Non-Uniform Nested Simulation Algorithms in Portfolio Risk Measurement

2015 ◽  
Author(s):  
Saifeddine Ben Hadj
Keyword(s):  
Risk Measurement ◽  
Portfolio Risk ◽  
Simulation Algorithms

Portfolio Risk Measurement

1999 ◽  
Vol 2 (1) ◽  
pp. 34-42 ◽  
Author(s):  
Sam Y. Chung
Keyword(s):  
Risk Measurement ◽  
Portfolio Risk

PENGUKURAN RISIKO PORTFOLIO DENGAN MENGGUNAKAN METODE VALUE AT RISK (VAR)

2013 ◽  
Author(s):  
Fajri Adrianto ◽  
Laela Susdiani
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Measurement Method ◽  
Simulation Method ◽  
Risk Measurement ◽  
Portfolio Risk ◽  
Historical Simulation ◽  
Stock Investment ◽  
Risk Investment

Value at Risk (VAR) is a risk measurement method that use in risk investment calculation. VAR shows risk in nominal. This research calculate risk portfolio of stock using VAR method and measure whether VAR value overvalued or underestimated. Using historical simulation method is found VAR value tend to decrease when stock investment consist more stocks in the portfolio. Risk investment calculation consistent with standar devistion as risk measurement, which the more investment diversified the less the risk in the investment. Then, using backtesting reveal that VAR tend too high in portfolio consisting small number of stocks. VAR value can accepted in the portfolio that consist many stocks or the more investment diversified the more accurate VAR value as risk measurement.

scholarly journals Calculation Formulas and Simulation Algorithms for Entropy of Function of LR Fuzzy Intervals

Entropy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 289 ◽  
Author(s):  
Jie Shen ◽  
Jian Zhou
Keyword(s):  
Numerical Integration ◽  
Linear Function ◽  
Nonlinear Function ◽  
Risk Measurement ◽  
Integration Process ◽  
Entropy Optimization ◽  
Simulation Algorithms ◽  
Simplified Calculation ◽  
Discretization Process ◽  
Fuzzy Interval

Entropy has continuously arisen as one of the pivotal issues in optimization, mainly in portfolios, as an indicator of risk measurement. Aiming to simplify operations and extending applications of entropy in the field of LR fuzzy interval theory, this paper first proposes calculation formulas for the entropy of function via the inverse credibility distribution to directly calculate the entropy of linear function or simple nonlinear function of LR fuzzy intervals. Subsequently, to deal with the entropy of complicated nonlinear function, two novel simulation algorithms are separately designed by combining the uniform discretization process and the numerical integration process with the proposed calculation formulas. Compared to the existing simulation algorithms, the numerical results show that the advantage of the algorithms is well displayed in terms of stability, accuracy, and speed. On the whole, the simplified calculation formulas and the effective simulation algorithms proposed in this paper provide a powerful tool for the LR fuzzy interval theory, especially in entropy optimization.

scholarly journals Nested Simulation in Portfolio Risk Measurement

2008 ◽  
Vol 2008 (21) ◽  
pp. 1-31 ◽  
Author(s):  
Michael B. Gordy ◽  
◽  
Sandeep Juneja
Keyword(s):  
Risk Measurement ◽  
Portfolio Risk

Multidimensional portfolio risk measurement: a mixed copula approach

2020 ◽  
Vol 12 (3) ◽  
pp. 228
Author(s):  
Wen Li Cai ◽  
Na Liu ◽  
Yu Xuan Wu ◽  
Xiang Dong Liu
Keyword(s):  
Risk Measurement ◽  
Portfolio Risk ◽  
Copula Approach

Kernel Smoothing for Nested Estimation with Application to Portfolio Risk Measurement

2017 ◽  
Vol 65 (3) ◽  
pp. 657-673 ◽  
Author(s):  
L. Jeff Hong ◽  
Sandeep Juneja ◽  
Guangwu Liu
Keyword(s):  
Kernel Smoothing ◽  
Risk Measurement ◽  
Portfolio Risk

scholarly journals Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review

2019 ◽  
Vol 12 (1) ◽  
pp. 48 ◽  
Author(s):  
Ruili Sun ◽  
Tiefeng Ma ◽  
Shuangzhe Liu ◽  
Milind Sathye
Keyword(s):  
Covariance Matrix ◽  
Portfolio Selection ◽  
Factor Model ◽  
Minimum Variance ◽  
Risk Measurement ◽  
Financial Data ◽  
Portfolio Risk ◽  
Matrix Estimation ◽  
Measurement Moment ◽  
Portfolio Selection Model

The literature on portfolio selection and risk measurement has considerably advanced in recent years. The aim of the present paper is to trace the development of the literature and identify areas that require further research. This paper provides a literature review of the characteristics of financial data, commonly used models of portfolio selection, and portfolio risk measurement. In the summary of the characteristics of financial data, we summarize the literature on fat tail and dependence characteristic of financial data. In the portfolio selection model part, we cover three models: mean-variance model, global minimum variance (GMV) model and factor model. In the portfolio risk measurement part, we first classify risk measurement methods into two categories: moment-based risk measurement and moment-based and quantile-based risk measurement. Moment-based risk measurement includes time-varying covariance matrix and shrinkage estimation, while moment-based and quantile-based risk measurement includes semi-variance, VaR and CVaR.

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