Capital Asset Pricing Model Model Research Articles

Stock Portfolio Analysis of Agribusiness Companies on Indonesia Stock Exchange

Stock portfolio analysis is the analysis conducted by diversifying or selective combining shares in investment, with a portfolio of risks to be minimized. The purpose of this study is to find out the formation of optimal portfolios using the Capital Asset Pricing Model (CAPM) model approach and Arbitrage Pricing Model (APT). With both models, an investor will be able to find out the composition of stocks, especially shares of companies engaged in agribusiness, as well as directly to find out the proportion of each stock and its risks and benefits arising from the formation of the portfolio. The results showed that by using the CAPM and APT models in the calculation of the formation of optimal portfolios in stocks excange Agribusiness, produces a portfolio with stocks composision 3 froms, namely AALI, TBLA and UNSP. APT model approach shows a greater value than the CAPM models, the highest return value can be generated is 14.088% while that may happen is losses -0268% while the CAPM models yield the highest return rate of 5.74% and the losses will be experienced by -14.54 %. significant difference in outcome is caused from the different assumptions of the models above. From these results should be expected investors to take investment decisions of agribusiness firms stocks in the Indonesia Stock Exchange with respect to the results obtained from the approach to the CAPM and APT models, in addition to the results obtained from both models are also investors give the attention of fundamental and technical factors companies that investors are not wrong and more confident in make investment decisions.

Investment and Analysis of China's New Energy Industry Chain

The aim of this paper is to provide an intricate analysis of investment prospects within China's emerging clean energy sector using the Capital Asset Pricing Model (CAPM). Initially, the paper delves into the background, objective, and current state of China's clean energy industry. It then offers a comprehensive explanation of the CAPM model, elucidating its theoretical foundation and underlying assumptions. Key concepts such as the risk-free rate, beta coefficient, and market risk premium are clarified. In subsequent sections, the paper describes the data collection methods employed by the research institute and justifies the selection of sample companies.Moving on to the results section, the paper presents an evaluation of investment prospects by utilizing the beta coefficient as a pivotal determinant. The analysis takes into consideration pertinent factors like performance, growth potential, and financial stability, empowering investors to make well-informed decisions. Building upon the research findings, the paper concludes by providing comprehensive insights and recommendations for investment in China's clean energy sector. Furthermore, the paper substantiates its conclusions by citing relevant references, thereby establishing the credibility and validity of the findings.Ultimately, this study enhances our understanding and assessment of the investment potential within China's clean energy industry. By promoting sustainable development within this sector, this research contributes to China's broader objective of attaining long-term environmental and economic sustainability.

Comparison Between Different Pricing Models: Evidence from the Technology Industry

The primary goal of this study is to investigate the applicability and analytical effectiveness of three models, namely the Capital Asset Pricing Model (CAPM), the Fama-French Three-Factor Model, and the Fama-French Five-Factor Model, within the technology industry. The study focuses on a sample of six representative technology companies, employing monthly data spanning a period of five years from 2018 to 2023. Empirical tests and regression analyses are conducted to empirically assess the performance of these three models. The results demonstrate that the Fama-French Three-Factor Model exhibits superior fitting performance compared to the CAPM model, as initially hypothesized. However, when comparing the fitting performance of the Fama-French Five-Factor Model to the Fama-French Three-Factor Model, the study reveals that the former does not exhibit a significant improvement and even shows a slight decrease in fitting effectiveness. For the technology industry, the Three-Factor Model effectively captures systematic risk and accounts for a sizable proportion of the variation in regressions. Additional factors in the Five-Factor Model might introduce additional complexity without significantly enhancing the model's explaining extent. Overall, this study underscores the importance of model selection and raises awareness about the trade-off between model complexity and explanatory capability, particularly in the technology industry.

