Evaluation of Transaction Risks of Mean Variance Model Under Identical Variance of the Rate of Return – Simulation in Artificial Market

2005 ◽  
pp. 42-49 ◽  
Author(s):  
Ko Ishiyama ◽  
Shusuke Komuro ◽  
Hideki Tanuma ◽  
Yusuke Koyama ◽  
Hiroshi Deguchi
Keyword(s):  
Rate Of Return ◽  
Artificial Market ◽  
Variance Model ◽  
Mean Variance

scholarly journals Market-based instruments for risk-averse farmers: rubber agroforest conservation in Jambi Province, Indonesia

2016 ◽  
Vol 22 (2) ◽  
pp. 133-155 ◽  
Author(s):  
Utkur Djanibekov ◽  
Grace B. Villamor
Keyword(s):  
Income Inequality ◽  
Risk Aversion ◽  
Real Options ◽  
Risk Averse ◽  
Variance Model ◽  
Income Uncertainty ◽  
Real Options Approach ◽  
Pigovian Taxes ◽  
Rubber Agroforest ◽  
Mean Variance

AbstractThis paper investigates the effectiveness of different market-based instruments (MBIs), such as eco-certification premiums, carbon payments, Pigovian taxes and their combination, to address the conversion of agroforests to monoculture systems and subsequent effects on incomes of risk-averse farmers under income uncertainty in Indonesia. For these, the authors develop a farm-level dynamic mean-variance model combined with a real options approach. Findings show that the conservation of agroforest is responsive to the risk-aversion level of farmers: the greater the level of risk aversion, the greater is the conserved area of agroforest. However, for all risk-averse farmers, additional incentives in the form of MBIs are still needed to prevent conversion of agroforest over the years, and only the combination of MBIs can achieve this target. Implementing fixed MBIs also contributes to stabilizing farmers’ incomes and reducing income risks. Consequently, the combined MBIs increase incomes and reduce income inequality between hardly and extremely risk-averse farmers.

Portfolio optimization with transaction costs: a two-period mean-variance model

2014 ◽  
Vol 233 (1) ◽  
pp. 135-156 ◽  
Author(s):  
Ying Hui Fu ◽  
Kien Ming Ng ◽  
Boray Huang ◽  
Huei Chuen Huang
Keyword(s):  
Transaction Costs ◽  
Portfolio Optimization ◽  
Variance Model ◽  
Mean Variance

scholarly journals Multi-time state mean-variance model in continuous time

2021 ◽  
Vol 27 ◽  
pp. 92
Author(s):  
Shuzhen Yang
Keyword(s):  
Boundary Conditions ◽  
Continuous Time ◽  
Optimal Strategy ◽  
Investment Portfolio ◽  
Variance Model ◽  
Investment Plan ◽  
Terminal Time ◽  
Variance Risk ◽  
Maximum Drawdown ◽  
Mean Variance

The objective of the continuous time mean-variance model is to minimize the variance (risk) of an investment portfolio with a given mean at the terminal time. However, the investor can stop the investment plan at any time before the terminal time. To solve this problem, we consider to minimize the variances of the investment portfolio in the multi-time state. The advantage of this multi-time state mean-variance model is the minimization of the risk of the investment portfolio within the investment period. To obtain the optimal strategy of the model, we introduce a sequence of Riccati equations, which are connected by jump boundary conditions. In addition, we establish the relationships between the means and variances in the multi-time state mean-variance model. Furthermore, we use an example to verify that the variances of the multi-time state can affect the average of Maximum-Drawdown of the investment portfolio.

scholarly journals The Exponential-Weight Mean-Variance Model: A novel computational model for the Balloon Analogue Risk Task

2019 ◽  
Author(s):  
Harhim Park ◽  
Jaeyeong Yang ◽  
Jasmin Vassileva ◽  
Woo-Young Ahn
Keyword(s):  
Computational Model ◽  
Computational Models ◽  
Model Comparison ◽  
Exponential Weight ◽  
Multiple Model ◽  
Variance Model ◽  
Balloon Analogue Risk Task ◽  
Parameter Recovery ◽  
Post Hoc ◽  
Mean Variance

The Balloon Analogue Risk Task (BART) is a popular task used to measure risk-taking behavior. To identify cognitive processes associated with choice behavior on the BART, a few computational models have been proposed. However, the extant models are either too simplistic or fail to show good parameter recovery performance. Here, we propose a novel computational model, the exponential-weight mean-variance (EWMV) model, which addresses the limitations of existing models. By using multiple model comparison methods, including post hoc model fits criterion and parameter recovery, we showed that the EWMV model outperforms the existing models. In addition, we applied the EWMV model to BART data from healthy controls and substance-using populations (patients with past opiate and stimulant dependence). The results suggest that (1) the EWMV model addresses the limitations of existing models and (2) heroin-dependent individuals show reduced risk preference than other groups in the BART.

Optimal selection of financial risk investment portfolio based on random matrix method

2020 ◽  
Vol 20 (3) ◽  
pp. 859-868
Author(s):  
Jie Tian ◽  
Kun Zhao
Keyword(s):  
Covariance Matrix ◽  
Random Matrix ◽  
Financial Risk ◽  
Good Effect ◽  
Investment Portfolio ◽  
Variance Model ◽  
Minimum Risk ◽  
The Mean ◽  
Risk Investment ◽  
Mean Variance

The optimization of investment portfolio is the key to financial risk investment. In this study, the investment portfolio was optimized by removing the noise of covariance matrix in the mean-variance model. Firstly, the mean-variance model and noise in covariance matrix were briefly introduced. Then, the correlation matrix was denoised by KR method (Sharifi S, Grane M, Shamaie A) from random matrix theory (RMT). Then, an example was given to analyze the application of the method in financial stock investment portfolio. It was found that the stability of the matrix was improved and the minimum risk was reduced after denoising. The study of minimum risk under different M values and stock number suggested that calculating the optimal value of M and stock number based on RMT could achieve optimal financial risk investment portfolio result. It shows that RMT has a good effect on portfolio optimization and is worth promoting widely.

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