Application of quasi-oppositional symbiotic organisms search based extreme learning machine for stock market prediction
| Autor: | Binod Kumar Sahu, Manoj Ranjan Nayak, Smita Rath |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Optimal design
Stock market prediction General Computer Science Mean squared error 020209 energy 02 engineering and technology Stock market index Mean absolute percentage error 0202 electrical engineering electronic engineering information engineering Econometrics 020201 artificial intelligence & image processing Stock (geology) Predictive modelling Extreme learning machine Mathematics |
| Zdroj: | International Journal of Intelligent Computing and Cybernetics. 12:175-193 |
| ISSN: | 1756-378X |
| DOI: | 10.1108/ijicc-10-2018-0145 |
| Popis: | PurposeForecasting of stock indices is a challenging issue because stock data are dynamic, non-linear and uncertain in nature. Selection of an accurate forecasting model is very much essential to predict the next-day closing prices of the stock indices. The purpose of this paper is to develop an efficient and accurate forecasting model to predict the next-day closing prices of seven stock indices.Design/methodology/approachA novel strategy called quasi-oppositional symbiotic organisms search-based extreme learning machine (QSOS-ELM) is proposed to forecast the next-day closing prices effectively. Accuracy in the prediction of closing price depends on output weights which are dependent on input weights and biases. This paper mainly deals with the optimal design of input weights and biases of the ELM prediction model using QSOS and SOS optimization algorithms.FindingsSimulation is carried out on seven stock indices, and performance analysis of QSOS-ELM and SOS-ELM prediction models is done by taking various statistical measures such as mean square error, mean absolute percentage error, accuracy and paired samplet-test. Comparative performance analysis reveals that the QSOS-ELM model outperforms the SOS-ELM model in predicting the next-day closing prices more accurately for all the seven stock indices under study.Originality/valueThe QSOS-ELM prediction model and SOS-ELM are developed for the first time to predict the next-day closing prices of various stock indices. The pairedt-test is also carried out for the first time in literature to hypothetically prove that there is a zero mean difference between the predicted and actual closing prices. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|