Firms

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.

This chapter discusses theoretical foundations and empirical evidence for the most prominent asset pricing theory: the Capital Asset Pricing Model (CAPM). It represents a pricing model for risky assets. The CAPM has been extended to the multi– factor model (MFM) and arbitrage pricing theory (APT). The motivation of the latter has been to overcome the problems associated with the market portfolio in the CAPM by introducing a multi–factor approach. The subsequent chapter is kept simple and refers to the CAPM only. In some additional remarks crucial assumptions regarding investors’ preferences and stock return distributions are relaxed. Currently the debate whether exact pricing restrictions in the MFM and APT imply the return to the “good old CAPM” is still going on. By introducing state dependent relationships as well as general nonlinearities in a CAPM model one can try to unify the different views but we will not elaborate on such extensions. A more extensive treatment of static and dynamic portfolio theories is given in Part VI of the book.

This paper uses three models to estimate the financial performance of 33 securities traded on the Athens Stock Exchange (ASE). To estimate the expected returns, this study uses the Capital Asset Pricing Model (CAPM), the Market Model, and the Arbitrage Pricing Theory (APT). There is significant evidence that the APT performs better than the CAPM and the Market Model, while the differences between the CAPM and the Market Model appear not to be significant. The three models are tested for a five-year period from 2000 to 2005. Total risk is significantly negatively related to returns during down markets, while this relationship is positive but not significant in up markets. There is evidence that, apart from the market risk, other risk factors that influence the stock returns are the inflation rate and the exchange rate.

Chapter 4 The arbitrage pricing theory and multifactor models of asset returns

Stock prices are usually analysed and explained in terms of underlying financial indicators, such as earnings per share or dividend payout ratios. Nevertheless, fluctuations in the conditions of the economy can result in changes in demand, which can impact on profits and dividends. Since macroeconomic variables affect financial indicators it follows that macroeconomic variables affect stock prices. If markets are rational and efficient, then stock prices will reflect all known information regarding macroeconomic factors that are perceived to affect stock prices. It follows that stock prices should not change significantly unless there is a surprise or news about the state of the economy (as reflected in unexpected changes in macroeconomic variables). Intuitively, this implies that models of stock price determination based on news ought to be superior to conventional models that use the levels or changes in variables. The utilisation of news in research on stock prices is very limited. Two approaches have been traditionally used to represent the news in the absence of surveys of expectations: either by assuming announcements are news such as those in event studies or by using an econometric time series approach to extract the news components from total changes in the variables, as is the case with the news model. The majority of studies involving news models have been in the foreign exchange market using news estimated econometrically—very little has been done in estimating and testing a macro news model of stock prices and certainly nothing has been done on stock prices in developed economies such as Australia. Thus this research is motivated by the significant gaps in the literature with respect to the development, estimation and testing of a news model of stock prices. Most of the studies that investigate the relations between macro variables and stock prices have been carried out using conventional approaches by estimating models that use the variables in their levels. Some of the multivariable models of stock prices arise as a result of anomalies found in implementing the capital asset pricing model. Other multivariable approaches such as the arbitrage pricing theory (APT), due to Ross (1976), suggest that macro variables are useful, but APT is silent on the appropriate macroeconomic explanatory variables. Furthermore, there have been limited attempts to examine macroeconomic variables collectively, but not with the aim of developing a macro model of stock prices. This thesis presents the results of research that uses comprehensive econometric procedures to investigate which macroeconomic variables have significant effects on Australian stock prices and whether news about such variables can enhance the performance of conventional stock price determination models. Seven macroeconomic variables are examined: interest rates, inflation, the money supply, economic activity, commodity prices, exchange rates and a foreign stock market index to account for spill-over effects. This provides a valuable contribution to the understanding of the individual effects of macroeconomic variables on stock prices and adds to the limited literature regarding the usefulness of news in models of stock price determination. The results from this research demonstrate that although news is a theoretically sound and intuitively plausible basis for improving macro models of stock prices, in practice there is no ex-ante exploitation possible by estimating news utilising econometric methods. Simply put, news cannot be predicted—this is established by using three comprehensive methods of estimating news, which is the residual of a model fitted to the time series data of a particular variable.

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.

Portfolio efficiency of APT and CAPM in two Scandinavian stock exchanges

This research aims to determine the influence of each model of balance used for determining the return of shares measured by CAPM and APT in telecommunications sector companies listed on the Indonesia Stock Exchange period 2016-2018. The data collection method uses purposive sampling. The population used in this research is the stock price on telecommunication telecommunications sectors listed on the Indonesia Stock Exchange. The purpose of this research is to compare the accuracy of Capital Asset Pricing Model (CAPM) and Arbitrage Pricing Theory (APT) in estimating the return of telecommunication stock return. From the results of the Median Absolute Deviation (MAD) value has a small difference. Based on the results of Independent Sample T-Test can be concluded that there is no significant difference between CAPM and APT method in predicting the return of telecommunications stocks return.

Portfolio management plays a significant role in the world of finance and investing, offering benefits and contributions to both individual investors and institutions. Researchers use many mathematical models to make informed decisions about how to allocate and manage investments within a portfolio to optimize risk versus return trade-off based on the investors preference and constraints. This paper primarily employs the literature review methodology and comparative analysis methodology. Firstly, it collects, summarizes, and analyzes multiple papers on portfolio management models, including Markowiz Mean-Variance Model, Capital Market Line (CML), Arbitrage Pricing Theory (APT) and Capital Asset Pricing Model (CAPM) with the origin of the models, their key assumptions, components, and applications. Additionally, this paper also utilizes comparative analysis by comparing the similarities, differences, and respective downsides and benefits of the four main research models. Through this comparison, the paper investigates the relationships and application distinctions among the models. As a result, these models evolve and refine over time, with some building on others. CAPM extends the Markowitz Model by introducing the risk-free rate and market portfolio as benchmarks, simplifying the risk-return relationship, and introducing systematic risk. The Capital Market Line (CML), derived from CAPM, illustrates efficient portfolios made up of both market and risk-free assets and shows the risk-return trade-off. APT, a later model, can be seen as an extension of CAPM.