The Application of the Capital Asset Pricing Model (CAPM) in China's Financial Market: An Analysis of Regulatory Impact and International Comparison

Indentation of Abstract should be left 0.53"/1.35cm. As the world's second largest economy, China is also one of the world's biggest emerging economies; The Capital Asset Pricing Model (CAPM) is one of the most classic pricing models, and China's asset pricing model has gained a lot of experience from it. This research investigates the application of the CAPM in China's financial market, focusing on the influence of financial market regulation and conducting a comparative analysis with international markets. CAPM is a fundamental asset pricing model used to estimate asset expected returns and risks based on their covariance with the overall market portfolio. The study aims to analyze the practical implementation of CAPM in China's financial market, considering the impact of financial market regulation on the model's effectiveness. Key variables such as market data, risk-free rates, and stock returns are utilized, with specific adjustments made to accommodate China's unique regulatory environment. The research's significance lies in providing valuable insights into asset pricing and risk assessment in China's financial market, as well as implications for investors and policymakers. By comparing the results with international markets, this study contributes to a broader understanding of the CAPM model's applicability and effectiveness in diverse regulatory settings.

A comparison of CAPM and Fama-French three-factor model under Machine Learning approaching

With the economy experiencing rapid growth in recent years, more individuals have started venturing into the stock market. Precisely forecasting the rate of return can mitigate investment risks for stock investors and significantly enhance their investment returns. The Capital Asset Pricing Model (CAPM) and the 3-factor Fama-French model (FF3) are widely recognized in academic and practical settings. This model comparison provides frameworks to analyze the relationship between portfolio risk and return in inefficient markets. This research utilized the Support Vector Regression (SVR) algorithm to forecast the returns of a diversified portfolio in the Hanoi stock market (HNX) from 2010 to 2022. Subsequently, the explanatory power of the CAPM and FF3 models were compared using the Ordinary Least Squares (OLS) algorithm. Finally, this research incorporated the SVR algorithm within the FF3 framework to develop a predictive model. The research findings demonstrate that the FF3 model provides a superior explanation to the CAPM model. Additionally, the study reveals that the SVR algorithm outperforms the OLS algorithm in terms of efficiency, as it yields lower Root Mean Square Error (RMSE) values. Consequently, the next research direction entails replacing the FF3 model with a more comprehensive multi-factor model, anticipating obtaining an enhanced predictive model.

A Review of the Applicability of Pricing Models in the Stock Market

The capital asset pricing model (CAPM) model has always been the core theory of asset pricing and is widely used in the world as a finance tool in the securities market, but it is not fully effective for the economic market due to the current state of development in some countries. This paper compares and analyses the CAPM model and its improved and alternative models based on existing literature and statistical data. This paper first explains the CAPM model, analyses its formula, and then describes the disadvantages and shortcomings of the CAPM model. Then it gives examples of other replaceable models, first explains those models, then lists the advantages of these models compared with the CAPM model as well as some of their shortcomings, and finally concludes through the comparison of these models to the CAPM model that although the CAPM model may not be applicable to the market in many cases, it can be replaced by other models, and even then there is no one-size-fits-all model that can replace all the market models, and conclusions need to be made on a case-by-case basis.

An Empirical Test Based on the Validity of the Capital Asset Pricing Model of American Firms

Nowadays, quantitative finance has become a more and more mainstream research direction, and the origin model of quantitative finance is the capital asset pricing model (CAPM)created by William Sharp and others. This paper mainly studies the feasibility of CAPM model for the American market, in order to prove the universality and accuracy of CAPM model, and analyzes the relevant errors. The research object of this paper is 59 randomly selected listed companies in 11 industries in S&P500 index, and the regression is carried out by the ordinary least square method, and the goodness of fit is obtained, so as to prove its universality. The data comes from Yahoo Finance. Through data analysis, this paper believes that CAPM model is universal, but it has low adaptability for some special industries, so it is necessary to introduce more variable factors or carry out non-linear regression to improve the accuracy of its prediction.

