Arbitrage Pricing 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.

Applicability Analysis of Arbitrage Pricing Model in Chinese Stock Market

This paper presents the fundamentals and benefits of the arbitrage pricing model, emphasizing the significance of utilizing arbitrage pricing theory to the growth of the stock market. Firstly, the thesis analyzes and summarizes the mature research on the arbitrage pricing model abroad. This paper, taking into account the unique circumstances of the Chinese stock market, summarizes and contemplates the empirical examination of the arbitrage pricing model's applicability in the Chinese stock market. Most research lines in the Chinese market have been found to be in agreement with the arbitrage pricing principle, yet some studies have come to the contrary result. The fundamental reason is that the analysis of the model needs to be further improved, and China's stock market needs to be developed. Proposals to foster the growth of China's stock market are finally put forth.

Research on the Financial Model Selection between Capital Asset Pricing Model, Arbitrage Pricing Model, and Fama-French Model

Financial modeling magnifies the importance of various systematic and unsystematic risks occurring in modern finance, which elicits the functionality of the Capital Asset Pricing Model (CAPM) introduced by Sharpe, Lintner, and Treynor. A considerable amount of societal support for CAPM has been triggered by its simplicity and precision in terms of making decisions for assets based on absolute risk rather than total risk. Objectively speaking, CAPM is also deeply limited by its unique prerequisites or assumptions. One pivotal point for investors to ponder is the selection of different methods and judge the individual applicability before implementation and this article aims to offer investors some financial advice derived from this process. Methods applied in this article involve information-gathering from empirical examples and tests, as well as financial analysis by comparison and selection among several models. This paper concludes that the Arbitrage Pricing Model (APM) and Fama French factor(s) Model (FFM) are differentiated and should be applied selectively and accordingly to cater to the imminent situations that investors are about to tackle.

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.

Research on Amazon's stock price forecasting based on arbitrage pricing model based on big data

The generation of big data is based on the network data generated when people use Internet information systems to interact. Big data can reflect the general laws of specific fields and industries, provide more accurate references for decision makers and managers, and provide people with better Data services. Arbitrage pricing model has long been widely quoted by scholars as an alternative theory to capital asset pricing model, which is used to make a regression analysis on Amazon's stock price in this study. In our study, we aim to construct an arbitrage pricing model to make a regression analysis on Amazon's stock price, which is demonstrated to have a higher prediction accuracy and better fitting degree compared with the self-coding network. First, six relevant indicators are selected to conduct establishment of arbitrage pricing model. Then, a self-coding neural network is constructed to estimate the influence coefficients of each factor on Amazon's stock price, which are compared with the results obtained by regression analysis. Finally, the following conclusions are obtained that the arbitrage pricing model has a high prediction accuracy for Amazon's stock price, and the fitting degree of the final model can reach 0.996, which is better than that of the self-coding network.

Testing The Indonesian Stock Market Arbitrage Pricing Model

This research aims to explain the return and risk premium using an APT model from the Indonesian stock market. The study uses a two-stage regression model. This study uses a sample of stocks included in the Kompas100 index. The stocks included in Kompas100 represent the market capitalization value from the Indonesian stock market. The originality of this research is the inclusion of foreign macro-factors and the use of surprise or unanticipated factors in the Pre-specified Macro-economic Arbitrage Pricing Theory Model. The results prove that there is a multi-factor APT model consisting of The risk premium for inflation, the risk premium for interest rates, and the risk premium for foreign macroeconomic factors represented by the Dow Jones index and the Shanghai index. The results of this study further strengthen the theory and previous research on the multi-factor APT model.

Analytical View of Pricing Weather and Freight Derivatives: 1950–2020

A weather derivative is financial instrument that companies or individuals use to hedge against the risk of weather-related losses. Freight derivatives value is derived from the future levels of freight rates, like a dry bulk-a category of cargo stowed in bulk, consisting of grain, cotton, coal, etc., carrying rates, and oil tanker rates. Numerous empirical studies exist on weather and freight derivatives and their pricing models such as Indifference Pricing Approach, Arbitrage Pricing Model, Financial Pricing model, Benchmark Pricing Approach, Fair Pricing Approach, Actuarial Pricing, Consumer Based Pricing Method, and Index Modeling. This paper aims to address issues relating to the functioning of weather and freight derivatives. This paper also focuses on the studies published on weather and freight derivatives’ pricing models during the last seven decades (i.e., 1950–2020). Objectives: (1) To understand the vital issues relating to models of weather and freight derivatives. (2) To compare pricing models of weather and freight derivatives during the last seven decades (i.e., 1950–2020).

