International Journal of Finance and Accounting 2016, 5(1): 54-61 DOI: 10.5923/j.ijfa.20160501.07 Forecasting Stock Market Volatility on Bursa Malaysia Plantation Index Hui-Shan Lee 1,2,* , David Ching-Yat Ng 3 , Teck-Chai Lau 1 , Chee-Hong Ng 3 1 Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Malaysia 2 Faculty of Economics and Management, Universiti Putra Malaysia, Malaysia 3 Graduate School of Management, Universiti Putra Malaysia, Malaysia Abstract This research applies the Bursa Malaysia Plantation Index to examine the most suitable forecasting model. The Plantation Index is studied because Malaysia is the world second largest in oil palm producer. Additionally, volatile crude palm oil price has resulted in the Plantation Index becoming more volatile as earnings of plantation companies depend heavily on crude palm oil prices. The forecasting techniques applied were random walk, moving average, simple regression and historical mean. The error in forecasting was measured by symmetric and asymmetric error statistics. The most suitable volatility forecasting technique for Bursa Malaysia Plantation Index was simple regression technique. The findings to a very large extent indicate that although there are different sophisticated forecasting technique, investor, managers and regulators could employ the less costly simple regression method to forecast oil palm related stocks and make their wise decision in investment, management and regulation in oil palm industry. Keywords Forecasting, Security market volatility, Volatility forecasting technique, Symmetric error statistics, Asymmetric error statistics 1. Introduction Volatility of stock markets has generated much interest among investors because high volatility can bring about huge gains or losses to investors. This directly creates a risk to investors (Poon and Clive 2003). Undeniably, a rational investor always makes an investment decision based on risk and return. There have been numerous studies that have been carried out in order to identify the risk factors. A volatility forecasting technique is used as a risk indicator because it can predict the future trend by tracing the pattern. Numerous practitioners and investors have applied volatility forecasting techniques in stock market valuation and derivative securities in order to help them make better judgment in asset allocations, portfolio choices and to determine the fair value of assets. Stephen (2004) indicated that there are a large number of volatility forecasting techniques but not all techniques are appropriate to be applied in different context. Hence it is important to determine which technique/s is/are superior to forecast the stock market. Identifying the best volatility forecasting technique is a critical job (Brailsford and Faff, 1996). This is because a best predict volatility forecasting * Corresponding author: hslee@utar.edu.my (Hui-Shan Lee) Published online at http://journal.sapub.org/ijfa Copyright © 2015 Scientific & Academic Publishing. All Rights Reserved techniques not only depends on data availability and predefined assumption but also depends on the quality of data (Abraham et al, 2007). This study seeks to examine the ability of four different types of volatility forecasting technique in predicting the Bursa Malaysia Plantation Index. The research objectives of this are: 1. To determine the most suitable forecasting model among the four volatility forecasting techniques. 2. To examine the relationship between the period of historical data and accuracy to forecast Bursa Malaysia Plantation Index. 3. To determine the degree of under-prediction or over-prediction for each volatility forecasting technique. 1.1. Bursa Malaysia Bursa Malaysia is considered a relatively young stock market compared to other capital markets in developed countries such as United States. However, Bursa Malaysia’s growth has been nothing short of stunning since its inception. According to Chong and Puah (2009), the market valuation of Bursa Malaysia in 1980s was estimated as RM43 billion and this had increased to RM1 trillion in 2007. In 2012, Malaysia becomes an oasis and hot spot in a tepid global market for the Initial Public Offerings (IPO) because the second and third world largest initial public offering occurred in Malaysia - Felda Global Ventures Holding