calculate optimal portfolios with the Markowitz method and risk analysis with ES, an application was made using the Matlab GUI. The data used in this study consisted of three JII stocks including CPIN, CTRA, and BSDE stocks. The results of the portfolio formation with the Markowitz method obtained an optimal portfolio, namely the combination of CPIN = 34.7% and BSDE = 65.3% stocks. At the 95% confidence level, the ES value of 0.206727 is greater than the VaR value (0.15512).  

Risk Budgeted Portfolio Optimization Using an Extended Ant Colony Optimization Metaheuristic

2012 ◽  
Vol 3 (4) ◽  
pp. 25-42 ◽  
Author(s):  
G. A. Vijayalakshmi Pai
Keyword(s):  
Ant Colony Optimization ◽  
Portfolio Optimization ◽  
Stock Exchange ◽  
Experimental Studies ◽  
Optimization Methods ◽  
Investment Strategy ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Data Set ◽  
Exchange Data

Risk Budgeted portfolio optimization problem centering on the twin objectives of maximizing expected portfolio return and minimizing portfolio risk and incorporating the risk budgeting investment strategy, turns complex for direct solving by classical methods triggering the need to look for metaheuristic solutions. This work explores the application of an extended Ant Colony Optimization algorithm that borrows concepts from evolution theory, for the solution of the problem and proceeds to compare the experimental results with those obtained by two other Metaheuristic optimization methods belonging to two different genres viz., Evolution Strategy with Hall of Fame and Differential Evolution, obtained in an earlier investigation. The experimental studies have been undertaken over Bombay Stock Exchange data set (BSE200: July 2001-July 2006) and Tokyo Stock Exchange data set (Nikkei225: July 2001-July 2006). Data Envelopment Analysis has also been undertaken to compare the performance of the technical efficiencies of the optimal risk budgeted portfolios obtained by the three approaches.

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