Empirical Test on CAPM Model of China's Stock Market by Industry Grouping

Capital Asset Pricing Model (CAPM) is a hotly debated issue of modern financial theory research, and the viability of the capital resource evaluating model in China's flow capital market requires further experimental examination and testing. The indexes of 27 industries and the Shanghai Shenzhen 300 index are taken as the research objects, and the day to day exchanging information from January 5, 2015 to December 31, 2021 are used for regression analysis. This study assesses the risks and rewards of each business by computing the coefficients for various industries throughout various time periods. It then verifies the accuracy of the CAPM model by using the linear relationship between the average return rate and coefficients. Although the return on the stock market is linearly connected with the beta coefficient for the majority of regression findings with a shorter time horizon (less than 100 days), systematic risk is insufficient to account for the expected return on the stock portfolio, which is in conflict with the theoretical assumptions of the capital asset pricing model. Meanwhile, the regression's fit coefficient is modest, indicating that other risk factors have a non-negligible impact on stock returns. For the regression results divided by longer maturity as well as 40 days as maturity, the stock market return shows a non-linear correlation with the beta coefficient. Thus, it may be said that the CAPM model does not apply to the stock market in China.

Relationship Between Corporate Capital Structure and Company Value Based on the CAPM and APT model and the WACC analysis

The core of financial management and investment activities is to maximize the wealth of the company and shareholders. Company value maximization is inseparable from shareholder value maximization. Due to the fact that the structure of company's capital would influence the level of profit return and the circumstance of cash flow, the management for financial framework is a significant connection between the economic situation of the corporation, by which it can benefit the value. The author briefly analyzed the CAPM since it is not an accurate model, which has unrealistic assumptions and the disadvantages of unrest, by using the APT model to replace the CAPM model to study the arbitrage pricing model and its relationship with the capital asset pricing model (CAPM). From the analysis of these models and the introduction of four capital structure theories, the connection between corporation capital structure and corporate value is further studied.

Introduction to CAPM: Advantages, Disadvantages and Alternatives

Capital Asset Pricing Model (CAPM) is a widely used financial model for asset pricing. This paper summarizes the advantages of CAPM, highlighting its applicability to most developed countries. Based on academic research, this paper also discusses the limitations of the CAPM model, including issues with its assumptions and its limited suitability for developing countries. In the end, Alternative solutions are discussed, including finding other financial models to replace or improve the CAPM. However, through the summary, this paper finds the current financial models are relatively independent and most of them have some shortcomings in the assumption. It is difficult to find a perfect model. Therefore, the conclusion is that the future research direction should be to integrate a summative financial model to integrate the advantages of each model to help future financial analysis in both developed and developing countries.

The Comparative Analysis of the Influence of Shanghai Composite Index and Shenzhen Component Index on stock return of Contemporary Amperex Technology Co. Limited (CATL)

CATL has been a popular choice among all the stocks in Chinas stock market and has been recognized by many investment institutions as a good choice for long-term holding. However, its stock return always varies in Shanghai Composite Index and Shenzhen Component Index and no previous research has been done in terms of this area. Thus, to figure out the influence each market does on CATLs stock, this research applied Capital Asset Pricing Model (CAPM) as the quantitative calculation method and made a linear regression to calculate the difference in return by analyzing the P-value, coefficients () and intercepts (). The findings indicate that CATLs stock price is more highly valued by the Shenzhen Component Index while Shanghai Stock Exchange has a more significant influence on CATLs stock. In addition, the effectiveness of the CAPM model in stock valuation is further verified through the comparative analysis.

The Research on the Application of CAPM Model in Chinese Stock Market

With the improvement of living standards, more and more people tend to use their savings to make stock investment, and how to make good use of precious capital for project investment, industrial support policy of the government how to develop practical, make the flow of resources efficiently has the development potential and competitive enterprise project, which requires us to make accurate judgment and the correct decision. By adopting the method of regression analysis, carries on the empirical analysis of China's securities market sampling, shows that, by using statistical analysis methods, this study can select a relatively appropriate market portfolio yield, improve the accuracy of asset value and asset allocation, which is an effective and analytical obstacle to the use of Capital Asset Pricing Model (CAPM) to the China's capital market. And then put forward some model to analyze the enlightenment of capital and asset pricing for the stock market. The study draws a conclusion that the beta of a stock plays a decisive role in investing. Stocks with different beta values are selected according to different stock market conditions in order to achieve the best expected annualized return.