Risks and risk premiums of GE corn: A macromarketing framework

It has been more than two decades since genetic engineered (GE) corn has been introduced in the United States and Spain. Despite the wide scale adoption of GE corn, (92% of planted acreage in the US in 2017), biodiversity conservation, environmental protection goals, and food safety continue to surface as potential risk factors. We developed a macromarketing framework to provide a linkage between the consumers, producers, and societal impacts of GE corn. An empirical Arbitrage Pricing Model (APT) was used to quantify risks and risk premiums associated with GE corn production. The risk premium deduced from the APT model provides a measure of intrinsic compensation for taking on higher or lower risks by participants in the marketing system. An Auto-Regressive Distributed Lag (ARDL) regression estimation of the APT model reveals that GE causes corn prices to go down due to increase supply, but significantly reduced the risk premium for producing corn in the United States. GE corn also provided environmental beneficial outcomes by reducing the use of fertilizers.

Exchange rate exposure in the South African stock market before and during the COVID-19 pandemic

We examine the nature of exchange rate exposure before and during the COVID-19 pandemic. Using a multifactor arbitrage pricing model and daily data from South Africa, we show that, as compared with sectors, industries have been more exposed to the exchange rate risk during than before the pandemic. We further show that exchange rate exposure mostly hurts the sectors and industries, although a few sectors, such as beverages, mining, personal goods, and tobacco, and industries, such as basic materials, consumer goods, and technology, may benefit from it. Our estimates survived robustness checks.

БАГАТОФАКТОРНІ МОДЕЛІ ОЦІНЮВАННЯ ІНВЕСТИЦІЙНИХ ПРЕМІЙ: АНАЛІЗ ДИСКУРСУ ТА МІСЦЕ В СУЧАСНІЙ ТЕОРІЇ МІЖНАРОДНОГО ПОРТФЕЛЬНОГО ІНВЕСТУВАННЯ

The paper dwells on multi-factor models of individual securities and investment portfolios expected returns and investment premiums valuation. Main stages of these models appearance and development are discovered. Theory and practice realized that single-index models were not relevant in terms of estimating expected returns, since at least several basic factors affected premiums substantially. Notwithstanding the basic principle of compensating risk beared by respective return remained unchanged two new models – intertemporal CAPM and international CAPM were underlying dynamic development of multi-factor models. The latter along with market risk factor considered other premium components like those resulting from exchange rate risks for different currencies. Components of scientific discourse in this field are identified, position of models under question in contemporary theory of international portfolio investing is defined. Multi-factor models expanded and enhanced portfolio paradigm of international investing, particularly its specific concept of expected returns valuation. Unlike some other paradigm components this concept is proved to be positive theoretically and well applicable in practice. Factors of international models of investment premiums valuation origin are specified. More precise emphasize is made on international multi-factor CAPM and APT models. More cross functional nature of arbitrage pricing model compared to CAPM is justified. Gnoseological status of Fama and French multi-factor model is specified. Its affiliation with both existing paradigms of international investing – value investing and portfolio paradigm is argued. This in turn determines its unique position in existing knowledge in the field. Technically and methodologically it was developed on the ground of traditional CAPM model – it implies existing risk factor, specific sensitivity ratio to the existing risk factor and respective investment premium. This justifies the model affiliation with traditional and dominating portfolio paradigm of international investing. On the other hand, in its current version the model completely corresponds with value paradigm principles. Intrinsic, internal value of securities is defined, the valuation is subjective, traditional fundamental analysis ratios like book-to-market value index are used. The model thus establishes particular connection between two paradigms of international portfolio investing.

Arbitrage Pricing Model Based on Factor Analysis-Random Forest Regression and its application

Firstly, this paper establishes K-factor linear model and arbitrage pricing model (ATP) according to ‘the Asset Pricing Model-Arbitrage Pricing Theory’, Then from 2001 to 2017, the Statistical Yearbook of the National Bureau of Statistics collected 10 factors as the original factors such as gross national product, gross industrial product and gross tertiary industry product. After synthesis and simplification, three common factors are extracted to replace ten original factors.The first common factor variable is used to reflect the overall economic level of the country;The second common factor variable reflects a country's inflation rate;The third public factor variable reflects the total annual net export trade situation of the country. After the common factor is determined, the value of the common factor is calculated from the original data.Collect the annual return of 10 stocks for 17 years and do twice random forest regression,we get the arbitrage pricing model. Then, based on the same common factor data, another arbitrage pricing model is obtained by imitating the linear regression method of previous similar papers. By comparing the pricing error, we can find the pricing effect of the model obtained by random forest regression is better than that of the model obtained by linear regression.

