Capital Asset Pricing Model Research Articles

Capital Asset Pricing Model (CAPM) Analysis: Technology Sector Stock Conditions Before and During the Pandemic

The COVID-19 pandemic made people more active in saving, such as investing in the capital market. Stocks in the technology sector were excellent stocks because the trading volume increased by up to 7.3 times during the pandemic. The Capital Asset Pricing Model (CAPM) was a model to see the expected rate of return and aimed to assist investors in making investment decisions. CAPM used beta (β) to measure the sensitivity a stock or portfolio is to market movements. Beta indicates the tendency of an asset's return to react to fluctuations in the overall market. This study aimed to look at differences in technology sector stocks in the period before and during the pandemic using the CAPM method and paired t-test. The research using a purposive sampling method. A quantitative descriptive method was used in this study and used secondary data in the form of financial statements of technology sector companies listed on the Indonesia Stock Exchange. Based on the results of the study, seven stocks had an average negative return before the pandemic and positive returns during the pandemic. There was one efficient stock in the pre-pandemic period and six inefficient shares, and seven shares were classified as efficient shares during the pandemic. The results of the paired t-test showed that there was a significant difference between individual returns before and during the pandemic.

The role of gold in terrorism: Risk aversion or financing source?

Based on the perspective of terrorism, this study uses a bootstrap full-sample causality test and sub-sample rolling window estimations to explore the risk aversion capability and terrorist financing capability of gold's time-varying dimension. The results suggest that terrorist incidents (defined by the number of terrorist attacks) and terrorist brutality (measured by the number of fatalities produced by terrorist attacks) are important factors in explaining changes in gold prices, but their effects differ. With extensive media coverage, the cause of investors' panic has changed from terrorist incidents to terrorist brutality. The results from some sub-sample periods support the capital asset pricing model by showing that terrorist attacks push up gold prices through a “terror premium.” Considering reverse causality, gold price can be used as an early warning of terrorist attacks, but its terrorist financing function is not yet proven. In the context of increasingly serious terrorism, studying the interaction mechanism between terrorist attacks and gold prices can help investors reasonably plan investments and provide insights for the government on combatting terrorism and maintaining world peace.

Conditional effects of higher order co-moments in asset pricing: Evidence from Borsa Istanbul

This paper explores how systematic higher order moments (co-skewness and co-kurtosis) are priced in Borsa Istanbul. We tested the significance of higher order co-moments and analyzed their contribution to the standard capital asset pricing model and the Fama and French (2015) 5-factor model. We used a two-stage method to analyze the weekly returns of beta and size-sorted portfolios and individual stocks over the sample period from June 22, 2007 to November 15, 2023. We also used models conditional on market movements. The findings reveal that co-skewness has statistically significant effects on portfolio returns in Borsa Istanbul, especially in up markets. We also present the statistically significant effects of co-kurtosis on individual stock returns in both up and down markets.

Capital Asset Pricing Model for the Stock Market in Pakistan

The Capital Asset Pricing Model (CAPM), within modern financial theory, offers a theoretical framework for pricing assets with uncertain returns. CAPM assesses systematic risk and proposes a linear relationship between risk and expected returns for any asset. It serves as a potent tool for pricing risky assets. In this present study, the trade-off between risk-return was investigated within the framework of CAPM and its validity was tested on the daily returns of companies listed in the chemical, textile and food sectors of the Pakistan stock market during the period July 2004- Feb 2014. The results of empirical testing by regression analysis supported the CAPM’s validity for these sectors in Pakistan and found CAPM β as a single factor which was priced by the market. The KSE-100 index was used as a market, and the year treasury-bills return rate was taken as a risk-free rate.

Exploring Downside Co-Skewness and Upside Co-Kurtosis: Implications for Asset Pricing Models

This study examines how the investors' preferences for downside co-skewness and upside co-kurtosis may influence the asset pricing. We analyze data from 2000 to 2021, encompassing 2874 companies listed on the Shanghai Stock Exchange. Our methodology includes both time series and cross-sectional analyses, employing the Fama-Macbeth approach. Our findings reveal that the estimated values for downside co-skewness and upside co-kurtosis contribute to a significant premium, one that remains unexplained by traditional market factors such as size, value, profitability, and investment. Furthermore, when these higher-order co-moments are incorporated into the Capital Asset Pricing Model (CAPM), they demonstrate significant explanatory power in understanding the variations in stock returns. This augmented CAPM, with downside co-skewness and upside co-kurtosis, exhibits a superior goodness-of-fit compared to conventional asset pricing models. This suggests a crucial link between these higher-order risk factors and stock valuation, offering new insights into the complexities of investor behavior and market dynamics.