How accurate is the CAPM approach compared to the Reward Beta for shares of manufacturing and mining companies in Indonesia's LQ45 Index?

This study evaluates the efficacy of the Capital Asset Pricing Model (CAPM) and Beta Reward Model in forecasting stock returns of companies within the manufacturing and mining sectors listed on Indonesia's LQ45 index. Utilizing monthly closing stock prices from January 2010 to December 2019, the research focuses on ten companies—five from each sector—that consistently appeared in the index throughout the study period. The analysis involves a classic assumption test followed by regression analysis for each company. Key performance indicators, including R-squared, Root Mean Square Error (RMSE), and Mean Absolute Error (MAE), are employed to compare the predictive capabilities of the CAPM and Beta Reward Model. The findings indicate a systematic and superior performance of the Beta Reward Model over the CAPM in predicting stock returns in the Indonesian context. This study contributes to the existing literature on stock return prediction models and provides practical insights for investors and financial analysts in Indonesia.

Investment Decisions On Indonesia Energy Sector Companies By Capital Asset Pricing Model Model

This research was conducted to analyze the level of investment feasibility in IDX index stocks for the 2022 period using the Capital Asset Pricing Model (CAPM) method in determining investment decisions. This type of quantitative research is descriptive. The population of this study is Oil & Gas Storage, Distribution companies listed on the IDX-IC index for the period January - December 2022. The samples are 8 company shares that meet the criteria set by the researcher. This study uses SPSS linear regression analysis to determine the beta coefficient of the Capital Asset Pricing Modeling (CAPM) method and compares the expected return with the stock market rate of return during the observation period to further distinguish between efficient and inefficient stocks. The results of the observations show that 7 companies have efficient shares and 1 company that has inefficient shares which can be seen in the SML Security Market Line (SML) graph or the securities market line (GPS) of the CAPM model for efficient shares and inefficient shares.

Validity of Capital Asset Pricing Model(CAPM)Empirical Research on the Panel Industry in China

In recent years, the stock of the panel industry has developed well and the country has invested heavily in this industry, so investors are enthusiastic about the panel industry. Based on the investment potential of the panel industry, this paper selects the latest data of 12 stocks in Shenzhen Stock Exchange from January 1, 2007 to December 31, 2021, and uses the capital asset pricing model (CAPM) to conduct an empirical study on China's panel industry. The results show that the applicability of the coefficient panel industry is not strong, and the applicability of the CAPM model in the panel industry is not good. At the same time, combined with the stock market environment of China's panel industry, this paper makes a further analysis of the CAPM model, and puts forward some investment suggestions for investors the following investment suggestions for reference: evaluating the risk of assets by using a number of indicators before investment; seizing the investment opportunities of upstream new materials and so on.

A Literature Study on the Capital Asset Pricing Model

Capital Asset Pricing Model (CAPM) is an important theory in financial economics. It was based on Markowitz's Modern Asset Allocation Theory (MPT) and proposed by Sharpe. This model expresses the relationship between risk coefficient, asset return rate, and systematic risks by simple mathematical formulas. The model has four advantages, handling of risks when evaluating investment behavior, accuracy when estimating equity capital, relatively reliable and better than Weighted Average Cost of Capital (WACC) in investment evaluation. CAPM also has some weakness, consisting of variables and application in investment evaluation. There are three variables in CAPM model, risk-free rate of return, equity risk premium and beta. The weakness about application in investment evaluation shows that in beta of projects and firms are different, complex restructure and periods. The Arbitrage Pricing Theory (APT) can be an option of CAPM, and it is a more flexible and complex model compared with CAPM. However, the latest research proves that Portfolio Theory has very big problems. High-risky assets do not necessarily have high returns. This view may be embodied in "low-risk anomalies" and "Idiosyncratic Volatility". In the future, researchers will introduce more elements for CAPM to improve accuracy, or develop new models.

