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The capital asset pricing model (CAPM) is a foundational asset pricing model that is widely applied and holds particular significance in the globally influential Chinese stock market. This study focuses on the banking sector, enhancing the performance of the CAPM and further assessing its applicability within the Chinese stock market context. This study incorporates a heterogeneous autoregressive (HAR) component into the CAPM framework, developing a CAPM-HAR model with time-varying beta coefficients. Empirical analysis based on high-frequency data demonstrates that the CAPM-HAR model not only enhances the capability of capturing market fluctuations but also significantly improves its applicability and predictive accuracy for stocks in the Chinese banking sector. [ABSTRACT FROM AUTHOR]

The present study aimed to assess the relationship between corporate governance factors and stock returns based on the capital asset pricing model and the Fama and French three-factor model. The statistical population included companies acting in the Istanbul Stock Exchange from 2010 to 2020. Using a systematic elimination sampling method, 70 companies were selected. The data panel method was used along with two-stage regression of Fama and Macbeth [16] and EViews11 software to estimate the models. The results represented a significant and positive relationship between the level of transparency in information disclosure, the structure of the directors' board, and the structure of ownership and shareholders' rights with stock returns based on the capital asset pricing equation. Moreover, there was a significant and positive relationship between the general index of corporate governance and the stock returns of companies based on the three-factor equation of Fama and French. This index is comprised of three sub-indices. [ABSTRACT FROM AUTHOR]

Introducción/objetivo: este estudio analiza el rendimiento ajustado al riesgo de las criptomonedas más populares en comparación con el índice S&P 500, utilizando el Alpha de Jensen para evaluar si estas superan el rendimiento ajustado por riesgo en el periodo 2019-2023. Objetivo: examinar el rendimiento ajustado al riesgo de Bitcoin, Ethereum, Tether y Binance frente al S&P 500, determinando su capacidad para superar el mercado mediante el Alpha de Jensen. Metodología: se empleó un enfoque cuantitativo descriptivo, calculando rendimientos logarítmicos diarios, estimando el beta de las criptomonedas, aplicando el modelo CAPM para rentabilidades ajustadas por riesgo y utilizando el Alpha de Jensen para evaluar la compensación del riesgo. Resultados: las criptomonedas presentaron mayor volatilidad y rendimientos extremos en comparación con el S&P 500, mostrando diferencias significativas en su capacidad para compensar el riesgo. Conclusiones: a pesar de su alta volatilidad, Ethereum y Binance lograron compensar el riesgo de manera adecuada, mientras que Bitcoin evidenció una capacidad menos consistente y Tether no logró compensarlo. Estos resultados subrayan la importancia de estrategias de inversión adaptativas en el dinámico mercado de criptomonedas. ABSTRACT:Introduction: this study analyzed the risk-adjusted performance of the most popular cryptocurrencies compared to the S&P 500 index, using Jensen’s Alpha to determine whether these assets outperformed on a risk-adjusted basis during the 2019–2023 period. Objective: the research aimed to evaluate the risk-adjusted performance of Bitcoin, Ethereum, Tether, and Binance relative to the S&P 500, assessing their ability to outperform the market using Jensen’s Alpha. Methodology: the study employed a quantitative descriptive approach by calculating daily logarithmic returns, estimating the Beta of cryptocurrencies, applying the CAPM model for risk-adjusted returns, and utilizing Jensen’s Alpha to measure risk compensation. Results: the findings revealed that cryptocurrencies exhibited higher volatility and extreme returns compared to the S&P 500, with significant differences in their ability to compensate for risk. Conclusions: despite their high volatility, Ethereum and Binance successfully compensated for risk, while Bitcoin displayed less consistent performance, and Tether failed to provide adequate risk compensation. These findings underscore the importance of adaptive investment strategies in the dynamic cryptocurrency market.

The legislative framework on territorial and urban planning has become increasingly rich and complex in the European Union, particularly Italy. The structured – and often hindering – system of division of responsibilities between the central State, Regions, local institutions, and organisms generates different levels of administrative verification. The environmental and landscape constraints by which each Public Administration with jurisdiction over the territory exercises its powers strongly impact territorial management and negatively affect investments. Over the years, this has been one of the main reasons behind the significant dilation of the risk and the time required to obtain the necessary authorizations to start construction, producing “business risk.” Based on this premise, this work presents a methodological investigation of the relationships between environmental and landscape constraints, the regulatory framework involving the building, and its Market Value. This is finally aimed at finding suitable methods and procedures to formulate a reasonable discount rate considering the constraints and the related regulations that operate on an asset. A multi-step method integrating the Capital Asset Pricing Model, Analytic Hierarchy Process, and Delphi Method is proposed to assess the discount rate component related to urban risk.

