Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model

被引：0
|
作者：
Roman Matkovskyy
Taoufik Bouraoui
机构：
[1] Rennes School of Business,Department of Finance and Accounting
来源：
Journal of Quantitative Economics | 2019年 / 17卷
关键词：
Index of financial safety (IFS); Forecasting; Nonlinear autoregressive with exogenous input (NARX) model; Neural networks; C43; C45; C53;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The aim of this paper is to extend the index of financial safety (IFS) approach with improving its predictive performance and to show the applicability of artificial neural networks to economic and financial short time series. To this end, prediction is performed by means of the nonlinear autoregressive with exogenous inputs (NARX) model that represents the neural networks and can emulate any nonlinear dynamic state space model. Thus, a NARX model, trained by means of Levenberg–Marquardt algorithm, was chosen since it gave the best performance. Results reveal that the NARX models are suitable for performing short time series composite indexes prediction.
引用
收藏
页码：433 / 446
页数：13
相关论文
共 50 条
  • [1] Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model
    Matkovskyy, Roman
    Bouraoui, Taoufik
    [J]. JOURNAL OF QUANTITATIVE ECONOMICS, 2019, 17 (02) : 433 - 446
  • [2] Wastewater flow forecasting model based on the nonlinear autoregressive with exogenous inputs (NARX) neural network
    El Ghazouli, Khalid
    El Khatabi, Jamal
    Shahrour, Isam
    Soulhi, Aziz
    [J]. H2OPEN JOURNAL, 2021, 4 (01) : 276 - 290
  • [3] The nonlinear autoregressive network with exogenous inputs (NARX) neural network to damp power system oscillations
    Carbonera, Luis Felipe Bianchi
    Pinheiro Bernardon, Daniel
    de Castro Karnikowski, Douglas
    Alberto Farret, Felix
    [J]. INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2021, 31 (01)
  • [4] Estimating time-series leaf area index based on recurrent nonlinear autoregressive neural networks with exogenous inputs
    Chai, Linna
    Qu, Yonghua
    Zhang, Lixin
    Liang, Shunlin
    Wang, Jindi
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2012, 33 (18) : 5712 - 5731
  • [5] Neural Nonlinear Autoregressive Model with Exogenous Input (NARX) for Turboshaft Aeroengine Fuel Control Unit Model
    De Giorgi, Maria Grazia
    Strafella, Luciano
    Ficarella, Antonio
    [J]. AEROSPACE, 2021, 8 (08)
  • [6] A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation
    Boussaada, Zina
    Curea, Octavian
    Remaci, Ahmed
    Camblong, Haritza
    Bellaaj, Najiba Mrabet
    [J]. ENERGIES, 2018, 11 (03):
  • [7] A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of Timestamp Influence on Bitcoin Value
    Aljojo, Nahla
    Alshutayri, Areej
    Aldhahri, Eman
    Almandeel, Seita
    Zainol, Azida
    [J]. IEEE ACCESS, 2021, 9 : 148611 - 148624
  • [8] Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs
    Buitrago, Jaime
    Asfour, Shihab
    [J]. ENERGIES, 2017, 10 (01)
  • [9] Performance of Modeling Time Series Using Nonlinear Autoregressive with eXogenous input (NARX) in the Network Traffic Forecasting
    Haviluddin
    Alfred, Rayner
    [J]. 2015 INTERNATIONAL CONFERENCE ON SCIENCE IN INFORMATION TECHNOLOGY (ICSITECH), 2015, : 164 - 168
  • [10] A Recurrent-Cascade-Neural network- nonlinear autoregressive networks with exogenous inputs (NARX) approach for long-term time-series prediction of wave height based on wave characteristics measurements
    Miky, Yehia
    Kaloop, Mosbeh R.
    Elnabwy, Mohamed T.
    Baik, Ahmad
    Alshouny, Ahmed
    [J]. OCEAN ENGINEERING, 2021, 240
12345