Analisis Keakuratan Capital Asset Pricing Model Dan Arbitrage Pricing Theory Dalam Memprediksi Return Saham (Studi Pada Perusahaan LQ 45 Di Bursa Efek Indonesia Periode 2016-2020)

This study is based on the rapid development of the investment world. Hence, most investors have limited abilities and strategies in investing, therefore it takes important methods and concepts to assess the level of profit from an investment with various existing risk factors. This study focuses on the comparison of the accuracy between the Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT) methods in predicting stock returns of LQ 45 index companies for the 2016-2020 period. This study aimed to determine which method was more appropriate in predicting the company's stock returns. The accuracy of the CAPM and APT methods was measured by using the Mean Absolute Deviation (MAD). The Independent Sample T-test was used to determine whether there was a difference in accuracy between the CAPM and APT methods in predicting stock returns. The results of this study show that by using the calculation of the Mean Absolute Deviation, the APT method is more accurate than the CAPM method in predicting stock returns. The MAD APT value (0.000246) is smaller than the MAD CAPM value (0.003739) and based on data processing from the Independent Sample T-test shows that H0 is rejected, which means that there is a significant difference in accuracy between the CAPM and APT models particularly in predicting the company's stock return.

The Influence of Environmental Change on Pharmaceutical Companies -- Analysis of Opportunities for Pharmaceutical Companies, Take Roche Inc., Pfizer, and Merck. as an example

The impact of natural environment change on biological pharmaceutical companies has become a growing concern in recent years. In response, re-searchers have employed various models to analyze the relationship between natural environment changes and the financial performance of these companies. This paper will use the Capital Asset Pricing Model (CAPM) and Fama-French Three-Factor Model (FF3F) to estimate the impact of natural environment changes on biological pharmaceutical companies. Using secondary data from past studies, this paper conducts a literature review to analyze the impact of natural environmental changes on these companies, particularly in terms of their risk and return tradeoffs. Results from previous research indicate that both CAPM and FF3F models can be used to measure the risk and return trade-offs in the context of natural environmental changes. The CAPM model has been used to identify factors such as natural disasters and climate change that influence the risk of these companies, while the FF3F model has been used to measure the effect of regulatory changes on their stock prices. Overall, this paper brings together previous insights and findings, aiming to provide a deeper understanding of the impact of natural environment change on biological pharmaceutical companies. It concludes that further research is needed to investigate other factors that can influence the performance of these companies in the face of natural environmental changes.

Comparison Analysis Between Accuracy of CAPM and APT Models in Predicting Return of IDX-30 Stocks during Covid-19 Pandemic

This study is done to analyze and compare the accuracy of Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT) Model in predicting stocks’ actual return. The purpose of the study is to find the discrepancy of accuracy of CAPM and APT models in predicting company stocks’ return registered in IDX-30 index from Indonesian Stock Exchange from January 2020-2022. The period is chosen because of the Covid-19 pandemic in Indonesia. The chosen stocks are the stocks which have positive return, never leave the index, never have any changes in stocks’ amount in major and minor evaluation, never do stock split, and have routine dividend payout along the study’s period. The result is there is a significant difference between CAPM and APT models in predicting the actual return based on the result from t-test independent samples. Observed from the Mean Absolute Deviation (MAD) of the two models, CAPM model MAD is smaller than those from APT model, thus CAPM is the more accurate model in calculating return form IDX-30 stocks from January 2020-2022.

Recurrence Plot Analysis of Stock Market Based on CAPM Model and Stock Price Time Series

In this paper, we mainly use recurrence plot, recurrence quantification analysis and cross recurrence plot to investigate the potential nonlinear dynamical characteristics of the stock market. In addition, we introduce and analyze the capital asset pricing model (CAPM), which can analyze the correlation between returns and risks of stock price data. In particular, we selected the large-cap stocks represented by SSE 50 index and the small-cap stocks represented by CSI 500 index as our research objects. Through the recurrence plot analysis of the time series of [Formula: see text] factor of CAPM and the time series of the stock market, we can find the advantages of large-cap stocks, such as stronger stationarity and long-term certainty, the disadvantages of small-cap stocks, such as greater risk and information, and nonlinear cross recurrence with the stock market.