Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models
Open Access
- 1 June 2016
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 11 (6), e0156338
- https://doi.org/10.1371/journal.pone.0156338
Abstract
The motivation behind this research is to innovatively combine new methods like wavelet, principal component analysis (PCA), and artificial neural network (ANN) approaches to analyze trade in today’s increasingly difficult and volatile financial futures markets. The main focus of this study is to facilitate forecasting by using an enhanced denoising process on market data, taken as a multivariate signal, in order to deduct the same noise from the open-high-low-close signal of a market. This research offers evidence on the predictive ability and the profitability of abnormal returns of a new hybrid forecasting model using Wavelet-PCA denoising and ANN (named WPCA-NN) on futures contracts of Hong Kong’s Hang Seng futures, Japan’s NIKKEI 225 futures, Singapore’s MSCI futures, South Korea’s KOSPI 200 futures, and Taiwan’s TAIEX futures from 2005 to 2014. Using a host of technical analysis indicators consisting of RSI, MACD, MACD Signal, Stochastic Fast %K, Stochastic Slow %K, Stochastic %D, and Ultimate Oscillator, empirical results show that the annual mean returns of WPCA-NN are more than the threshold buy-and-hold for the validation, test, and evaluation periods; this is inconsistent with the traditional random walk hypothesis, which insists that mechanical rules cannot outperform the threshold buy-and-hold. The findings, however, are consistent with literature that advocates technical analysis.This publication has 65 references indexed in Scilit:
- An Algorithm for Testing the Efficient Market HypothesisPLOS ONE, 2013
- Price forecasting of day-ahead electricity markets using a hybrid forecast methodEnergy Conversion and Management, 2011
- A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systemsNeural Computing & Applications, 2010
- Do Foreign Exchange Markets Still Trend?SSRN Electronic Journal, 2006
- Wavelet based denoising integrated into multilayered perceptronNeurocomputing, 2004
- Predicting time series using neural networks with wavelet-based denoising layersNeural Computing & Applications, 2004
- AN INVESTIGATION OF THE HYBRID FORECASTING MODELS FOR STOCK PRICE VARIATION IN TAIWANJournal of the Chinese Institute of Industrial Engineers, 2004
- An architectural framework for the construction of hybrid intelligent forecasting systems: application for electricity demand predictionEngineering Applications of Artificial Intelligence, 1998
- Stock performance modeling using neural networks: A comparative study with regression modelsNeural Networks, 1994
- Least Median of Squares RegressionJournal of the American Statistical Association, 1984