This study aims to provide guidance to investors in identifying efficient and inefficient stocks, as well as evaluating stocks that have an optimal balance between return and risk using the Capital Asset Pricing Model (CAPM). The CAPM method is used to predict the return of risky securities and as a benchmark in assessing the level of investment returns. By implementing CAPM, investors can make more informed and strategic investment decisions in portfolio management. This study uses a purposive sampling technique to select samples, where the specific criteria are companies listed on the Indonesia Stock Exchange and consistently included in the IDX30 stock index in the 2020-2023 period. Selection is made based on stock efficiency, where individual returns are greater than expected returns (Ri>ERi). There is a linear relationship between systematic risk and expected returns, where stocks that have a high beta value, the expected return will also be high, and vice versa. Of the 16 stocks analyzed, 7 company stocks are included in the efficient stock category, namely ADRO, ANTM, BBCA, BBNI, BBRI, BMRI, and UNTR, while the other 9 stocks are included in the inefficient category. The results of this study are expected to provide insight to investors in selecting efficient stocks for optimal investment decision-making.

Investment is an activity related to the economic and business world. Investment actions can meet future financial needs where the invested funds gain returns after a certain period. Investors with broad insights significantly influence investment decisions. This study aims to analyze the comparative calculation of investment return rates between three models, namely Single Index Model (SIM), Capital Asset Pricing Model (CAPM), and Arbitrage Pricing Theory (APT), in eight mining company sectors listed on the Indonesia Stock Exchange (IDX 30). This study uses historical data from the mining company sectors to calculate and compare the investment return rates based on these three models. The research method used is statistical analysis to evaluate and compare the predicted investment return rates from the Single Index Model (SIM), Capital Asset Pricing Model (CAPM), and Arbitrage Pricing Theory (APT). The data used includes historical stock prices, company financial data, and relevant market data. The results of this study are expected to provide a better understanding of the effectiveness and advantages of each model in the context of mining companies listed on IDX 30. The results of this study show that the Single Index Model (SIM) indicates a moderate financial potential with an average value of 7,58, which is lower compared to CAPM. A high risk (beta) of 2,20 indicates that this investment has a higher risk than the market. On the other hand, the Capital Asset Pricing Model (CAPM) has a higher average return value of 19,15, indicating greater profit potential but also commensurate risk. The Arbitrage Pricing Theory calculation of 6,46, the lowest, reflects a more cautious calculation of return estimates. The inflation beta risk value of 100.924,50 and the deposit interest beta risk of 9.320,14 are very high. [ABSTRACT FROM AUTHOR]

This study investigates the ESG performance–systemic risk (SR) nexus among Indian companies. Using the beta coefficient from the Capital Asset Pricing Model (CAPM) and statistical analysis, it explores how ESG performance affects SR. The findings reveal that firms with higher ESG scores have lower SR sensitivity. Notably, there is a significant difference in risk sensitivity between high- and low-ESG-rated companies, with ESG effects being less pronounced in high-cap firms compared to low-cap firms. Conversely, large firms, older firms, and those with lower borrowing costs show a diminished effect of ESG ratings on their SR sensitivity. These results underscore the importance of firm-specific characteristics in determining the efficacy of ESG strategies in risk mitigation. This study reveals that ESG performance reduces SR, with market valuation affecting this relationship. [ABSTRACT FROM AUTHOR]

