Generally, business risks are categorized as either systematic risks or unsystematic risks. Systematic risks or beta are considered as risks that have a general impact on all securities while unsystematic risk is an intrinsic, security specific risk. The study critically studied the characteristics of downside beta for listed companies in Malaysia. The process involves a random selection of 50 Shariah-compliant and 50 conventional stock returns, analysed from January 2015 to January 2020. Firstly, the study tabled the stock returns of the market benchmark, Financial Times Stock Exchange Bursa Malaysia Kuala Lumpur Composite Index (FBM KLCI) and both Shariah-compliant and conventional stocks portfolios. The downside beta is then computed using three methods: Historical Volatility (HV), Exponentially Weighted Moving Average (EWMA) and GARCH (1,1). While analysis of the Shariah-compliant and conventional portfolio as an index can indicate statistically significant difference in their downside beta values, the randomly selected 50 portfolio stocks in this research indicated no statistically significant difference between the two. Furthermore, the Sortino ration is used to determine the beta to return performance between the two portfolios. The Sortino ratio results indicates Shariah-compliant businesses outperforms their conventional counterparts. As such, there is higher appeal for investors to adopt an Islamic business framework, provided due diligence in anchored on downside beta an d reward analysis.

The study focuses on establishing the downside beta for Shariah compliant index, conventional index and bitcoin index (a cryptocurrency) in Malaysia. The indices for the Shariah compliant is the FTSE Bursa Malaysia EMAS Shariah (FTFBMS), the conventional index used is the FTSE Bursa Malaysia EMAS (FTFBMEMAS) and the proxy index for the cryptocurrency is the bitcoin. Given the weak track record of cryptocurrencies in Malaysia, the bitcoin is used as a proxy to simulate cryptocurrency behavior in Malaysia. Downside beta for the three portfolios is calculated through the use of historical volatility (HV) and the Exponentially Weighted Moving Average (EWMA) methods. The findings indicate there is a statistically significant difference in downside beta for each of the portfolios, although the difference is very minimal between Shariah compliant index and the conventional index. However, bitcoin poses to be a riskier portfolio with significant difference over both other indices. The low beta for Shariah complaint indices and its conventional counterparts suggests the large market volume the two indices share, still maintaining them as the mainstream financial models. While bitcoin is vastly riskier, it is surely making promising strides as far as financial trading methods are concerned. Moreover, there is great optimism in cryptocurrency models that assimilate moral Islamic trading principles as research has shown Shariah compliant stocks to be more efficient.

In the modern financial market, investors have to make quick and efficient investment decisions. The problem arises when the investor does not know the right tools to use in investment decision making. Different tools can be implemented in trading strategies to predict future stock prices. Therefore, the primary objective of this paper is to analyse the performance of the Geometric Brownian Motion (GBM) model in forecasting Nestle stock price by assessing the performance evaluation indicators. To analyse the stocks, two software were used, namely Microsoft Excel and Python. The model is trained for 16 weeks (4 months) of data from May to August 2019 and 2020. The simulated sample is for four weeks (1 month) which is for September 2019 and 2020. The findings show that during the Pandemic Covid-19, short-term prediction using GBM is more efficient than long-term prediction as the lowest Mean Square Error (MSE) value is at one week period. In addition, the Mean Absolute Percentage Error (MAPE) for all GBM simulations is highly accurate as it shows that MAPE values are less than 10%, indicating that the GBM method can be used to predict Nestle stock price during an economic downturn.

The diversity of investment in Malaysia provides an excellent platform to gauge volatility. Malaysia as an emerging market with a rich Islamic culture serves as an inspiration to randomly model a portfolio of 50 Shariah compliant stock returns from 2015 to 2020. The systematic risk of a company’s stock returns is measured by computing the volatility and downside volatility for the said period. The Exponentially Weighted Moving Average (EWMA) method is used to outline the risk levels of Shariah compliant stocks for the recent stipulated period. The results indicate a statistical difference between beta and downside beta for Shariah compliant portfolio. This signals investors to be cognisant of the semi-variant characteristics of returns in estimating volatility. Meanwhile, there is no significant difference in performance using the Sharpe and Sortino ratio on the beta and downside beta scores respectively. Consequently, this suggests that investors can always measure performance to a sufficient degree of accuracy regardless of their volatility choice