Determining the Number of Factors and Proposing a Multi-Factor Model: An Exploration of Iranian Market Data

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Karimi, Kiyan | 2020

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 53328 (44)
University: Sharif University of Technology
Department: Management and Economics
Advisor(s): Baharmgiri, Mohsen; Hagh-Panah, Farshad
Abstract:
Asset pricing models are one of the most important tools in investment management and portfolio allocation. Multi-factor asset pricing models try to explain the relationship between risk and expected return through a limited number of macroeconomic, fundamental or statistical factors. Usually, these models are suggested based on the US market and its intrinsic qualities. Although, there are some similarities between the Iranian and the US market, these economies are structurally different and therefore, proposing a proper multi-factor model based on the Iranian market’s fundamental characteristics will greatly improve the understanding of risk-return relationship in this market. In this research, a multi-factor model based on the Iranian market data is going to be proposed using statistical methods such as principal components analysis. By comparing this model to the Fame-French three factor model which is one of the most widely used multi-factor asset pricing model, it is shown that the proposed model is more capable in explaining the cross-section of expected returns
Keywords:
Asset Pricing Model ; Tehran Stock Exchange ; Arbitrage Pricing Theory (APT) ; Systematic Risk ; Multifactor Model ; Principal Component Analysis (PCA) ; Expected Returns Cross Section

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