Asset Pricing Model Research Articles

Capital Asset Pricing Model (CAPM) 2.0: Account of Business and Financial Risk

The famous Capital Asset Pricing Model (CAPM), widely used in practice, takes into account only the business risk associated with investments in a specific company [not the entire market (or industry)]. In practice, most listing companies use debt financing and operate at a non-zero leverage level. This means that the financial risk associated with the use of debt financing, along with business risk, must be taken into account. The purpose of this paper is to simultaneously account for business and financial risk. We combined the CAPM theory and the Modigliani-Miller (MM) theory, which is the perpetual limit of the BFO (Brusov-Filatova-Orekhova) theory. The article shows that R. Hamada’s attempt to take into account both business and financial risks has proved unsustainable, and the formulas he obtained, widely used in practice, are incorrect. The paper outlines the correct formulae that made it possible to generalize CAPM for the first time, taking into account both business and financial risk. The application of the new CAPM 2.0 model to a number of companies is considered and the difference between the results obtained within the framework of CAPM 2.0 and CAPM is demonstrated. CAPM is one of the main models [along with APT (arbitrage pricing theory) and WACC] within the income approach to business valuation. This significantly increases the value of the developed CAPM 2.0 approach, which can significantly improve the accuracy of the assessment.

The Importance of Risk Preference Parameters in Prospect Theory: Evidence from Mutual Fund Flows

In this paper, we use the well-documented mutual fund flow-performance relationship to infer information about investors’ preferences. We show that applying preference parameter values from experimental settings to market data can significantly understate the role of prospect theory in explaining investor behavior. We find evidence that mutual fund investors exhibit loss aversion and differential attitudes toward risk over losses (risk-seeking) and gains (risk-averse) but no significant probability weighting when evaluating fund performance. Our results apply more strongly to retail funds compared to institutional funds, consistent with the view that prospect theory is more relevant for retail investors. Finally, we show that, for parameter values that best explain fund flows, prospect theory outperforms the global risk aversion framework and widely-used asset pricing models in explaining investors’ responses to fund performance.

Advancing portfolio optimization: The convergence of machine learning and traditional financial models

This paper delves into the transformative impact of machine learning (ML) on portfolio optimization, showcasing how ML algorithms can significantly enhance traditional financial models such as the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT). Through a comprehensive examination of regression analysis, classification algorithms, and reinforcement learning, we illustrate the methodologies by which ML refines the prediction of asset returns, assesses investment risks, and dynamically adjusts portfolio allocations. We discuss the integration of ML with CAPM and APT to improve the estimation of systematic risk and identify multi-factor influences on asset returns, offering a more nuanced approach to optimizing portfolios. Additionally, the paper highlights the role of big data in augmenting predictive accuracy and the application of optimization algorithms like Gradient Descent and Genetic Algorithms in achieving optimal asset allocations. By addressing challenges such as multicollinearity and overfitting, we demonstrate the potential of ML to revolutionize investment strategies, enabling more sophisticated risk management and return maximization. This study not only underscores the synergy between ML and traditional financial theories but also paves the way for future innovations in financial analytics.

Valuation and pricing of equity securities: A test of CAPM in a developing market economy

The study is on valuation and pricing of equity securities. A test of CAPM in a developing market economy (2006-2020) The major aim of the study is to investigate the capability and relevance of CAPMt to equity prices in Nigeria stock market from 2006-2020 and show if the model empirical findings are in line with results obtained from the developed markets. The model concerned in the study is Capital asset pricing model (CAPM) by Sharp 1962. from (2006-2020) Using a sample of 62 companies derived from the eleven major sectors of the Nigeria economy and Using panel data analysis and valuation status analysis results showed that, CAPM demonstrated positive and in significant impact on stock return(RI) of the Nigeria stock market. These variables do not play role on explaining the movement in the value of stock return of the selected firms within the period, The result of the relationship between actual stock return (RI) and models calculated return obtained is dominated by under valuations and over valuations with few appropriately valued stocks which are insignificant in nature, again the r2 and coefficient of determination < 1 or even negative in some cases .p value >0.05, and the result obtained in Nigeria is not the same with that of the developed economy. It is therefore recommended that, portfolio managers and other financial analysts should not adopt CAPM, as a tool to examine, explain. predict or assess accurately return of stocks traded in the Nigeria stock market.

