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COVID-19 has slowed the growth of, the global economy, which has certain practical significance. Consequently, this study seeks to analyze the investment opportunities in the medical sector before and after the COVID-19 outbreak. In this study, the Markowitz mean–variance (MV) model, capital asset pricing model (CAPM), and correlation models are constructed based on the principle of Markowitz MV and correlation analysis. Simultaneously, statistical analysis is used to verify the analysis, and the MATLAB statistical tool is used to build the model. The results show that the actual expected yield of China's medical sector is significantly higher than that calculated by the CAPM before and after the pandemic, and that the investment value of the medical sector is undervalued by the market. From the perspective of risk, China's medical sector has a stable systemic risk premium. Based on the above analysis, when building investment portfolios in the post-pandemic era, investors should appropriately allocate stocks in the medical and pharmaceutical sectors to improve the portfolio income and diversify the investment risk. [ABSTRACT FROM AUTHOR]

Since Markowitz's initial contribution in 1952, portfolio selection has undoubtedly been one of the most challenging topics in finance. The development of online optimization techniques indicates that dynamic learning algorithms are an effective approach to portfolio construction, although they do not evaluate the risk associated with each investment decision. In this work, the performance of the well-known Online Gradient Descent (OGD) algorithm is evaluated in comparison with a proposed approach that incorporates portfolio risk using β control of portfolio assets modeled with the CAPM strategy and considering a time-varying β that follows a random walk. Thus, the traditional OGD algorithm and the OGD with β constraints are compared with the Uniform Constant Rebalanced Portfolio (UCRP) and two specific indexes for the Brazilian market, consisting of small caps and the assets belonging to the Bovespa index. The experiments have shown that β control, combined with an appropriate definition of the β interval by the investor, is an efficient strategy, regardless of market periods with gains or losses. Moreover, time-varying β has been shown to be an efficient measure to force the desired correlation with the market and also to reduce the volatility of the portfolio, especially during hazardous bear markets. [ABSTRACT FROM AUTHOR]

The process of predicting the stock return is considered the main challenge confronting the financial analyst and the investment decision-maker in particular. The objective of the study aims at testing the ability of both CAPM model and APT theory in predicting the stock return. The study investigated a sample of 10 banks listed in the Iraq Stock Exchange for the period (2012-2021). A variety of appropriate statistical and financial means and tools were employed. The study results in many conclusions including the rejection of the study hypotheses and the acceptance of alternative hypotheses based on the analytical results, and then there is a difference in the required rate of return calculated according to each of CAPM model and APT theory as well as the actual return. [ABSTRACT FROM AUTHOR]

The purpose of this article is to investigate the effect of behavioral deviations on the pricing of financial assets with the assumption that sentiment is an important and relevant risk factor in the Iranian capital market. This paper also examines the effect of sentiment, momentum, size, value, and market risk premium by estimating the Multi-Factor Asset Pricing Model (APT). In order to perform empirical analysis, the quarterly returns of companies listed on the Tehran Stock Exchange in the period 2010-2019 in the form of 18 stock exchange groups including 63 listed companies are used. Using two indicators of market turnover sentiment. and sentiment effect. we estimate the sentiment index and by extending the Carhart model and considering two sentiment variables in the form of SAPM model, coefficients estimate by using Hausman-Taylor panel data method. The results of the model show that in the SAPM model, the sentiment variable is very important and significant and have a positive relationship with the average seasonal rate of return of different stock exchange groups.

The Capital Asset Pricing Model (CAPM) makes a significant contribution to understanding the relationship between return and risk and valuing assets in the capital market. The basic idea of the CAPM model is that assets exposed to the same level of systemic risk should have the same level of expected return. Therefore, the CAPM model values the asset, ie. determines its price at a level that ensures that the expected return corresponds to the assumed systemic risk. In addition to the positive aspects of the CAPM model, the paper pays equal attention to understanding the problems and taking into account the shortcomings and limitations that this model faces. The aim of the research is to find an answer to the question of whether the CAPM model is the correct model for valuing financial assets. In this regard, the paper presents numerous pieces of evidence for and against the validity of the CAPM model, concluding that, even after more than half a century of research, no consensus has been reached in the financial literature on the presence or absence of its validity.

