Work

Non-linear Autoregressive with Exogeneous input (narx) bitcoin price prediction model using PSO-optimized parameters and moving average technical indicators

Year: 2018

Type: article

Abstract: This paper presents a Multi-Layer Exogeneous Inputs (NARX) Bitcoin price forecasting model using the opening, closing, minimum and maximum past prices together with Moving Average (MA) technical indicators.As there were many parameter (PSO)-based method was used to optimize the number of hidden units, input lag and output lag of the NARX model.The results demonstrated the ability of the model to predict Bitcoin prices accurately while passing all model validation tests.

Source: Journal of Fundamental and Applied Sciences

DOI: 10.4314/jfas.v9i3s.61

Authors: N.I. Indera, I.M. Yassin, A. Zabidi, Z.I. Rizman

Institutions: Universiti Teknologi MARA System, Universiti Teknologi MARA

Language: English

Topic: Stock Market Forecasting Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W2775007683

FWCI: 12.19

Cites: 17

Cited by: 93

Related to: 10