Democracy and stock market returns

AbstractIn this article, we empirically examine the relation between democracy level and stock index returns in a sample of 74 countries. Compared with democracies, autocratic states are characterized by lower returns despite exhibiting higher return volatility. Even though this higher volatility can be mostly attributed to diversifiable country‐specific risk, the capital asset pricing model cannot explain the return differential. Instead, it is the level of investor protection that can fully account for the phenomenon described here. Autocratic leaders may be reluctant to promulgate regulations shielding investors, and the resultant expropriation depresses the returns realized by outsiders.

Deep factor asset pricing with policy guidance based on multi-source heterogeneous information

We propose a novel latent factor pricing model to extract latent pricing factors and corresponding factor loadings from multi-source heterogeneous information through a deep learning architecture. Notably, we pioneer the extraction of policy pricing factors from China’s national strategies (“Five-Year Plans”, “Government Work Reports”, and “Monetary Policy Reports”) using natural language processing and a dynamic topic model. The proposed mixed-frequency deep factor asset pricing (MIDAS-DF) model learns from mixed-frequency heterogeneous data and captures nonlinear joint patterns between inputs and outputs, providing more nuanced insights into asset pricing. The empirical analyses of the Chinese A-share market from January 1, 2003 to July 31, 2022 show that the MIDAS-DF model outperforms competing models in pricing individual stocks, various test portfolios, and investment portfolios. The results also demonstrate that low-frequency policy information anchors long-term pricing trends, while high-frequency market and sentiment information refine short-term pricing accuracy. They work together to enhance the pricing performance.

Financial Integration of the European, North America, Asiatic and Japanese stock markets from 2003 to present times

We apply an integration/segmentation analysis between the European (EU) market and the North America stock market (US and Canada), the Asian Stock Market (AS) and the Japanese (JP) market. The analysis is carried out from 2003 until the present time. We apply the Jorion and Schwartz (1986) methodology and extend the work of Brooks et al. (2009) using a simpler Capital Asset Price Model (CAPM) and the Market return downloaded from the Fama French website for the time period analysed. Our results in this empirical study show integration between the European portfolios and the US stock market and the Asian Portfolios and the US stock market in the full time period analysed. Although the methods applied in this paper have been already introduced in the literature, this is the first time that they are applied systematically to compare the integration and segmentation between different economies and a given portfolio set. This systematic approach helps to establish the conclusiveness of their forecasts.

On the importance of asset pricing factors in the relative valuation

In this study, we examine the implications of multi-factor asset pricing models in corporate valuation, focusing on the relative valuation approach. Our investigation centers around an eight-factor model, which we compare against traditional valuation methods that rely on industry or risk grouping and cross-sectional averages. The purpose of this comparison is to assess the efficacy of incorporating pricing factor variables into the valuation process and to understand their impact on valuation accuracy. The findings of our analysis suggest that the use of the eight-factor model leads to a reduction in estimation errors of valuation multiples, indicating an important improvement in precision compared to conventional valuation methods. Additionally, our research offers insights into the practicality of applying multi-factor models. It contributes to the intersection between empirical asset pricing and corporate finance by providing a detailed evaluation of advanced valuation models and their relevance in improving the accuracy of relative valuation.

Implementasi Metode Capital Asset Pricing Model (CAPM) Sebagai Penetapan Keputusan Investasi Saham Berdasarkan Undervalue dan Overvalue (Studi pada Sektor Perbankan di BEI Periode 2018-2022)

The study aims to implement the CAPM (Capital Asset Pricing Model) method in undervalued and overvalued equity investment decisions in the banking sector in the EIB during the period 2018-2022. This research method uses descriptive quantitative methods. The data source used is secondary data of the closing price per month of the Bank listed on the Indonesian Stock Exchange and the Financial Services Authority during the period June 2018 s/d December 2022. Sampling using purposive sampling technique of 5 National Private Public Bank (BUSN) Devisa. The results of this study showed that of the 5 shares of the company that were the sample of the research, 1 company shares became undervalue, namely the company of the Bank of Jewelry (BNLI) where the rate of return of individual shares is greater than the expected return, while 4 other companies were included in the overvalue shares: Bank Central Asia (BBCA), Bank Pan Indonesia (PNBN), Bank CIMB Niaga (BNGA), and Bank OCBC NISP (NISP) whose individual share return rate is smaller than its expected return.

