Nvidia’s stock returns prediction using machine learning techniques for time series forecasting problem

Marcin Chlebus (), Michał Dyczko and Michał Woźniak ()
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Michał Dyczko: Faculty of Mathematics and Computer Science, Warsaw University of Technology

No 2020-22, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: The main aim of this paper was to predict daily stock returns of Nvidia Corporation company quoted on Nasdaq Stock Market. The most important problems in this research are: statistical specificity of return ratios i.e. time series might occur to be a white noise and the fact of necessity of applying many atypical machine learning methods to handle time factor influence. The period of study covered 07/2012 - 12/2018. Models used in this paper were: SVR, KNN, XGBoost, LightGBM, LSTM, ARIMA, ARIMAX. Features which, were used in models comes from such classes like: technical analysis, fundamental analysis, Google Trends entries, markets related to Nvidia. It was empirically proved that there is a possibility to construct prediction model of Nvidia daily return ratios which can outperform simple naive model. The best performance was obtained by SVR based on stationary attributes. Generally, it was shown that models based on stationary variables perform better than models based on stationary and non-stationary variables. Ensemble approach designed especially for time series failed to make an improvement in forecast precision. It seems that usage of machine learning models for the problem of time series with various explanatory variable classes brings good results.

Keywords: nvidia; stock returns; machine learning; technical analysis; fundamental analysis; google trends; stationarity; ensembling (search for similar items in EconPapers)
JEL-codes: C32 C38 C44 C51 C52 C61 C65 G11 G15 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2020
New Economics Papers: this item is included in nep-big, nep-cmp, nep-fmk, nep-for and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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https://www.wne.uw.edu.pl/index.php/download_file/5749/ First version, 2020 (application/pdf)

Related works:
Journal Article: Nvidia's Stock Returns Prediction Using Machine Learning Techniques for Time Series Forecasting Problem (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:war:wpaper:2020-22

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