Multifraktalitas dan Studi Komparatif Prediksi Indeks dengan Metode Arima dan Artificial Neural Network (ANN)

Harjum Muharam; Muhammad Panji

doi:10.21512/tw.v9i2.720

Authors

Harjum Muharam Universitas Diponegoro
Muhammad Panji Universitas Diponegoro

DOI:

https://doi.org/10.21512/tw.v9i2.720

Keywords:

LQ45, multifraktality, ARIMA, artificial neural network

Abstract

This paper discusses technical analysis widely used by investors. There are many methods that exist and used by investor to predict the future value of a stock. In this paper we start from finding the value of Hurst (H) exponent of LQ 45 Index to know the form of the Index. From H value, we could determinate that the time series data is purely random, or ergodic and ant persistent, or persistent to a certain trend. Two prediction tools were chosen, ARIMA (Auto Regressive Integrated Moving Average) which is the de facto standard for univariate prediction model in econometrics and Artificial Neural Network (ANN) Back Propagation. Data left from ARIMA is used as an input for both methods. We compared prediction error from each method to determine which method is better. The result shows that LQ45 Index is persistent to a certain trend therefore predictable and for outputted sample data ARIMA outperforms ANN.

Dimensions

Plum Analytics

Author Biographies

Harjum Muharam, Universitas Diponegoro

Fakultas Ekonomi

Muhammad Panji, Universitas Diponegoro

Fakultas Ekonomi

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