Is Long‐Run Risk Really Priced? Revisiting Liu and Matthies (2022)

ABSTRACTThe claim by Liu and Matthies (LM) that their macro news risk factor (NI) prices 51 portfolios (associated with four different portfolio groups) is not appropriate. In fact, their single‐factor model is successful only in explaining the momentum deciles, while producing strongly negative performance for the remaining groups. The pricing performance is more doubtful in the case of the alternative news factor (HNI), as the respective risk price is not identified. LM's conclusions stem from a combination of questionable empirical choices and misinterpretation of their results. Moreover, the NI model cannot explain prominent capital asset pricing model anomalies not considered in their study.

Geopolitical risk and the dynamics of REITs returns

The aim of this study is to analyze the relative importance of geopolitical risk (GPR), as introduced by Caldara and Iacoviello (2022), on the dynamics of U.S. REITs returns. Using an extended conditional version of Fama and French (1993)’s capital asset pricing model, we highlight the role played by GPR and its two components, geopolitical acts (GPA) and geopolitical threats (GPT), on the expected returns of securitized real estate. Our robust results report the level and the significant of the geopolitical risk metrics on the decomposition of REITs returns grouped into different portfolios (from CRSP/Ziman series). We shed light on the link between the characteristics of REITs and the relative importance of geopolitical risk during the last decades.

Testing and Ranking of Asset Pricing Models Using the GRS Statistic

Testing and Ranking of Asset Pricing Models Using the GRS Statistic

Analysis of Capital Asset Pricing Model in Chinese Stock Market

Analysis of Capital Asset Pricing Model in Chinese Stock Market

Investigating the Relationship Between Environmental, Social, and Governance Factors and the Capital Asset Pricing Model

This study delves into the intricate relationship between the Capital Asset Pricing Model (CAPM) and Environmental, Social, and Governance (ESG) factors in the investment landscape. Through an extensive review of existing literature and comparative analyses, the paper uncovers the historical development of CAPM, the rise of ESG considerations, and their convergence in modern financial theory. The research aims to shed light on the ongoing debates surrounding integrating ESG factors into the CAPM framework, revealing both supportive and critical viewpoints. Through a critical evaluation of empirical studies, the paper identifies gaps in the current body of knowledge, emphasizing the need for further research to understand the interplay between ESG factors and CAPM. The study concludes that while ESG considerations have increasingly influenced investment decisions, their precise relationship with traditional financial models, such as CAPM, remains an area ripe for exploration.

A consumption-based term structure model of bonds and equity

In this study, I propose a consumption-based asset pricing model to capture the dynamic properties of term structures of bonds and equity. I extend the long-run risks model by introducing a mean-reversion of dividend growth and the external habit formation of a representative agent. The mean-reverting dividend growth generates a negative equity term premium, while the habit formation augments the equity premium and renders an upward-sloping bond yield curve, on average. In addition, fluctuations in the surplus consumption ratio and the conditional variance of consumption growth allow the model to reproduce pro-cyclical variations in bond and equity yield spreads and counter-cyclical variations in bond and equity term premiums, as observed in the U.S. data.

The effects of the Russia–Ukraine war and the Wagner Group coup on defense stocks in Europe: an event study analysis

Purpose This study aims to examine the impact of the beginning of the Russia–Ukraine war and the Wagner Group’s attempted military coup against Putin’s regime on the European defense sector, consisting of weapons manufacturers. Design/methodology/approach The authors use the event study methodology to quantify the impact. That is, the authors assume that markets are efficient, and abnormal stock returns around the event dates capture the magnitudes of the impacts of the two events studied on European defense sector companies. The authors use the capital asset pricing model and two different multifactor models to estimate expected stock returns, which serve as the benchmark necessary to obtain abnormal returns. Findings The start of the war on February 24, 2022, when the Russian forces invaded Ukraine, was followed by high positive abnormal returns of up to 12% in the next few days. The results are particularly strong if multiple factors are used to control for the risk of the defense stocks. Conversely, the authors find a negative impact of the rebellion initiated by the mercenary Wagner Group’s chief, Yevgeny Prigozhin, on June 23, 2023, on the abnormal returns of defense industry stocks on the first trading day after the event. Originality/value To the best of the authors’ knowledge, this is the first study of the impact of the Russia–Ukraine war on the defense sector. Furthermore, this is the first study to measure the financial implications of the military coup initiated by the Wagner Group. The findings contribute to a rapidly growing literature on the financial implications of military conflicts around the world.