Estimation of return stock rate by using wavelet and kernel smoothers

This article aim to estimate the Return Stock Rate of the private banking sector, with two banks, by adopting a Partial Linear Model based on the Arbitrage Pricing Model (APT) theory, using Wavelet and Kernel Smoothers. The results have proved that the wavelet method is the best. Also, the results of the market portfolio impact and inflation rate have proved an adversely effectiveness on the rate of return, and direct impact of the money supply.

A Proposed Model to Interpret the Behavior of Macroeconomic / Market Variables and Their Linkage with the Saudi Petrochemical Sector: نموذج مقترح لتفسير سلوك المتغيرات الاقتصادية الكلية والسوقية وعلاقتها بعائد قطاع البتروكيماويات السعودي

The study seeks to identify the economic and the market factors that، effect on the returns of the petrochemical sector market listed at the Saudi Tadawul market، using the arbitrage pricing model to estimate the return of the petrochemical sector، using some economic variables such as changes in oil prices، the growth rate in the gross national product and the rate of inflation. The study found through the multi linear regression model showed that، there is a positive relationship between the returns of the petrochemical sector with the market value، money supply، and the treasury bill returns. The researchers recommended that، the study be conducted on other economic variables and for a longer period، as well as measure the impact of economic variables on the returns of the Saudi market using other sectors.

From small markets to big markets

We study the most famous example of a large financial market: the Arbitrage Pricing Model, where investors can trade in a one-period setting with countably many assets admitting a factor structure. We consider the problem of maximising expected utility in

Interest Rate Parity with Credit Risk: Implications for Carry Trades

The incredible profitability of the carry trade over the past six decades constitutes a puzzle for interest rate parity. Contrary to recent behavioral or friction-based approaches that explain deviations from traditional interest rate parity, I derive interest rate parity in a general arbitrage pricing model of foreign exchange with credit-risky sovereign lending and sharp currency devaluations associated with default; in particular, foreign sovereign credit risk makes forward contracts more valuable relative to standard covered interest rate parity. I calibrate the model for Mexico and the United States, and find that credit risk and currency devaluation fully account for the profitability of both the covered and uncovered carry trade. Modest default probabilities are sufficient to explain deviations from covered interest rate parity for G10 countries. I find support for the recent notion that the United States is a global provider of safe assets, via default intensities implied by currency forward contracts.

Linear beta pricing with inefficient benchmarks in a given factor structure

ABSTRACTWe show the equivalence between the zero-beta version of a multi-factor arbitrage pricing model and a linear pricing model utilizing undiversified inefficient benchmarks in a given factor structure. The resulting linear model is a two-beta model, with one beta related to the inefficient benchmark and another adjusting for its inefficiency. This linear model shows that there are only two distinctive and computable sources of risk, affecting security expected returns, despite the existence of several risk factors. In a short empirical example we demonstrate that the model can be employed to provide guidance and allow researchers to test for the validity of their selection of the underlying risk factors driving variations in security returns.

Linear Beta Pricing with Inefficient Benchmarks in a Given Factor Structure

We show the equivalence between the zero-beta version of a multi-factor arbitrage pricing model and a linear pricing model utilizing undiversified inefficient benchmarks in a given factor structure. The resulting linear model is a two-beta model, with one beta related to the inefficient benchmark and another adjusting for its inefficiency. This linear model shows that there are only two distinctive and computable sources of risk, affecting security expected returns, despite the existence of several risk factors. In a short empirical example we demonstrate that the model can be employed to provide guidance and allow researchers to test for the validity of their selection of the underlying risk factors driving variations in security returns.

