Forecasting of Jakarta Islamic Index (JII) returns using Holt-Winters family models

Abstract

Purpose: This research aims to forecast JII returns by employing various Holt-Winters models. The models used in this research are Holt-Winters seasonality, Holt-Winters damped method, and Holt-Winters with maximum likelihood approach. Holt-Winters model is capable of recognizing and modeling trends and seasonality. Therefore, it is suitable for forecasting purposes.Methodology: Three models are employed in this research. The first one is Holt-Winters seasonality, also known as triple exponential smoothing. This model analyzes the level, trend, and seasonality components in the return series. The second model is the Holt-Winters damped method that uses smoothing parameters to lower the overstatement effect that usually occurs within Holt-Winters seasonality. The third model is Holt-Winters with Maximum Likelihood. Holt-Winters seasonality estimates parameters by choosing the least-squares. At the same time, Holt-Winters with Maximum Likelihood uses maximum likelihood to fit in the series with certain distributions and generate forecasts by determining distributions with the most likelihood.Findings: The result showed that Holt-Winters seasonality forecasts better than the other methods. The model could recognize the seasonal pattern and trend of the JII returns. It has the lowest Root Mean Squared Error (RMSE) as the parameter for forecast accuracy. Holt-Winters damped method has accuracy right below Holt-Winters seasonality. It can also map the pattern and trend of the returns. Holt-Winters with Maximum likelihood predicts less accurately. However, it can recognize the random walk inclination of the return, although it failed to generate the seasonal pattern and trend of the JII returns.Originality: This research attempted to apply Holt-Winters models to predict JII returns. Most research concerning the Islamic stock index focuses on volatility and forecast based on the level of volatility. Therefore, this research can fill in the gaps in the literature in which forecast of Islamic stock index can be conducted by modeling the seasonality and trend using Holt-Winters models.Practical implications: Investors always try to find the best generating investment return. Investors concerned with the shariah rules will always find lawful investment tools such as Islamic stocks or the Islamic stock index. Returns of the Islamic stock index can be forecast by using the Holt-Winters model. Therefore, investors might know the pattern of returns generated by investing in Islamic stocks.

Komparasi Metode Single Exponential Smoothing Dan Holt's Linear Method Pada Forecasting Volume Impor

“…Metode single exponential smoothing memberikan pembobotan empiris yang secara proporsional lebih lemah dari semua pengamatan sebelumnya (Utami & Atmojo, 2017). Sedangkan holt's linear method adalah metode yang dapat mengatasi pengaruh tren dan musiman yang muncul secara sekaligus pada suatu data deret waktu (Ponziani, 2021)).…”