This paper examines the ability of beta (β) to measure the systematic risks posed by the COVID-19 crisis and analyzes the impact of the COVID-19 crisis on stock returns for a sample of 50 stocks, grouped on the basis of size and value in the Egyptian Stock Market. CAPM beta of the stock was used to represent the systematic risk stocks, market capitalization was used to construct the large and small stocks portfolios and the book-to-market equity ratio was used to construct high medium and small portfolios. The results showed that systematic risks measured by beta increased after COVID-19 crisis for all sample stocks, the portfolios consisting of stocks with high and medium B/M ratio and the portfolios consisting of small capitalization stocks and big capitalization stocks. However, the COVID-19 crisis has no effect on systematic risks for the portfolio consisting of stocks with low B/M ratio. The results also indicated that stock returns decreased after the COVID-19 crisis for all sample stocks, the portfolios consisting of stocks with low B/M ratio and the portfolios consisting of big stocks. However, the COVID-19 crisis does not affect stock returns for the portfolios consisting of stocks with high and medium B/M ratio and the portfolios consisting of small stocks.

Our paper studies the impacts of the Dieselgate scandal on the required rate of return on equity investments into VW, Daimler, and BMW. The object of investigation is the beta coefficient that determines the risk premium in the Capital Asset Pricing Model (CAPM). Our research takes a deep dive into the developments from the turning point of the scandal (the EPA NOTICE 2015) on September 18, 2015 – when a Notice of Violation of the Clean Air Act was issued to Volkswagen by the EPA – to the end of February 2016. This period also covers FORMAL COMMENCEMENT 2016, when the U.S. Department of Justice first sued Volkswagen on behalf of the EPA. The spillover (contagion) effect of fraudulent practices of VW impacted BMW, Daimler and other companies in the industry that share a similar business model and market segment. Our research of historical market betas has not confirmed the expectation that in the context of the Dieselgate scandal the return required on equity investments into VW, Daimler, and BMW would soar. The Dieselgate scandal proves that the reliability of beta estimates is an inverse function of market volatility. Historical market beta is, therefore, not a good estimate of the required rate of return for the companies in question. [ABSTRACT FROM AUTHOR]

Copyright of Strategy & Development Review is the property of Strategy & Development Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Accounting & Management is the property of Croatian Accountant and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Increase in mutual funds’ popularity makes problem of determination of factors, which influence on investor’s decision up-to-date. Investors usually pay more attention to risk factors and future return based on CAPM or any other model. Aim of this paper is analysis of dependency between common risk factors and future returns and calculation of CAPM model for 147 European mutual funds through artificial neural network.

RESUMEN La creación de fondos de inversión inmobiliaria en Colombia ha abierto posibilidades de diversificación de portafolio a agentes que deseen invertir en el sector inmobiliario sin tener que comprar y administrar finca raíz de forma directa. El comportamiento de estos fondos ha mostrado una rentabilidad promedio superior y una volatilidad menor que la del mercado durante los últimos años. Este artículo aplica el modelo de valoración de activos de capital (CAPM) y estima varios modelos autorregresivos y de heterocedasticidad condicional, con el fin de calcular el beta de estos fondos como una aproximación a la sensibilidad al riesgo sistemático del sector inmobiliario. Los resultados de las estimaciones muestran que el nivel de riesgo del sector inmobiliario se encuentra muy por debajo del riesgo de mercado, lo cual sugiere que los proyectos inmobiliarios tienen un costo de capital mucho menor que el de determinados proyectos en otros sectores.******The creation of property investment funds in Colombia has made portfolio diversification possible by allowing parties to invest in the property sector without buying and managing real estate directly. In recent years, the behavior of these funds has shown higher average profits and lower volatility than that of the market. This study applies the Capital Asset Pricing Model (CAPM) and estimates various autoregressive models and models of conditional heteroscedasticity, in order to calculate the beta of these funds as an estimate of the property sector’s sensitivity to systematic risk. Results show that the risk level of the property sector is far lower than that of the market, suggesting that real estate projects have much lower capital costs than projects in other sectors.

The Capital Asset Pricing Model is a model that describes the relationship between risk, expected return and valuation of securities. The theoretical and practical value of this model has proved unquestionable, but under ideal circumstances. The theory has been utilized by numerous researchers and it confirms the linear relationship between risk and return under the CAPM (Capital Asset Pricing Model) model showing that greater exposure to risk provides higher returns. However, empirical research showed there were numerous factors that CAPM model did not take into account since it is based on assumptions which exist in reality, but are invisible. Therefore, it is very interesting to study the application of the CAPM model on selected shares on the Croatian capital market and analyze the possibilities of its application in discovering the misvalued shares. Share price changes on the Croatian capital market suggest there are some unknown factors that also influence share valuation. There is no doubt that the fundamental analysis of shares is not sufficient for evaluating the real share value in light of various invisible elements and all available information available which affect their value as well.

