Multifactor Assets Pricing Model

Multifactor Assets Pricing Model
Author: Khushboo Sagar
Publisher:
Total Pages: 20
Release: 2020
Genre:
ISBN:

Generous consideration has been pursued to the empirical testing of multi factor assets pricing models. However, literature provides mixed kind of evidences in the support of multi factor assets pricing model. This study reviews 20 research articles based on multi factor assets pricing model and examines 25 research papers based on the empirically testing of multi factor assets pricing model published during 2001 and 2018 to study the multi factor assets pricing model in the Indian context as well as foreign context. CAPM is a popular normative model used by researchers to explain the relationship between risk and expected return of a risky asset which was developed by Sharpe (1964) and Lintner (1965). This model takes only one risk factor which is the excess market portfolio return (Market premium). Because of poor performance of CAPM in explaining realized returns, the Fama and French three factor asset pricing model (1993) was developed. Fama and French (1993) documented the size effect and the value effect that were not included in the CAPM, generally known as CAPM anomalies. Mark M. Carhart (1997) developed the Carhart four factor model. It is an extension of the FF three factor model with one another factor i.e. momentum factor effect for asset pricing of stocks. In view of the limitations of the earlier three-factor model, Fama and French five-factor asset pricing model (2014) was developed. Fama and French (2014) came with profitability pattern and investment pattern in average stock return along with the market premium, size premium and value premium. This paper may be an expedient source of information to the academics, financial analyst and researchers to understand the asset pricing model.

Asset Pricing Factor Models in the German Stock Market

Asset Pricing Factor Models in the German Stock Market
Author: Julian Fischer
Publisher: GRIN Verlag
Total Pages: 109
Release: 2021-06-14
Genre: Business & Economics
ISBN: 3346420094

Master's Thesis from the year 2021 in the subject Business economics - Investment and Finance, grade: 1,7, University of Hannover (Institut für Finanzwirtschaft und Rohstoffmärkte), language: English, abstract: In this paper, we examine how various modern multifactor models, such as the Carhart factor model, five-factor model and its complement six-factor model by Fama and French, the q-factor model by Hou, Wue and Zhang, and the mispricing factor model by Stambaugh and Yuan perform in the German stock market. It is discernible that, depending on the application model, like factor spanning tests, different sortings, return anomalies, sector- and equity fund investigation, they often provide quite similar explanatory power, while in individual cases sometimes one and sometimes the other model performs better. The underlying factors contribute differently to the explanatory power depending on the time period. Thus, in case of doubt, the six-factor model is preferable, as it is the most versatile model. Since the establishment of the capital asset pricing model as a cornerstone of modern capital market theory in the 1960s, new investigations and studies have been built on this model on an ongoing basis. This continuously leads to extensions and modifications of the asset pricing models since then. These models can be used in various ways, for example to explain the pricing of risky financial assets under restrictive assumptions or to gain important insights into the relationship between expected return and risk of securities. These can be used in various ways, for example to explain the pricing of risky financial assets under restrictive assumptions or to gain important insights into the relationship between expected return and risk of securities. In this paper, we aim to answer the overarching research question of how modern asset pricing models perform for the German stock market. For this purpose, we first discuss the characteristics of the German stock market, followed by the milestones of the development of factor models, their empirical evidence and their factors, as well as internationally known return anomalies. In the subsequent part, five modern asset pricing models are tested in different scenarios of the German stock market, including factor spanning tests, different sortings, anomalies, sectors and in equity funds. For this purpose, various analytical methods are used and performed with the software “Stata”. Finally, the comprehensive results are summarized and concluded.

Multifactor Models Do Not Explain Deviations from the CAPM

Multifactor Models Do Not Explain Deviations from the CAPM
Author: Archie Craig MacKinlay
Publisher:
Total Pages: 52
Release: 1994
Genre: Capital
ISBN:

A number of studies have presented evidence rejecting the validity of the Capital Asset Pricing Model (CAPM). This evidence has spawned research into possible explanations. These explanations can be divided into two main categories - the risk based alternatives and the nonrisk based alternatives. The risk based category includes multifactor asset pricing models developed under the assumptions of investor rationality and perfect capital markets. The nonrisk based category includes biases introduced in the empirical methodology, the existence of market frictions, or explanations arising from the presence of irrational investors. The distinction between the two categories is important for asset pricing applications such as estimation of the cost of capital. This paper proposes to distinguish between the two categories using ex ante analysis. A framework is developed showing that ex ante one should expect that CAPM deviations due to missing risk factors will be very difficult to statistically detect. In contrast, deviations resulting from nonrisk based sources will be easy to detect. Examination of empirical results leads to the conclusion that the risk based alternatives is not the whole story for the CAPM deviations. The implication of this conclusion is that the adoption of empirically developed multifactor asset pricing models may be premature.

