Financial Time series Forecasting using Holt-Winters in H-step Ahead

Document Type : Research Paper

Authors

1 Prof. of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran

2 MSc. Student in Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran

Abstract

Up to now various methods have been used to predict stock prices and profits. According to financial volatility markets, the most important thing is which of the methods can be applied to predict the optimal decision to help managers and decision makers and business sectors. Most studies have been done up to now to predict the time series, autoregressive method known as Box-Jenkins has been used to predict the time series. While there are many time series with seasonal variations or cyclic which can not be adequately modeled by a polynomial. In this study, Holt-Winters method is used to predict non-stationary time series data for the profit sale of an intermediate product. The results show that the proposed method compared with classical methods and procedures S-filtered has a higher performance in forecasting future values.

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References

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Financial Research Journal
Volume 18, Issue 3
March 2016
Pages 505-518

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