Bachelorarbeit, 2021
140 Seiten, Note: 1,0
1. Introduction
1.1 Rationale and Contributive Factors
1.2 Objective and Aims
2. Literature Review
2.1 Real Estate Investment Trusts
2.2 The Capital Asset Pricing Model
2.3 Stock Return Anomalies
2.4 Fama-French Three-Factor Model
2.5 Carhart Four-Factor Model
2.6 Evidence from the US and Japanese REIT-Market
2.7 Gap in the Literature
3. Empirical Framework
3.1 The Alternative Factor Model
3.2 Data Base
3.3 Methodology
3.3.1 Construction of the Risk Factors
3.3.2 Construction of the Test Portfolios
3.3.3 Regression Models and Evaluation Methods
4. Empirical Analysis
4.1 Descriptive Statistics
4.2 Regression Results
4.2.1 Variation in REIT Returns
4.2.2 The Cross-Section of REIT Returns
5. Conclusion
The academic paper aims to empirically evaluate whether multifactor asset pricing models, specifically the Fama-French Three-Factor Model, the Carhart Four-Factor Model, and a newly proposed Alternative Four-Factor Model, provide superior predictive power for REIT returns in the US and Japanese markets compared to the traditional Capital Asset Pricing Model (CAPM).
2.1 Real Estate Investment Trusts
A Real Estate Investment Trust (REIT) is characterized by holding and operating lasting income-generating properties (equity REITs) or by generating income through financing real estate (mortgage REITs)1. By securitizing its illiquid real estate, individual and institutional investors are offered the opportunity to invest in real estate without actively managing, financing, or operating the actual buildings. Investors simultaneously benefit from fungible trading possibilities since REITs are typically listed on major securities exchanges (see, for instance, Bone-Winkel, Schäfers and Schulte (2008, p. 45), Parker (2012, p. 11)). Although REITs highly correlate with the stock market in the short-term, this relation steadily decreases and becomes insignificant over time. Instead, publicly listed REITs exhibit a strong positive correlation with direct real estate in the long-term, thus rather adapting attributes of real estate as opposed to ordinary stocks (Bienert, Sebastian and Just, 2015, pp. 72–73; Ghosh, Miles and Sirmans, 1996, pp. 46–51). This highlights the importance of separately testing whether ordinary multifactor asset pricing models are suitable for analysing REITs and thus real estate returns.
1. Introduction: Outlines the limitations of the CAPM in explaining stock returns and introduces the motivation to test multifactor models on US and Japanese REIT markets.
2. Literature Review: Synthesizes current theories on REIT characteristics and asset pricing models, including the CAPM, Fama-French, and Carhart models, while identifying the research gap.
3. Empirical Framework: Details the construction of the author's Alternative Factor Model (AFF) incorporating net profit margin, data sources, and the methodology for constructing risk factors and test portfolios.
4. Empirical Analysis: Presents the descriptive statistics for risk factors and the results of time-series regressions and cross-sectional analysis across both markets.
5. Conclusion: Summarizes findings regarding the efficiency of multifactor models in predicting REIT returns and provides implications for future research and real estate investment management.
Real Estate Investment Trusts, REITs, Multifactor Asset Pricing Models, CAPM, Fama-French Three-Factor Model, Carhart Four-Factor Model, Alternative Factor Model, Net Profit Margin, Systematic Risk, US Market, Japanese Market, Equity Returns, Market Equity, Book-to-Market-Equity, Momentum.
This work evaluates whether multifactor asset pricing models, originally designed for ordinary stocks, can effectively explain the returns of Real Estate Investment Trusts (REITs) in the US and Japanese markets.
The thesis covers corporate finance, real estate management, and econometric modeling, specifically looking at how factors like firm size, value, momentum, and profitability affect REIT returns.
The primary goal is to empirically test whether augmenting the traditional CAPM with additional risk factors (size, value, momentum, and profitability) enhances the prediction power for REIT returns.
The study utilizes linear time-series regressions using the Newey and West (1987) estimator to handle autocorrelation and heteroskedasticity, alongside GRS F-statistic tests for model validation.
The empirical section includes a comprehensive comparison of model fit (adjusted R²), significance of factor loadings, and the cross-sectional explanatory power determined by analyzing intercept terms (alphas).
Core keywords include REITs, Asset Pricing, Fama-French, Carhart, Multifactor Models, Net Profit Margin, and International Real Estate Management.
The study highlights structural differences such as the age of the REIT regimes, leverage ratios, and identifies that while traditional factors work in the US, findings in Japan often differ, particularly regarding the momentum factor.
The model introduces "Net Profit Margin" (NPM) as a new factor to account for firm profitability, aiming to capture systematic risk that standard models might overlook.
The findings provide valuable insights for fund managers, suggesting that asset-specific risk factors are crucial for REIT performance evaluation and that model selection should be mindful of country-specific market dynamics.
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