Old age care fund helps to manage their funds In easy way

Abstract: A Old Age Care Funds is a sort of investment vehicle in which the combined capital of several participants is used to purchase a diverse range of bonds, equities, and other securities. Funds, which are professionally managed, give people the chance to invest in a variety of assets without having to handle them themselves. The value of the Fund shares that investors purchase varies according to how well the underlying assets perform. Funds are well-liked by both rookie and seasoned investors because they offer diversity, liquidity, and expert management. Diverse mutual fund categories, such as stock, bond, money market, and hybrid funds, are available to suit varying investment goals and risk tolerances. Investors can select funds according to their risk tolerance, time horizon, and financial objectives. Securities regulators supervise mutual funds to maintain transparency and safeguard the interests of investors. They are now an essential instrument for people to develop a diversified investment portfolio and engage in the financial markets. Old Age Care Fund portfolio analysis is an important component of investment management that includes a variety of approaches for evaluating the performance, risk, and composition of investment portfolios. The efficient market hypothesis (EMH) states that markets are efficient and reflect all available information, making it difficult for fund managers to regularly outperform the market, according to Malkiel and Fame (1970). Jensen (1968) proposed the Capital Asset Pricing Model (CAPM), which emphasizes risk-adjusted returns and the identification of alpha, which indicates a fund manager’s capacity to create excess returns above the market. IndexTerms – Python, Powet-BI, Data Analysis.

Herding behaviour towards high order systematic risks and the contagion Effect—Evidence from BRICS stock markets

This paper investigates the existence of herding movements towards several systematic risk factors derived from the Capital Asset Pricing Model (CAPM) and its extensions. The measure of herding is estimated using the dispersion of the risk factor loadings. The state space model is employed to extract time series of herding dynamics. We empirically survey the herding behaviors in the BRICS stock markets (i.e., Brazil, Russia, India, China, and South Africa) using monthly stock index data from 2006 to 2022, and identify various herding patterns towards specific factors. We also examine the impact of unanticipated shocks in crucial macroeconomic variables on the degree of herding measure in these countries. Lastly, we test the contagion hypothesis of herding across markets using correlation analysis. The results show that the level of herding linkages increases significantly in periods of market stress, casting doubt on the effectiveness of asset allocation in these markets for the sake of diversity.

The Predictive Ability of U.S. Stock Market Skewness on Indonesian Stock Market Returns

The three-moment capital asset pricing model (three-moment CAPM) suggests that the expected excess return on stocks should include compensation for skewness risk. This study aims to investigate the ability of U.S. stock market skewness to predict Indonesian stock market returns. The data used in this research includes the S&P500 Index, JCI, JII, and LQ45 from January 2001 to December 2022. The results of this study indicate that U.S. stock market skewness can predict future excess returns of the Indonesian stock market. Additionally, when the estimation model incorporates alternative variables from both the U.S. and Indonesian stock markets, the predictive ability of U.S. stock market skewness remains significant and outperforms these alternative variables. The findings of this research can be used as a strategy for investors when trading in the Indonesian stock market. When the skewness of the U.S. stock market increases, the return of the Indonesian stock market is expected to decrease in the following month.

Cryptocurrency returns and consumption-based asset pricing

ABSTRACT This paper examines whether the cross-section of cryptocurrency returns is captured by risk factors based on consumption-based asset pricing. It is an imperative task for financial economists to find the fundamental risk behind characteristic-based cryptocurrency factors in order to economically understand cryptocurrency. To address the data availability issue in the analysis of cryptocurrency, we employ mixed data sampling (MIDAS) regression to check the relation between the principal component analysis (PCA) factors in cryptocurrency returns and the factors in the consumption capital asset pricing models (CCAPMs) and intertemporal capital asset pricing models (ICAPMs). We establish significant links between them, which in turn implies that cryptocurrency returns are investors’ compensation for bearing consumption risk, conditional consumption risk, and intertemporal consumption risk. This finding underscores that cryptocurrency returns are the manifestation of macroeconomic equilibrium derived from investors’ utility maximization.