Impact of Firm Size and Systematic Risk on Stock Returns in Companies of Different Industries

Purpose: The study explores the relationship between firm size, systematic risk, and stock returns across various industries. The purpose of the study is to analyze how these factors influence stock returns and to provide insights for investors and financial analysts. The theoretical framework is based on the Capital Asset Pricing Model (CAPM) and existing literature on firm size, systematic risk, and stock returns.  Methodology: The research methodology involves quantitative analysis using financial data from companies in different industries. Variables such as firm size, systematic risk, and stock returns are measured and analyzed using statistical techniques and models. The study aims to uncover patterns and relationships that can help in understanding the dynamics of stock returns in diverse industry settings.  Findings: The findings of the study reveal significant correlations between firm size, systematic risk, and stock returns. Larger firms tend to exhibit lower systematic risk and higher stock returns compared to smaller firms. The analysis also highlights industry-specific variations in the impact of firm size and systematic risk on stock returns, suggesting that industry dynamics play a crucial role in shaping investment outcomes.  Originality: This study contributes to the existing literature by providing empirical evidence on the relationship between firm size, systematic risk, and stock returns in companies across different industries. The originality of the work lies in its comprehensive analysis of these factors and its implications for investment decision-making.

Empirical Analysis of Stock Patterns in the Hong Kong Stock Market Based on Asset Pricing Models and Prospect Theory

COVID-19 impacts hundreds and thousands of people globally while increasing volatility in the Hong Kong stock market, Asia’s financial hub. This paper aims to investigate whether prospect theory and COVID-19 can help illustrate variations in stock returns on the market based on asset pricing models. The empirical findings demonstrate that the pandemic triggers volatility in the Hong Kong stock market. The return of Portfolios is highly correlated to Hong Kong’s broad stock market. Five factors of Fama French models help improve the model’s performance by capturing cross-sectional anomalies such as firms’ size, profitability, etc. Prospect theory reinforces the accuracy of the model’s prediction, although explanatory power is minimal. Stocks with the highest previous monthly returns have higher returns in the current month. Momentum exists in the Hong Kong stock market, particularly stocks with large market capitalization. Value-weighted portfolios perform better than equal-weighted. Asset pricing models reach precise results because of R-square and are applicable to reflect stock returns’ patterns in the Chinese stock market.

Analyzing the Risk-Return Trade-Off Relationship of Chinese New Energy Firms Using the Capital Asset Pricing Model

This study examines the risk-return trade-off for prominent Chinese new energy companies within the context of the country's burgeoning sustainable energy sector. Utilizing the Capital Asset Pricing Model (CAPM), the paper investigates the systematic risk factors impacting the stock returns of BYD, CATL, and Sungrow, which are leaders in the electric vehicles, energy storage, and photovoltaic sectors, respectively. The research highlights the unique beta coefficients indicative of each company's market volatility and explores the implications of these risk profiles for investors and policymakers. While the findings suggest the presence of abnormal returns and provide valuable insights for investment strategies and policy formulation, the paper acknowledges limitations in market-based risk assessment and suggests future research to incorporate a broader range of company-specific factors and comparative analyses. This study contributes significantly to understanding the complexities and dynamics of risk management in China's rapidly advancing new energy market.

Assessing the Impact of the COVID-19 Pandemic on the Risk-Return Profile of the U.S. Aviation Sector

The COVID-19 pandemic precipitated unparalleled disruptions in the aviation sector, prompting a critical evaluation of the risk-return dynamics within the industry. This investigation focuses on the stock performance of seven prominent U.S. aviation entities, encompassing both manufacturers and airline operators. Employing the Capital Asset Pricing Model (CAPM), the study juxtaposes pre- and post-pandemic financial data to discern the pandemic's fiscal ramifications. The results unearth a dichotomous impact: while manufacturers with defense contracts like Lockheed Martin exhibited stability, commercial airlines such as American Airlines grappled with significant setbacks due to decreased travel. The analysis yields insights into the industry's differential responses to the crisis and highlights the necessity for adaptable strategies in mitigating economic volatilities. This research not only sheds light on the pandemic's immediate effects but also underscores the enduring need for resilience in aviation finance.