Comparison of Holt and Brown's Double Exponential Smoothing Methods in The Forecast of Moving Price for Mutual Funds
Viewed = 258 time(s)
Mutual funds are one of the promising investment media where the risk is directly proportional to the size of investment growth. With proper forecasting of NAV price movements will greatly help investors to make purchases and sales transactions, therefore the authors offer the use of two different forecasting methods namely Brown's method and Holt method in double exponential smoothing to get predictions of NAV price movements. The effectiveness of the use of the method will be measured from the value of Mean Average Percentage Error (MAPE). From the calculation results obtained by the data that the Holt method produces forecasting for 1809,657 with the best α value of 0.6 and MAPE of 0.644373568, while for the Holt method obtained forecasting value of 1810,924 with the α value and the best β value of 0.9 and 0.1 and the smaller MAPE value of 0.61604262 . Looking at the amount of MAPE generated, the Holt method has a smaller forecasting error rate when compared to Brown’s method.
Masruroh, A. (2014). Konsep Dasar Investasi Reksadana. SALAM: Jurnal Sosial Dan Budaya Syar-I. doi: 10.15408/sjsbs.v1i1.1526
Zamzany, F. R., & Setiawan, E. (2018). Studi Komparatif Kinerja Reksadana Saham Konvensional dan Syariah Di Indonesia. Akuntabilitas, 11(2), 305–318. doi: 10.15408/akt.v11i2.8794
Wu, L., Liu, S., & Yang, Y. (2016). Grey double exponential smoothing model and its application on pig price forecasting in China. Applied Soft Computing Journal. doi: 10.1016/j.asoc.2015.09.054
Utami, R., & Atmojo, S. (2017). Perbandingan Metode Holt Exponential Smoothing dan Winter Exponential Smoothing Untuk Peramalan Penjualan Souvenir. 11(2), 123–130.
Hansun, S. (2016). A New Approach of Brown’s Double Exponential Smoothing Method in Time Series Analysis. Balkan Journal of Electrical and Computer Engineering, 4(2). doi: 10.17694/bajece.14351
Copyright (c) 2019 Achmad Muchayan (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.