Bivariate Long Term Fuzzy Time Series Forecasting of Dry Cargo Freight Rates

This paper proposes a bivariate long term fuzzy inference system for time series forecasting task in the field of freight market. Fuzzy time series methods are applied by many scholars, it is broadly accepted pattern recognition, forecasting tool. Previous studies mainly establish algorithms for high frequency time series data such as daily, monthly intervals. The proposed model performs similar techniques for long term annual base data, also extends the conventional method with multi-variate heuristic algorithm.Empirical work is accomplished on shipping freight rate data, life expectancy is used as a leading indicator in the bivariate fuzzy time series model.