An Illustration of a Modified-Machlup (mM) Assessment for Resolving When Experts Disagree (WED) Issues as Applied to Three Archetypal Examples for Model Validation: Yule-Simpson Paradox (YSP), Fair Employee Compensation (FEC), and Put-Call Parity (PCP)

This paper (1) introduces a modified-Machlup (mM) assessment, as well as DQA and DQE concerns and a DQXY Thesis that tie the mM assessment to the Duhem-Quine (DQ) Thesis and theories of model validation (TMV), and then (2) applies the mM and DQA/DQE concepts to three archetypal models (i.e., YSP, FEC, and PCP) that (2a) represent both (observational) empirical and (theoretical) analytical models and (2b) illustrate “when experts disagree” (WED) issues, including (2c) issues that a Board might face as part of a corporate governance of model validation (CGMV) concern, including for corporate finance concerns (and, hence, CGMVCF), and (2d) issues that can be generalized to more-complex models that a Board also likely faces (e.g., assessing performance measures and valuing financial derivatives) in its role as a monitor of corporate activity. Since the Board may (3) not be technically trained in mathematics and statistics, (3a) a “novice-expert problem” (NEP) is also identified, for which (3b) an Evaluator-Decider-Advisor-Choice (EDAC) solution concept is introduced. The EDAC solution concept can utilize the mM and DQA/DQE attention-directing tools to help solve or resolve the NEP-WED issue for the Board. (4) An archetypal micro-CGMV story is introduced, and its application to the three archetypal models leads to two broad conclusions that a less-technically-trained Board would likely be interested in. First, regression equation coefficient estimates cannot necessarily identify unique factor sensitivity. Second, arbitrage pricing models cannot identify valuation for stand-alone financial instruments (including financial derivatives), especially those held for risk bearing; accordingly, any use of arbitrage pricing techniques may misrepresent corporate risk exposure and valuation. The key to both conclusions is understanding the conditionalities involved in the various models being utilized for argument purposes, especially as rote calculations, with such conditionalities fundamentally relating to the DQ Thesis. Accordingly, the mM and DQA/DQE assessments (1) help lead to the two conclusions and identify the DQ Thesis concerns involved, (2) help identify Bad Creativity (i.e., creativity that misleads) arising from misuse of mathematical technology, (3) help identify the Missing Premises in flawed enthymemic rhetorical argumentative structures and, consequently, (4) help Boards make better decisions.

Industry structure, macroeconomic fundamentals and return on equity

PurposeThe purpose of this paper is to examine the impact of industry structure and macroeconomic indicators on return on equity (ROE) of listed financial services firms.Design/methodology/approachHerfindahl–Hirschman Index concentration scales were used to categorise industries into competitive, moderate and concentrated segments, while Arbitrage Pricing Model principles were used to capture the effect of macroeconomic fundamentals on ROE. Generalised method of moments estimator was used to model random effects which were supported by the Hausman test.FindingsFindings suggest that the influence of macroeconomic fundamentals on ROE deteriorates as one moves from competitive to concentrated industries. ROE is volatile in concentrated markets and less volatile in competitive markets. Concentrated markets generally enjoy monopoly profits. Gross domestic product and interest rates have a positive impact on ROE, while inflation, unemployment and exchange rates have a negative effect.Originality/valueThis study highlights the need to apply appropriate business strategies and policies depending on the structure of the industry. Competitive advantage strategies may assist in sustaining profits of firms in competitive markets. Regulators need to be proactive and stress test the impact of a policy on industry performance before implementation because competitive and concentrated markets react differently to external shocks. Risk tolerant investors may invest in volatile markets such as Russia and South Africa, while risk-averse investors may prefer to invest in less volatile markets such as India and China.

Dynamics of the impact of currency fluctuations on stock markets in India: Assessing the pricing of exchange rate risks

This paper studies the dynamics of the impact of currency fluctuation on Indian stock market by assessing the pricing of exchange rate risk during the period 2005–2016, specifically before and after financial crises. Estimating a two-factor arbitrage pricing model, using a random coefficient model, the paper presents evidence that stock returns react significantly to foreign exchange rate fluctuations in the post-crisis period. Particularly, during the last four years of our sample, 2012–2016, the exchange rate risk factor is becoming a prominent determinant of stock returns, indicating that Indian investors are increasingly expecting a risk premium on their investment for their added exposure to exchange rate risk. This is also further corroborated by the study by highlighting the fact that higher the foreign exchange exposure of industry, measured by trade balance (net inflows), higher is their sensitivity to exchange rate risk (βS). A plausible reason for such premium could be the inadequate hedging by Indian firms to mitigate the exchange rate risk.