Forecasting Price Volatility Range of Crude Palm Oil by Mining the Historical Data Using Hybrid Range Model

Volatile price fluctuation of crude palm oil has been a major challenge faced by planters, plantation companies, investors, and even downstream industry. Severe price volatility over the past few years has negatively been impacting the decision making process of risk hedging and mitigation. This paper discusses various models that are generally used to forecast price and volatility in financial time series. A hybrid range model is proposed to forecast the possible future price volatility range by mining the historical price data of crude palm oil. Experiment was conducted on the historical data of futures crude palm oil for the period of twenty seven years to assess the competency of the hybrid model. The outcome of the experiment reveals a promising performance demonstrating the relevancy of the proposed hybrid range model. This study constitutes a novel approach using standard deviation to quantify price equilibrium of crude palm oil by mining the distribution and dispersion of historical price data points. Thus, the possible future range of price fluctuation can be postulated to aid the crucial financial decision making process.