Chaotic Stochastic Lee-Carter Model in Predicting Kijang Emas Price Movements: A Machine Learning Approach
Chaos is nonlinear and unpredictable which teaches us to expect the unexpected. Chaos Theory deals with nonlinear things that are effectively impossible to predict or control. There are a lot of important concepts about chaos has been introduced. The deterministic system has produced randomness which is called as “deterministic chaos”. An example of a deterministic chaotic system is the gold price index. In order to analyse the impact of chaos elements in predicting the gold price movements, the Chaotic Stochastic Lee-Carter Model was used in this study with the help of R software. This model is a hybrid of Chaos Theory and Stochastic Lee-Carter Model which was traditionally used in long run forecasts of age specific mortality rates. This research was done by using the data of Kijang Emas gold bullion coin’s selling and buying prices which were retrieved from the Central Bank of Malaysia (BNM). The results showed that Chaos Theory does help in improving the prediction accuracy of the current Stochastic Lee-Carter Model.
KeywordsChaos theory Lee-Carter model Data mining Machine learning Largest Lyapunov exponent
This study is conducted with the support from Universiti Teknologi MARA’s iRAGS grant 600-RMI/IRAGS 5/3 (19/2015).
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