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.

The impact of the economic crisis caused investors have difficulty in analyzing and predicting stock returns of the company. No exception to the banking industry shares are listed on the Indonesia Stock Exchange (BEI). In predicting stock returns are expected, there are two models that are often used by investors, the capital asset pricing model (CAPM) and the arbitrage pricing theory (APT). APT basically use reasoning stating that two investment opportunities that have the same characteristics identical bias not sold with different prices. The concept used is hokum one price (the law of one price). Analysis used in the study is the analysis of two different test average. Where comparing ten banking industry Stock Exchange Securities registered Indonesian (IDX). After conducting a hypothesis test using the SPSS output in the form of test results obtained bedadua average dependent samples, bahwathitung for APT testing by comparing the actual return (Ri) and expected return (ERI) stock with a variance equal to propabilitas assumet is 0.290 0,1.620. Therefore, P-value 0.290> 0.05, results showed that the expected return is not berbedas ignifikan with actual return (significant 0.290) This means that the hypothesis stated:. "Allegedly expected return results Arbitrage Pricing Theory model predictions with actual return on the banking industry that went public in the Indonesia Stock Exchange rejected. Therefore, the expected return does not differ significantly from the actual return the Arbitrage Pricing Theory Accurate models. Results of research conducted by the author, states that testing APT (Arbitrage Pricing Theory) by comparing Actual return (Ri) with Expected return (ERI) to measure stock returns is no difference. This means that the APT does not affect stock returns padaindustri banks that went public on the stock exchanges of Indonesia.

The purpose of the study had been aimed to further the understanding in exploring the relevance performance of the monopoly stock of Tenaga Nasional Berhad (TNB) to assess the stock performance return in comparison against the Malaysian stock market with reference towards the measurement of the Kuala Lumpur Stock Exchange (KLSE) market index performance as the benchmark. With reference to the previous studies, there is relevance support to identify the tendency of the findings to suggest the higher performance for the major stocks like TNB stock where the business model of TNB being monopolizing the industry creating the upper hand for the stability in driving the revenue and profit leading to higher value in the stock price. The methodology of the research had further the quantitative analysis study using the historical data of 10years from 2014 to 2023 to identify the potential pattern and trend to assess the comparison for the performance and trading trend for both the TNB stock and market index of KLSE. The outcome of the research had suggested the sufficient evidence to identify the higher average return for the TNB stock over the negative return average being achieved by the KLSE market index putting clear picture on the higher performance of the monopoly TNB stock. In addition, the growth of the trading volume trend had suggested that the investors are being higher confidence towards the growth of the TNB stock where the growth of the trading volume for TNB stock is higher than the trading volume for KLSE market index and even exceeding the average return for the TNB stock. 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The two most important static models of security markets — the Capital Asset Pricing Model (CAPM), and the Arbitrage Pricing Theory (APT) — have a common feature that expected returns of a possibly large number of securities satisfy a linear relationship with measures of sensitivity of returns to few common factors. In the CAPM, there is a single factor — the market return — and the pricing relation is exact. In the APT, there are multiple factors and the pricing relation is approximate. The nature of static (two-date) security markets models is such that trade occurs only once, followed by terminal realization of agents’ wealth and simultaneous maturity of all securities. Of course, when static models are used in empirical tests, time-series data on one-period security returns is used and various stationarity properties are assumed.

The persistence of performance of the General Equity Unit Trusts and All Unit Trusts that traded in South Africa during the period January 1988 to December 1997 and January 1993 to December 1997, is analysed using three models of performance measurement, namely the Capital Asset Pricing Model, a two-factor Arbitrage Pricing Theory model and a three-factor Arbitrage Pricing Theory (APT) model developed in this study. The Capital Asset Pricing Model does not explain the relative returns of the different portfolios. Both APT models account for almost all of the cross-sectional variation in expected returns. It is shown that there is evidence of both short-term and long-term persistence in performance of South African unit trusts. It appears that the worst performing unit trust portfolio tends to stay the worst performer. The portfolio of unit trusts with an average monthly return may eventually become the top performing portfolio, while the top performer over time tends to becomes an average performing portfolio.

In a competitive market, what should the rate of return on insurance companies’ equity be? What premiums should insurance companies charge? Traditionally, the answers to these questions have been based on actuarial and accounting concepts.1 More recently financial models of the insurance firm have been developed. Ferrari (1968) suggested a descriptive model which allowed an algebraic expression for the rate of return on equity as a function of the premiums charged to be derived. Combining this with the capital asset pricing model (CAPM) meant that an equilibrium value for the return on equity and the corresponding level of premiums could be found. This model is known as the insurance CAPM.2 The development of other asset pricing models in finance has also led to insurance counterparts. Thus the Arbitrage Pricing Theory, and option pricing models have been used to derive the return on equity and the level of premiums.3 Although the approaches based on asset pricing models have advantages compared to those based on traditional actuarial and accounting concepts, they are not ideal. One of the most important problems is that they are not well suited for finding premiums when an insurance company has multiple divisions. The difficulty is that it is not clear how earnings on reserves should be allocated among the various divisions of the firm.