Capital Asset Pricing Model (CAPM) was introduced through the works of William Sharpe (1964), John Lintner (1965) and Jan Mossin (1966) based on the research of Henry Markovitz. Due to the independent formulation of the model by these three american researchers, there are in the literature references to the Security Market Line (SML) model of financial assets evaluation. CAPM model, revolutionized the financial theory, highlighting the link between the rentability of the individual securities and the rentability of the financial market. The first fundamental hypothesis of the model is that investors are concerned about the expected rentability closely related to the risk associated with it. Consequently, under equilibrium conditions of the financial market, the CAPM model highlights a linear relationship between the expected rentability of the portfolio and the amount of risk assumed by investors.

Copyright of Finance & Business Economies Review is the property of Finance & Business Economies Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Accounting & Management is the property of Croatian Accountant and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The issues of including behavioral biases in the CAPM model were considered in this article. Two types of adjustments to the model were proposed: a premium for sentiment risk and a premium for subjective risk. A correlation model between the stock price, premium for the risk of investing in stocks, stock beta factor, risk-free interest rate, premium for liquidity risk, premium for corporate governance risk, premium for subjective risk and premium for sentiment risk were calculated for stocks of the company circulating in the Russian stock market. The resulting model revealed a linear relationship between the stock price and the premium for the risk of investing in stocks, the premium for corporate governance risk and the premium for sentiment risk. A quantitative interpretation of the investor's behavioral aspects was proposed; the presence of a statistically significant relationship between behavioral aspects and stock price was first tested. The impact of behavioral factors on the stock price was first calculated for a stock circulating in the Russian stock market. [ABSTRACT FROM AUTHOR]

In this study, wavelet analysis as a modern technique in financial and economic issues is used to evaluate capital asset pricing model. For this purpose, using market return, beta coefficient was calculated for daily return of 20 shares selected form Tehran Stock Exchange from March 2007 until March 2012. Then, the relationship between wavelet beta and mean stock return was evaluated on short-term, medium-term and long-term scales using least-squares technique. The findings indicate that the capital asset pricing model is a multi-scale model that uses different time scales for stock returns to provide different estimates of beta. Thus, Tehran Stock Exchange is a very efficient capital market on the long-term scale. Subsequently, values at risk of portfolios were calculated for each scale. According to the result, risk is highly concentrated on high-frequency time series (lower scales).

In investment theory and practice, crucial factor in decision is relation between rate of return and risk. This paper studies the CAPM model that is used to calculate the required rate of return to the certain level of risk. The CAPM model is used to analyze the rate of return visa verse the risk on the Macedonian capital market. But, the analyses do not apply to the whole market portfolio, but rather to the market index of common shares of the Macedonian Stock Exchange (MBI 10). When analyzing the relation between rate of return and risk, the variables that are incorporated in the CAPM model are calculated for a period of about 10 years, for the purpose of obtaining a more realistic value of beta, as a key element in this model. In the period of analysis, it appears one specific feature of the Macedonian capital market concerning that the rate of return of the Macedonian market of securities is low, below the risk free rate in the country, that determines a reverse relationship between the rate of return and risk. [ABSTRACT FROM AUTHOR]

This study investigates the stability of systematic risk of Tehran stock Exchange and a selected group of emerging stock markets including of Latin America, Asian South eastern and Istanbul Stock Exchange. The study uses time series specification of CAPM model (Black et al, 1972) and employs Bai and Perron (2003) structural break point test. The results show that based on Bai and Perron test, there are evidences of structural break in time series CAPM model and hence the instability in systematic risk for Brazil, Chile, Thailand, China, Malaysia and Tehran stock markets. The dynamic estimation results of systematic risk of these stock markets based on MGARCH - BEKK model indicate that, Tehran Stock Exchange has lowest level of systematic risk among other stock markets. The results show that there is significant fluctuation in dynamic trend of systematic risk of these stock markets in particular around structural break point dates. Based on the results, the BEKK model has more accurate performance than linear time series CAPM model for systematic risk forecasting proposes. These results provide useful policy guideline for investors in international risk management.