Monte Carlo Simulation for Data Volatility Analysis of Stock Prices in Islamic Finance for Malaysia Composite Index

Abstract

The objective of this study is to evaluate the volatility rate of sharia-company in Malaysia Stock Exchange using Monte Carlo Simulation (MCS). This study collected daily stock price form Thomson Reuters Datastream for calculating monthly return and volatility rate. In validating the findings of volatility rate, this study performed normality diagnostics test, and Monte Carlo Simulation (MCS). Result indicates the distribution of volatility rate is follows normal distribution. In addition, Monte Carlo Simulation also proved the volatility rate is 4.85% and standard deviation is 2.23. Result of process capability shows the value of volatility rate is under statistical control with implementation on Monte Carlo Simulation. The significant of this study is it provides a better understanding for investors regarding the financial environment in Malaysia Stock Exchange. This information will help investors to make proper selection of their investment portfolio.

Outliers detection in state-space model using indicator saturation approach

“…Thus, we concluded that the outliers detected in January 2008, September 2008 and January 2009 correspond to the recessionary period due to the world financial crisis. This finding demonstrates that IIS is a useful approach to identify outliers in financial data as compared to recent study using shariah compliant stock prices in Malaysia by [31]. This study differs from [31] research that was prone to methodological inadequacies due to inability of Box-Whisker plot to handle non-stationary data and to model the outliers detected.…”

“…This finding demonstrates that IIS is a useful approach to identify outliers in financial data as compared to recent study using shariah compliant stock prices in Malaysia by [31]. This study differs from [31] research that was prone to methodological inadequacies due to inability of Box-Whisker plot to handle non-stationary data and to model the outliers detected. In addition, the box-whisker plot approach is not able to perform significance testing to the outliers captured compared to IIS in GETS modelling.…”

Robust Hybrid Optimization Method to Reduce Investment Portfolio Risk Using Fusion of Modern Portfolio Theory and Genetic Algorithm

“…..…… 11The correlation coefficient for a sample can be derived as Equation (12). Consider the sample has n pair of x, y variables.…”

“…After Markowitz's work, researchers have shown great enthusiasm in portfolio management, trying different mathematical approaches to develop the theory of portfolio selection [10], [11]. Study that examine the volatility rate of sharia-compliant company listed on the Malaysian Stock Exchange using Monte Carlo Simulation method found that Monte Carlo Simulation proved the volatility rate is 4.85% and standard deviation is 2.23 [12]. The result shows the value of volatility rate is under statistical control with implementation of Monte Carlo Simulation approach [12].…”

“…Study that examine the volatility rate of sharia-compliant company listed on the Malaysian Stock Exchange using Monte Carlo Simulation method found that Monte Carlo Simulation proved the volatility rate is 4.85% and standard deviation is 2.23 [12]. The result shows the value of volatility rate is under statistical control with implementation of Monte Carlo Simulation approach [12]. Monte Carlo simulations are a very powerful way to demonstrate the basic sampling properties of various statistics in econometrics [13].…”