Analysis of Periodic and Seasonal Characteristics in Time Series: Taking the Dow Jones Industrial Average as an Example

The objective of this research is to conduct a comprehensive analysis of the Dow Jones Industrial Average (DJIA) with a focus on identifying cyclical and seasonal patterns observed in long-term time series data. In order to accurately predict future market trends, this research employs a combination of fundamental and advanced forecasting techniques, including mean, naive, snaive, drift, Holt, Holt-Winters, and ARIMA models. Furthermore, the research explores the impact of return ratios on market investment opportunities. Customized portfolio optimization strategies are developed based on the risk profiles of different investors, along with quantitative trading strategies that effectively manage market risks using the Capital Asset Pricing Model (CAPM). The research shows that the price of Dow Jones Industrial Index has a gradual upward trend, and its return rate has a certain periodicity and seasonality. The aim of this research is to provide valuable insights into the fundamental framework of the American stock market, enabling economists, investors, and policymakers to make informed decisions.

Intangible Capital, Investor Structure and Stock Return from the Perspective of RBV

The current research suggests the presence of asset mispricing by indicating that stock prices may not necessarily reflect underlying fundamentals. Additionally, prior studies often underestimate the importance and overlook contributions from resources to the returns. In this article, we propose the effect of intangible assets into asset pricing in the context of varying investor sentiment and long-term investment horizon. Drawing from the recourse-based view of intangible assets within firms, we can better assess a firms growth and stock returns. We conclude that the Capital Asset Pricing Model (CAPM) should incorporate the influence of intangible assets. These assets can reduce operational risk, thus affecting idiosyncratic risk.

A Comparative Study of CAPM Based on the US Stock Market

The capital asset pricing model (CAPM) is a highly useful and relatively simple equation used in this study for calculating the volatilities, also known as beta, of different stocks in four different industries in the S&P 500 Index and a 1-year T-Bill. The beta values of the stocks in each industry were added together to find the total beta for each industry. An overall decreasing trend in industry beta values near the end of the 2022 can be seen for banking and media & entertainment, while transportation increased a little and retail remained relatively constant, with transportation having beta values closest to one. Changes in industries with beta values near one will better reflect the overall market, as the markets beta is assumed to be one. The purpose of this research is to compare the risks and sensitivities of these four industries after the COVID pandemic, and the results show that as the pandemic subsides, beta values have begun to shift closer towards one.

Optimization Active and Passive Portfolio using Single Index Model and Capital Asset Pricing Model in Indonesia

The purpose of this study is to evaluate the performance and return of portfolios with active and passive strategies using the Capital Asset Pricing Model (CAPM) and a single index model in order to create the best possible portfolio for companies that do not consistently appear in the LQ 45 index between 2018 and 2023. Secondary data on the closing stock prices of the stocks in the LQ 45 index, which is reviewed on a daily basis, is used in the research. Using the LQ 45 index, the study tracks the performance and return of these erratic equities across the research period. The results showed that portfolios with a single index model provided higher returns than the Capital asset pricing model and portfolios with active strategies were able to provide greater returns than portfolios with passive strategies but the statistical test results did not show significant differences between them. The findings offer fresh perspectives on how to construct the ideal portfolio utilizing the Single Index Model and CAPM for the LQ 45 index stocks, which saw volatility between 2018 and 2023. The results can serve as a reference for future research and insight for investors in choosing investment strategies in the capital market.

Capital Asset Pricing Model: A Renewed Application on S&P 500 Index

Capital Asset Pricing Model: A Renewed Application on S&P 500 Index

The effect of structural oil shocks on stock returns of Indian renewable energy companies across market conditions

Purpose This study aims to evaluate the structural oil shocks effect on stock returns of Indian renewable energy companies across market conditions. Design/methodology/approach This study applies the structural vector autoregression model to estimate sources of oil shocks such as oil supply shock, aggregate demand shock and oil price-specific demand shock. In the next step, the panel quantile regression model estimates the effect of these oil shocks on stock return across market conditions. Monthly data are collected from January 2009 to December 2019. All renewable energy companies listed on the National Stock Exchange of India are considered for the analysis. Findings In the whole sample analysis, this study finds that oil shocks negatively affect stock returns in most of the market conditions except oil price-specific demand shock. In sub-groups, oil shocks driven by supply and aggregate demand also negatively affect stock return in most market conditions. This study finds the positive interaction of oil price-specific demand shock. A majority of these positive interactions happen in bearish market conditions. In the whole sample, the asymmetric effects of shocks driven from oil supply and oil price-specific demand are seen in most quantiles or market conditions. At the same time, aggregate demand shock does not affect asymmetrically. In the sub-group analysis, standalone renewable energy companies stock returns are least asymmetrically affected by these oil shocks. The asymmetries of oil supply-driven shock on stock returns of the renewable energy sub-group companies are found in most quantiles. Originality/value First, this is a company-level study of the stock returns response to the structural oil shocks in the renewable energy sector. Second, to the best of the authors’ knowledge, this type of study is the first in the Indian context. Third using panel quantile regression model along with capital asset pricing model framework, the authors investigate these effects across market conditions.

