The Fama 3 and Fama 5 factor models under a machine learning framework

Periklis Gogas, Theophilos Papadimitriou and Dimitrios Karagkiozis
Additional contact information
Dimitrios Karagkiozis: Department of Economics, Democritus University of Thrace, Greece

Working Paper series from Rimini Centre for Economic Analysis

Abstract: We examine four empirical models which are popular in money and stock markets world. These models are Fama – French 3 & 5 factors model, the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT) model. These tools are intensively used by investors and market professionals as an important part of the investment decision process and for the evaluation of the applied investment strategies. The last years, several surveys and studies have done, and various methodologies were implemented to evaluate the effectiveness of these four models. The methodological approach of the current thesis focuses on the Support Vector Regression (SVR). This method is running in comparison with the Ordinary Least Squares linear regression.

Keywords: stock markets; stock returns; machine learning; support vector regression (search for similar items in EconPapers)
JEL-codes: C45 C5 F31 F37 (search for similar items in EconPapers)
Date: 2018-02
New Economics Papers: this item is included in nep-big and nep-fmk
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://rcea.org/RePEc/pdf/wp18-05.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:18-05

Access Statistics for this paper

More papers in Working Paper series from Rimini Centre for Economic Analysis Contact information at EDIRC.
Bibliographic data for series maintained by Marco Savioli ().