The legislative framework on territorial and urban planning has become increasingly rich and complex in the European Union, particularly Italy. The structured – and often hindering – system of division of responsibilities between the central State, Regions, local institutions, and organisms generates different levels of administrative verification. The environmental and landscape constraints by which each Public Administration with jurisdiction over the territory exercises its powers strongly impact territorial management and negatively affect investments. Over the years, this has been one of the main reasons behind the significant dilation of the risk and the time required to obtain the necessary authorizations to start construction, producing “business risk.” Based on this premise, this work presents a methodological investigation of the relationships between environmental and landscape constraints, the regulatory framework involving the building, and its Market Value. This is finally aimed at finding suitable methods and procedures to formulate a reasonable discount rate considering the constraints and the related regulations that operate on an asset. A multi-step method integrating the Capital Asset Pricing Model, Analytic Hierarchy Process, and Delphi Method is proposed to assess the discount rate component related to urban risk. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative web application leveraging the Capital Asset Pricing Model (CAPM) to revolutionize financial analysis. As a cornerstone of modern financial theory, CAPM offers a systematic framework for managing portfolio risk and predicting expected returns. In addition to harnessing CAPM principles, the presented web application integrates advanced functionalities tailored to the intricate demands of academics, analysts, and financial researchers. This research endeavor unveils a cutting-edge web application that harnesses the power of CAPM for exhaustive financial analysis and portfolio optimization. Developed with Plotly and Streamlit, the application provides users with an intuitive and immersive platform to assess the performance of individual stocks about the S&P 500 index. Central to its functionality is the capability to explore historical stock data, unveiling temporal trends and correlations, facilitated by seamless data retrieval and visualization. Furthermore, the application facilitates equitable performance evaluations by standardizing stock prices, thereby offering a uniform scale for evaluating asset volatility and growth. This tool represents a significant leap forward in financial analysis, empowering users with more strategic investment insights and fostering a profound comprehension of market dynamics by seamlessly integrating traditional financial models with state-of-the-art web technologies. Through the utilization of the online application and CAPM, the study endeavors to prognosticate Return on Investment (ROI) and Risk of Investment (Beta) for various equities linked to the S&P 500, thereby facilitating informed decision-making and optimized portfolio management. [ABSTRACT FROM AUTHOR]

The valuation of banks is inherently complicated because of the uncertainties arising from their information opaqueness and inherent risks. Unlike non-banking firms, banks require specialised equity-side valuation approaches. This study addresses a gap in the literature by examining valuation methods used by bank equity researchers. The study used a total of 201 reports on South African banks (2018–2023), 56 reports on Nigerian banks (2018–2023), and 27 reports on Kenyan banks (2018–2023) to investigate the bank equity valuation methods utilised by analysts in the employ of Investec Ltd. and Standard Bank Group Ltd. The study's findings show that Investec's South African analysts predominantly used the warranted equity method, based on book value (BV), and return on equity (ROE), for valuing shares throughout the South African, Nigerian, and Kenyan banks surveyed. Furthermore, Standard Bank Group's analysts employed this method, incorporating tangible net asset value (tNAV) and return on tangible equity (ROTE), for South African and Nigerian banks, but in Kenya their analysts used the residual income model to value the equities of the five Kenyan banks they covered. These findings suggest that the warranted equity method and the residual income model are the mostly used bank equity valuation methods in South Africa, Nigeria, and Kenya. The study concludes with relevant recommendations, offering significant insights for banks, regulators, and investors to make knowledgeable decisions concerning equity valuation. [ABSTRACT FROM AUTHOR]

This paper aims to comprehensively compare the risk-return profiles of Islamic and conventional equity markets, providing valuable insights into the financial performance of stock market indices in Islamic countries as compared to those in developed nations. The objective is to delve into the intricate dynamics of these markets, shedding light on how they respond to various economic and financial factors. By focusing on the performance metrics of stock market indices in both Islamic and developed countries, this study intends to analyze not only the overall returns generated but also the associated risks involved. In doing so, it seeks to unearth the nuances in investment opportunities, uncovering potential patterns of divergence or convergence between these two market segments. Furthermore, this research endeavors to discern how different economic and regulatory environments impact these markets, contributing to a more profound understanding of global investment. [ABSTRACT FROM AUTHOR]

Researchers traditionally compute isolated points for an efficient frontier and assume a line which passes through a risk-free asset r f and is tangent to the frontier. The tangency plays pivotal roles for the capital asset pricing model (CAPM). However, the assumption may not hold in the presence of kinks (as non-differentiable points) on efficient frontiers. Kinks are detected by parametric-quadratic programming only and not by ordinary portfolio optimization. Up until now, there has been no research to theoretically scrutinize kink properties (especially implications to CAPM) and systematically quantify the nonexistence of the tangency. In such an area, this paper contributes to the literature. In theorems and corollaries, we prove the nonexistence of the tangency and substantiate that expected-return axis is composed of piecewisely connected intervals for which the tangency does not exist and intervals for which the tangency exists. Computationally, we reveal universal existence of kinks (e.g., 0.2 to 8.0 kinks for 5-stock to 1800-stock portfolio selections) and the tangency-nonexistence ratios as about 0.066. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Administrative Sciences / Yonetim Bilimleri Dergisi is the property of Canakkale Onsekiz Mart Universitesi, Terzioglu Kampusu 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 Jurnal Nusantara Aplikasi Manajemen Bisnis is the property of Universitas Nusantara PGRI Kediri 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.)