Empirical Analysis of Multifactor Asset Pricing Models. A Comparison of US and Japanese REITs

Empirical Analysis of Multifactor Asset Pricing Models. A Comparison of US and Japanese REITs
Author: Tim Perschbacher
Publisher: GRIN Verlag
Total Pages: 146
Release: 2023-07-10
Genre: Business & Economics
ISBN: 3346903400

Bachelor Thesis from the year 2021 in the subject Business economics - Investment and Finance, grade: 1,0, , language: English, abstract: This study is concerned with an empirical analysis of asset pricing. More specifically, this paper examines whether multifactor asset pricing models are able to explain variation in REIT returns in the US and Japan. In addition to traditional multifactor models, an Alternative Four-Factor Model (AFF) was developed considering net profit margin as an additional risk factor. Thence, this paper seeks to provide valuable information for investors and fund managers regarding their indirect real estate investment selection. Using a sample period between July 1994 (US) / July 2011 (Japan) to December 2020, rigorous multiple-time-series regression is applied to calculate factor loadings for each risk factor and the corresponding alpha values of each model to evaluate their effectiveness in explaining variation and cross-section of REIT returns. Most studies on asset pricing models focus on size and value sorted portfolios as dependent variables. This paper broadens the approach with four other double sorted test portfolios to check the robustness of each single factor to explain return anomalies. Results show that market premium and size premium represent risk factors for US-REITs, whereas market premium and value premium are suitable risk factors for Japanese-REITs. The momentum factor does not capture risk and is insignificant in both markets. The study shows low correlations between traditional and REIT specific as well as between US and Japanese risk factors. This suggests that firstly risk factors are country specific and secondly that they are asset specific. Moreover, the Fama-French Three-Factor Model (FF3) clearly outperforms the CAPM, while the Carhart Four-Factor Model (CH4) marginally improves the explanatory power over the FF3. This is observed in both markets. Outcomes demonstrate that the Alternative Four-Factor Model (AAF) does not improve prediction power for returns of Japanese-REITs compared to the FF3 and CH4. On the contrary, results are ambiguous concerning US-REITs. While the additional risk factor, net profit margin, generates a negative return, the model is superior to the FF3 and CH4 in terms of explaining variation and cross-section of returns.

Multifactor Consumption Based Asset Pricing Models Using the US Stock Market as a Reference

Multifactor Consumption Based Asset Pricing Models Using the US Stock Market as a Reference
Author: John Hunter
Publisher:
Total Pages: 19
Release: 2014
Genre:
ISBN:

In this paper we extend the time series analysis to the panel frame-work to test the C-CAPM driven by wealth references for developed countries. Speciጿically, we focus on a linearised form of the Consumption-based CAPM in a pooled cross section panel model with two-way error components. The empirical fiijndings of this two-factor model with various speciጿications all indicate that there is signiጿicant unobserved heterogeneity captured by cross-country ጿixed effects when consumption growth is treated as a common factor, of which the average risk aversion coefficient is 4.285. However, the cross-sectional impact of home consumption growth varies dramatically over the countries, where unobserved heterogeneity of risk aversion can also be addressed by random effects.

Asset Pricing in Emerging Markets

Asset Pricing in Emerging Markets
Author: Shabir Ahmad Hakim
Publisher:
Total Pages: 678
Release: 2015
Genre: Capital assets pricing model
ISBN:

Emerging markets are associated with developing economies and are structurally different from the developed markets. They offer higher expected returns as they are experiencing higher growth rates and potential for diversifying the risk in global portfolios as they are partially integrated with the developed markets. However, the structural differences coupled with partial integration limit the capability of the asset pricing models, originally designed for the developed markets, to capture risk and return dynamics of the assets in these markets and necessitate customization of the models to the local settings. Many asset pricing studies undertaken in this direction supplement the factors in developed market models with the factors that are unique to the emerging markets. However, the models have limited scope in explaining asset returns due to limited explanatory power of the factors included. This study proposes a multifactor asset pricing model with nine explanatory factors, which include returns on the local and global market portfolios, exchange rate, and returns on six mimicking portfolios that proxy for the common sources of risks associated with size, book to market value of equity, market liquidity, leverage, quality of earnings, and asset liquidity of firms. The last three factors in the model have not been tested in the emerging markets; among these, asset liquidity is introduced as an explanatory factor in asset pricing in this study. The model is tested in seven emerging markets, namely China, India, Indonesia, Malaysia, Thailand, South Africa, and Brazil using ten-year monthly data on non-financial firms over period of January 2004 to December 2013. Generalized method of moments (GMM) is applied for data analysis and model testing. The findings of the study reveal that the local market portfolio is the most dominant factor in all the markets. It subsumes the effects of the global market portfolio and the exchange rate in most of the markets. In addition, consistent cross-country behaviour of size related factor is observed in explaining returns on small and medium portfolios, and of book to market value of equity related factor in explaining returns on high book to market value portfolios. Other factors in the model exhibit different behaviours in different markets indicating presence of idiosyncrasies in the common sources of risks that drive returns in these markets. The newly introduced asset liquidity factor has strong impact on stock returns in four markets: India, Indonesia, Malaysia and South Africa. Furthermore, the new to emerging markets factors leverage and quality of earnings have noticeable influence on stock returns in two markets each; leverage in India and Malaysia, and quality of earnings in China and Brazil. The observed behaviour of the model in the markets studied mirrors the behaviour expected of asset pricing models in emerging markets, which are partially integrated with one another and are in different stages of economic lifecycle.