Wavelet neural network prediction of stock performance

Jackson Criswell, En Bing Lin

Research output: Contribution to journalConference articlepeer-review

Abstract

Wavelet methods and artificial neural networks are incorporated to examine the forecasting performance of the daily closing price of the Microsoft stock, NASDAQ:MSFT. An experimental analysis is performed to demonstrate improved performance of the wavelet neural network. Results in this study suggest that for these neurowavelet models a long history with a short training is ideal for stock prediction. This model could be used by investors, financial managers, or others to enhance their ability to select desired stocks.

Original languageEnglish
Pages (from-to)12-25
Number of pages14
JournalProceedings of the Asian Technology Conference in Mathematics
StatePublished - 2021
Externally publishedYes
Event26th Asian Technology Conference in Mathematics, ATCM 2021 - Virtual, Online
Duration: Dec 13 2021Dec 15 2021

Fingerprint

Dive into the research topics of 'Wavelet neural network prediction of stock performance'. Together they form a unique fingerprint.

Cite this