This study explores the effectiveness of entropy as a proxy of aggregate market risk, in explaining the cross-section of excess returns in asset pricing model, after controlling for established factors like market excess returns, size, book to market and momentum. The analysis considers Indian firms, given that Indian capital markets are characterized by relatively thin trading and higher volatility compared to developed markets. Entropy is estimated using Shannon Entropy. Factor mimicking portfolio is constructed based on Shannon Entropy, whose returns are used as additional risk factor in Fama–French–Carhart four factor asset pricing model. Gibbons Ross Shanken-F statistic and Adjusted R2 are used to judge the efficacy of this factor in capital asset pricing model. All analysis is done using built in functions of python. Market beta, size and Book-to-Market are found to impact equity returns significantly. Entropy factor also impacts equity returns, but to a lesser extent. Explanatory power of asset pricing model is found to improve after inclusion of entropy factor, as indicated by GRS-F Statistic and Adjusted R2. Entropy augmented Capital Asset Pricing Models can be used by firms to decide hurdle rate for project evaluation and by asset managers for identifying over-valued/under-valued securities. This is the first study that investigates the role of entropy in explaining asset returns, in addition to other established priced factors. This study is limited to Shannon Entropy only. Other forms of entropy may improve results further, and should be explored in future research. [ABSTRACT FROM AUTHOR]

Price markups and firms' Tobin's Q ratios are widely believed to have been increasing in the past several decades. Various models for the calculation of price markups have been developed, each relying on the historically held definition of the ratio of price to marginal cost; however, all of these have methodological drawbacks, and some of the results they have produced have been poorly reflective of the near past wider macroeconomic experience. This paper defines a new approach for the definition and measurement of markup pricing, and it also avoids some of the issues surrounding the marginal cost approaches by using the measure of economic rent and the capital asset pricing model. The results show limited markup pricing for the UK's FTSE 100 companies (2018–2023), but that certain real estate, technology/media and financial services/equity investment firms have enjoyed higher price markup levels. An analysis of the business models of these firms is used to qualitatively propose explanations for such markups. This work offers formal proof that that the expected price markup is equal to Tobin's Q and finds that the empiric market level of markup is near equivalent to the market Tobin's Q; the differences between the markup and Tobin's Q at the level of the firm are equally assessed. This work challenges the general consensus that price markups are above one and have been increasing; it may also aid policy makers with respect to taxation policy and regulatory measures, as well as the financial management of firms in decisions concerning capital deployment and portfolio management. The method merits expansion to wider data sets, as well as to those from outside of the UK. [ABSTRACT FROM AUTHOR]

Considering the particularities of economic development, countries should cooperate and participate in joint projects within regional and international groupings. The paper aims to develop a scenario approach to the investment policy of countries in the context of globalization. Defines how important the investment component of a country's economic development is and justifies why countries are heterogeneous regarding investment attractiveness. To fulfil the main goal the author applies the capital asset pricing model, which is a basic concept in the field of finance. In addition to the main goal, the text of the article systematizes the stages of development of the organizational project scenario, justifies the role of foreign investments in economic development, and analyses world trends regarding changes in the attractiveness of investments. The paper estimates how attractive national economies are for foreign investments as well. [ABSTRACT FROM AUTHOR]

Although the superiority of Fama-French (FF) five-factor model in capturing the United States (US) equity returns, this model performs poorly in other stock markets (Fama & French, 2017). Using the monthly data of nearly 600 Vietnamese published firms from 2008 to 2022, the primary purpose of this paper is to analyze and examine the performance of four famous multifactor asset pricing models: the capital asset pricing model (CAPM), the Carhart four-factor model, and the FF three-factor and five-factor models. We document the preference for the Carhart four-factor model over other models in producing a precise description to Vietnamese stock returns. The CAPM cannot give a reasonable explanation to the variation of Vietnamese stock returns, implying that market risk only accounts for a small proportion of the risk of holding Vietnamese stocks. Furthermore, adding the profitability and investment factors does not improve the explanatory power of asset pricing models in Vietnam, inconsistent with the result reported in the US stock market (Fama & French, 2015, 2020). [ABSTRACT FROM AUTHOR]