Unveiling influential factors in the capital asset pricing model: A novel approach utilizing Taguchi method

This study uses a Design of Experiment (DOE) approach and the Taguchi method to examine how different factors affect the expected return within the framework of the CAPM. The Capital Asset Pricing Model (CAPM) is a financial framework that forecasts an investment’s expected return by taking into account its systematic risk. This model factors elements like the risk-free rate, market risk premium, and beta to ascertain the expected return for a given asset. Typically, historical market data and financial analysis provide the inputs for CAPM. This method, frequently used in manufacturing and engineering, is modified for use in the financial domain to evaluate the importance of variables like beta, market risk premium, and the risk-free rate. The research identifies the factors that influence investment performance and shows how much each factor contributes to the expected returns. It is possible to ascertain each factor's percentage contribution to the expected return through statistical analysis. This work improves knowledge of CAPM and creates opportunities for improving investment decision-making processes by bridging the gap between financial theory and experimental design. Financial practitioners can achieve more reliable and accurate investment return forecasts by incorporating DOE techniques into their existing analytical toolkit.

Do socially responsible indices outperform conventional indices? Evidence from before and after the onset of Covid‐19

AbstractAccording to traditional portfolio theories constraints, restrictions, and screens applied in portfolio selection reduces the diversification opportunities which can impact financial performance. Is this true in the case of socially responsible investment (SRI)? To answer this, present study analyzes the performance of Socially Responsible (SR) indices in comparison to conventional indices in an emerging economy. The uniqueness of the study is that it analyses the performance of Shariah, ESG, and thematic indices in a single study. Further, the study measures the impact of Covid‐19 on them. Comparative performance evaluation was conducted by using absolute return analysis and risk‐adjusted measures namely, Sharpe ratio, Treynor ratio, tracking error, information ratio, capital asset pricing model (CAPM), Fama–French three‐factor, and Carhart's four‐factor models. The Structural break was identified, hence analysis was conducted for the total period (January 2017–March 2023) and two sub‐periods, that is, pre and post‐Covid‐19 period. No significant difference was found between the returns of SR indices and conventional indices as against the benchmark index on the basis of absolute return analysis. Sharpe ratio and Treynor ratio both were having negative values for all the SR and conventional indices. Tracking error for all the SR and Conventional indices were very low. The CAPM and both multi‐factor models univocally pointed toward the underperformance of all the SR (except S&P BSE 100 ESG index which had equal performance) and both conventional indices against the benchmark index. Noteworthy point is that only Shariah indices gave the highest returns during post‐Covid period. This research will help in deepening the SRI in the capital market. Companies should increase their ESG scores and make efforts to be listed on the SR indices. Policymakers should announce some kind of rebates, or recognition for star‐performing companies in the field of sustainability to encourage other companies to adopt SR practices in their business operations. The novelty of the current study is that it adds to the socially responsible literature by analyzing the performance of Shariah, ESG, and Thematic indices and conventional indices in a single study in the fastest‐growing economy of India and analyses the impact of Covid‐19 on this performance.

Asset Returns and Economic Uncertainty: A Cross-Country Analysis

This paper examines the effects of economic uncertainty (idiosyncratic vis-à-vis common uncertainty) on equity, bond and housing returns across both developed and developing countries. Building on International/Intertemporal Capital Asset Pricing Model (ICAPM), we find that economic uncertainty exerts negative effects on equity, bond and housing returns. When we decompose economic uncertainty into two parts: idiosyncratic and common economic uncertainty, we find that ‘idiosyncratic uncertainty’ affects equity, bond and housing returns more negative and pronounced than ‘common’ uncertainty, where investors do not demonstrate differences in responses to the different dimensions of uncertainty. Moreover, there are weak lagged effects of economic uncertainty on asset returns. Additionally, we find negative uncertainty premium for equity more persistently in bullish rather than bearish market conditions. Our results are also robust for low frequency data and inclusion of covid period in the analysis. Our findings have implications for policy makers in both developed and emerging markets regarding clear communication of economic policies.

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.

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.