Pattern Modelling in Time-series Forecasting

Pattern modelling in time-series prediction refers to the process of identifying past relationships and trends in historical data for predicting future values. This paper describes the development of a new pattern matching technique for univariate time-series forecasting. The pattern modelling technique out-performs frequently used statistical methods such as Exponential Smoothing on different error measures and predicting the direction of change in time-series. The paper discusses the prediction results on popular benchmarks and the real US S&P index for financial markets.