The main intention of this study is to use the accounting data using CAPM to determine the stock prices/returns for the Nigerian capital market. In this study, the independent variable is the prediction of the stock prices and the dependent variable is stock prices in the market. The proxy that is used in this study to measure the dependent variable is CAPM in Nigerian Market. The most important and interesting phenomenon to investors is the analysis from financial market pertaining to stock returns. The research method employed is quantitative which is unlike qualitative as a way of assessing the stock price. The study mainly aims at assessing the correlation of beta factors and the predictability of stock returns from Nigerian firms listed on the stock exchange. In order to boost the beta estimates and mitigate statistical problems resulted from incorrect measurement, the securities were combined into portfolios. In conclusion the study employs ordinary least squares (OLS) regression technique and obtained beta value which is positive and found conclusive evidence for using CAPM and is thus consistent with Nigerian stock market prices. The CAPM has implications for asset pricing since it shows how to calculate the requisite rate of return to assess the value of the stock prices with any given amount of systematic risk (beta) and since the beta is positive hence the policy makers and investors in the Nigerian stock market would make better informed decisions.

This study investigated the risk-return relationship using the Capital Asset Pricing Model (CAPM), Carhart four-factor Model (C4FM) and Fama and French Multifactor Models (FFMMs): F3FM and F5FM. This study analyzed the JSE ALSI returns of the South African market, in relation to the risk factors constructed by the data of twenty-six emerging markets, over the sample period from October 2000 to October 2021. The methodology employed was a comparison of the conventional regression analysis and novel Bayesian approach. Regression analysis estimated by Ordinary Least Squares (OLS) is one of the foremost methods used in South Africa. However, such an approach does not take into account the properties of the price data, namely, the asymmetric, volatile and random nature. While the Newey-West adjustment is one way to assist in capturing autocorrelation and volatility, it fails to consider asymmetry. The Bayesian approach accounts for all the aforementioned properties, overcoming the fundamental flaws of regression analysis. The additional model diagnostics highlighted in this study improved the Bayesian approach' robustness. The risk factors of the FFMMs estimated by regression analysis, with and without the Newey-West adjustment, were insignificant, whereas the Bayesian test results were significant. This finding clearly highlighted that model choice impacts the significance of parameter estimation and the financial decisions of investors, firms and policymakers. Jensen's alpha revealed CAPM to be optimal but none of the asset pricing models fully captured the risk premia. Thus, returns should be investigated with different risk measures for future research purposes.

Using the capital asset pricing model, this article critically assesses the relative importance of computing 'realized' betas from high-frequency returns for Bitcoin and Ethereum—the two major cryptocurrencies—against their classic counterparts using the 1-day and 5-day return-based betas. The sample includes intraday data from 15 May 2018 until 17 January 2023. The microstructure noise is present until 4 min in the BTC and ETH high-frequency data. Therefore, we opt for a conservative choice with a 60 min sampling frequency. Considering 250 trading days as a rolling-window size, we obtain rolling betas < 1 for Bitcoin and Ethereum with respect to the CRIX market index, which could enhance portfolio diversification (at the expense of maximizing returns). We flag the minimal tracking errors at the hourly and daily frequencies. The dispersion of rolling betas is higher for the weekly frequency and is concentrated towards values of β > 0.8 for BTC (β > 0.65 for ETH). The weekly frequency is thus revealed as being less precise for capturing the 'pure' systematic risk for Bitcoin and Ethereum. For Ethereum in particular, the availability of high-frequency data tends to produce, on average, a more reliable inference. In the age of financial data feed immediacy, our results strongly suggest to pension fund managers, hedge fund traders, and investment bankers to include 'realized' versions of CAPM betas in their dashboard of indicators for portfolio risk estimation. Sensitivity analyses cover jump detection in BTC/ETH high-frequency data (up to 25%). We also include several jump-robust estimators of realized volatility, where realized quadpower volatility prevails. [ABSTRACT FROM AUTHOR]

AbstractThis study expands previous research by adding intellectual capital to the capital asset pricing model and deepening the measurement of intellectual capital using more comprehensive proxies. This study is novel in that it is related to evaluation according to market developments using tests on potential factors in the asset pricing model by adding intellectual capital variables. Intangible assets have the explanatory and predictive power of size and value strategies in predicting returns. This study uses a sample of all industries from all companies listed on the Indonesia Stock Exchange during 2012–2022; the sample totals 5767 firm-years. The results show a significant relationship between the six-factor capital asset pricing model, intellectual capital, and excess stock returns. The robustness test supports these findings, suggesting that intellectual capital performs better financially as an intangible asset. This study contributes to the literature regarding the role of intellectual capital in the capital asset pricing model, which can be helpful when making investment decisions in emerging stock markets.

In the conventional capital asset pricing model (CAPM), standard deviation as a measure of risk penalizes both upward and downward movements. However, while downward movements in investments are risky, upward movements are favourable. Therefore, standard semideviation that treats only those negative differences in returns over the benchmark as risky was proposed as a measure of downside risk. Attempts have been made to obtain the formulation of beta in this context, called downside beta. In this work, CAPM in the mean‐semivariance framework (D‐CAPM), with semivariance measured in terms of negative deviation around expected return, is derived and established that the model proposed earlier with a version of downside beta with respect to this definition of semivaraince is invalid. The appropriate version of downside beta is obtained, and under the rectified formulation, the validity of the true D‐CAPM is empirically tested during July 2013–July 2018. The solution to the tangent point is also obtained. The proportion of investment in the stocks in the tangent portfolio and the downside beta for the stocks in the tangent portfolio are determined. We find that there is no evidence to disprove that D‐CAPM holds true considering either Nifty 50 or S&P BSE Sensex as market portfolio. [ABSTRACT FROM AUTHOR]

This study expands previous research by adding intellectual capital to the capital asset pricing model and deepening the measurement of intellectual capital using more comprehensive proxies. This study is novel in that it is related to evaluation according to market developments using tests on potential factors in the asset pricing model by adding intellectual capital variables. Intangible assets have the explanatory and predictive power of size and value strategies in predicting returns. This study uses a sample of all industries from all companies listed on the Indonesia Stock Exchange during 2012–2022; the sample totals 5767 firm-years. The results show a significant relationship between the six-factor capital asset pricing model, intellectual capital, and excess stock returns. The robustness test supports these findings, suggesting that intellectual capital performs better financially as an intangible asset. This study contributes to the literature regarding the role of intellectual capital in the capital asset pricing model, which can be helpful when making investment decisions in emerging stock markets. [ABSTRACT FROM AUTHOR]

The valuation of banks is inherently complicated because of the uncertainties arising from their information opaqueness and inherent risks. Unlike non-banking firms, banks require specialised equity-side valuation approaches. This study addresses a gap in the literature by examining valuation methods used by bank equity researchers. The study used a total of 201 reports on South African banks (2018–2023), 56 reports on Nigerian banks (2018–2023), and 27 reports on Kenyan banks (2018–2023) to investigate the bank equity valuation methods utilised by analysts in the employ of Investec Ltd. and Standard Bank Group Ltd. The study’s findings show that Investec’s South African analysts predominantly used the warranted equity method, based on book value (BV), and return on equity (ROE), for valuing shares throughout the South African, Nigerian, and Kenyan banks surveyed. Furthermore, Standard Bank Group’s analysts employed this method, incorporating tangible net asset value (tNAV) and return on tangible equity (ROTE), for South African and Nigerian banks, but in Kenya their analysts used the residual income model to value the equities of the five Kenyan banks they covered. These findings suggest that the warranted equity method and the residual income model are the mostly used bank equity valuation methods in South Africa, Nigeria, and Kenya. The study concludes with relevant recommendations, offering significant insights for banks, regulators, and investors to make knowledgeable decisions concerning equity valuation.

Understanding why and how asset prices rise is a major concern for industry, policymakers and investors. This has attracted the attention of researchers to the issue of asset pricing, especially high-risk assets such as stocks. The single-factor capital asset pricing model (CAPM) and the Fama and French (1993) three-factor model are some of the well-known models that seek to explain investors' expectations for high-risk asset returns, and various multifactorial extensions of these models have been proposed. One of the latest versions of these models is the seven-factor model, which is expected to have a higher explanatory power than the CAPM model and the Fama and French three-factor model. The purpose of this study is to evaluate the seven-factor model in Tehran Stock Exchange and compare it with CAPM model and Fama and French model in order to predict the expected returns of companies operating in the financial sector of Tehran Stock Exchange during the period 2016: 1 to 2019: 12. In this study, the estimation method is the Auto Regressive Distributed Lag (ARDL). The results of the study show that the seven-factor model gives a better estimate of the expected return than the CAPM and Fama and French models. Also in the seven-factor model, the variables of book value to market value ratio, momentum, liquidity turnover ratio and commodity index have a negative and significant effect on expected returns. But market factor, government bond index and company size factors do not have a significant effect on expected returns.

The blueberry industry is growing significantly in Colombia. For investors, cost analysis plays a key role in project planning for any agribusiness. This paper is an exploratory study, with a descriptive scope to identify components of establishment and production costs of growing blueberries in Colombia. Data were collected and analyzed from a project aimed at establishing a 1 ha blueberry crop in Zipaquirá and 18 blueberry small farms in the Cundiboyacense highlands. Components were applied to estimate the capital investment and to identify the establishment, production, and maintenance costs of this project. Decision investment analysis, including discount rates for the capital asset pricing model (CAPM), were used to compute the net present value (NPV), internal rate of return (IRR), and the return on investment (ROI). Production costs are still expensive due to the Colombian peso (COP) exchange rate compared to the US dollar (USD). Results show advantages for promoting the establishment of blueberry crops because of suitable climatic conditions for continuous production throughout the year in Colombia. Labor costs and utilities are cheaper compared to other countries and represent a competitive advantage in the investment. Intermediation suppliers affect establishment costs for commercial reasons. Blueberry production cost analysis in Colombia may facilitate agribusinesses to promote projects in Colombian agriculture.

The main intention of this study is to use the accounting data using CAPM to determine the stock prices/returns for the Nigerian capital market. In this study, the independent variable is the prediction of the stock prices and the dependent variable is stock prices in the market. The proxy that is used in this study to measure the dependent variable is CAPM in Nigerian Market. The most important and interesting phenomenon to investors is the analysis from financial market pertaining to stock returns. The research method employed is quantitative which is unlike qualitative as a way of assessing the stock price. The study mainly aims at assessing the correlation of beta factors and the predictability of stock returns from Nigerian firms listed on the stock exchange. In order to boost the beta estimates and mitigate statistical problems resulted from incorrect measurement, the securities were combined into portfolios. In conclusion the study employs ordinary least squares (OLS) regression technique and obtained beta value which is positive and found conclusive evidence for using CAPM and is thus consistent with Nigerian stock market prices. The CAPM has implications for asset pricing since it shows how to calculate the requisite rate of return to assess the value of the stock prices with any given amount of systematic risk (beta) and since the beta is positive hence the policy makers and investors in the Nigerian stock market would make better informed decisions. [ABSTRACT FROM AUTHOR]

In recent years, the rapid and significant development of emerging markets has globally led to insight from potential investors and academicians seeking to assess these markets in terms of risk inheritance. Therefore, this study aims to explore the validity and applicability of the capital asset pricing model (henceforth CAPM) and multi-factor models, namely Fama–French models, in Pakistan's stock market for the period of June 2010–June 2020. This study collects data on 173 non-financial firms listed on the Pakistan stock exchange, namely the KSE-100 index, and follows Fama-MacBeth's regression methodology for empirical estimation. The empirical findings of this study conclude that small portfolios (small-size companies) earn considerably higher returns than big portfolios (large-size companies). Ultimately, the risk associated with portfolio returns is reported to be higher for small portfolios (small-size companies) than for big portfolios (large-size companies). According to the regression output, the CAPM was found to be valid for explaining the market risk premium above the risk-free rate. Similarly, the FF three-factor model was found to be valid for explaining time-series variation in excess portfolio returns. Later, we added human capital into FF three- and five-factor models. This study found that the human capital base six-factor model outperformed the other competing asset pricing models. The findings of this study indicate that small portfolios (small-size companies) earn more returns than big portfolios (large-size companies) to reward the investor for taking extra risks. Investors may benefit by timing their investments to maximize stock returns. Company investment in human capital adds reliable information, replicates the value of the company and, in the long term, helps investors make rational decisions. [ABSTRACT FROM AUTHOR]