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Journal articles on the topic 'Non arbitrage pricing theory'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

Abdillah, Arif, and Aditya Kristamtomo Putra. "Analisis Perbandingan Keakuratan CAPM Dan APT Dalam Upaya Pengambilan Keputusan Investasi Saham Sektor Perbankan." JURNAL AKUNTANSI DAN BISNIS : Jurnal Program Studi Akuntansi 7, no. 1 (May 27, 2021): 42–50. http://dx.doi.org/10.31289/jab.v7i1.4336.

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The Capital Asset Pricing Model and the Arbitrage Pricing Theory are a balance model that uses risk measurement variables to see risk correlations and returns. This research is descriptive quantitative. The purpose of this research is to find out how much the value of stock returns in the banking sector is calculated by the Capital Asset Pricing Model and Arbitrage Pricing Theory, looking for a more accurate model and how big is the difference in accuracy of the significant accuracy of the Capital Asset Pricing Model and Arbitrage Pricing Theory in making investment decisions in the banking sector. The population in this study is a banking company registered at Indonesia Stock Exchange during 2015-2018. The sample in this study amounted to 36 banking companies listed on the Indonesia Stock Exchange during 2015-2018. The sampling method is a non-probability sampling method that is purposive sampling technique. The results of this study indicate that the Capital Asset Pricing Model is better than the Arbitrage Pricing Theory and there is no difference in accuracy between the Capital Asset Pricing Model and the Arbitrage Pricing Theory in an investment decision making effort at banking sector.

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2

Cummins, J. David. "Asset Pricing Models and Insurance Ratemaking." ASTIN Bulletin 20, no. 2 (November 1990): 125–66. http://dx.doi.org/10.2143/ast.20.2.2005438.

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AbstractThis paper provides an introduction to asset pricing theory and its applications in non-life insurance. The first part of the paper presents a basic review of asset pricing models, including discrete and continuous time capital asset pricing models (the CAPM and ICAPM), arbitrage pricing theory (APT), and option pricing theory (OPT). The second part discusses applications in non-life insurance. Among the insurance models reviewed are the insurance CAPM, discrete time discounted cash flow models, option pricing models, and more general continuous time models. The paper concludes that the integration of actuarial and financial theory can provide major advances in insurance pricing and financial management.

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3

Ruge-Leiva, Diego Iván. "The impact of Kiyoshi Ito´s stochastic calculus of financial economics." ODEON, no. 10 (October 6, 2016): 157. http://dx.doi.org/10.18601/17941113.n10.07.

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We discuss the direct or indirect incorporation into financial economics of Kiyoshi Itô´s work on stochastic calculus, particularly the Itô formula, the relevance of his findings for option pricing theory and the way his work has been used to find a unique option pricing function in a competitive and non-arbitrage market. On that basis, we discuss how the option pricing theory may be linked with the general equilibrium theory and other aspects of conventional economics, and finally, Itô’s role in econophysics.

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4

Francová, Blanka. "An Analysis of the Impact of Selected Factors on the Bond Market." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 66, no. 6 (2018): 1451–58. http://dx.doi.org/10.11118/actaun201866061451.

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Exchange rate risk is important factor for the valuation of capital asset on international markets. According to the International Arbitrage Pricing Theory currency movements affect the prices of capital assets and associated risk premiums. The International Arbitrage Pricing Theory is based on total return of asset decomposition to non‑currency return and currency return. The currency return is defined by exchange rate risk and the non‑currency return is defined by factors affecting the price of capital assets. We propose an empirical model to apply this theory using corporate bonds. Using a rich dataset from Morningstar in the period 2001–2017 we employ the linear regression analysis method OLS with fixed effects. We apply the model for different bond yields and different time‑series. The factors influence bond price differently for each yield and each time‑series. Our results confirm that currency movements significantly affect the bond prices.

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5

Ataullah, Ali. "Macroeconomic Variables as Common Pervasive Risk Factors and Empirical Content of the Arbitrage Pricing Theory in Pakistan." LAHORE JOURNAL OF ECONOMICS 6, no. 1 (January 1, 2001): 55–74. http://dx.doi.org/10.35536/lje.2001.v6.i1.a3.

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The Arbitrage Pricing Theory (APT) of Ross [1976] is one of the most important building blocks of modern asset pricing theory, and the prime alternative to the celebrated Capital Asset Pricing Model (CAPM) of Sharpe [1964], Lintner [1965], and others. This paper briefly reviews the theoretical underpinnings underlying the APT and highlights the econometric techniques used to test the APT with pre-specified macroeconomic factors. Besides this, the prime objective of this study is to perform an empirical test of the APT in the Pakistani stock market by using pre-specified macroeconomic factors and employing Iterative Non-Linear Seemingly Unrelated Regressions (ITNLSUR). These empirical results will be, hopefully, helpful for corporate managers undertaking cost of capital calculations, for domestic and international fund managers making investment decisions and, amongst others, for individual investors who wish to assess the performance of managed funds.

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6

Beaulieu, Marie-Claude, Jean-Marie Dufour, and Lynda Khalaf. "Identification-Robust Factor Pricing: Canadian Evidence." Articles 91, no. 1-2 (May 20, 2016): 235–52. http://dx.doi.org/10.7202/1036920ar.

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We analyze factor models based on the Arbitrage Pricing Theory (APT). using identification-robust inference methods. Such models involve nonlinear reduced-rank restrictions whose identification may raise serious non-regularities and lead to a failure of standard asymptotic theory. We build confidence sets for structural parameters based on inverting Hotelling-type pivotal statistics. These confidence sets provide much more information than the corresponding tests. Our approach may be interpreted as a multivariate extension of the Fieller method for inference on mean ratios. We also introduce a formal definition for a redundant factor linking the presence of such factors to unbounded confidence sets, and we document their perverse effects on minimum-root-based model tests. Results are applied to multifactor asset-pricing models with Canadian data, the Fama-French-Carhart benchmarks and monthly returns of 25 portfolios from 1991 to 2010. Despite evidence of weak identification, several findings deserve notice when data are analyzed over ten-year subperiods. With equally weighted portfolios, the three-factor model is rejected before 2000, but weakly supported thereafter. In contrast, the three-factor model is not rejected with value-weighted portfolios. Interestingly in this case, the market factor is priced before 2000 along with size, while both Fama-French factors are priced thereafter. The momentum factor severely compromises identification, which calls for caution in interpreting existing work documenting momentum effects on the Canadian market. This empirical analysis underscores the practical usefulness of our analytical confidence sets.

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7

Hassan, Waqar Ul, Zeeshan Hasnain, and Shahbaz Hussain. "Evaluating the Effectiveness of Asset Pricing Model before, during and after Financial Crisis 2008: Evidence from Karachi Stock Exchange." Business and Economic Research 7, no. 1 (April 23, 2017): 177. http://dx.doi.org/10.5296/ber.v7i1.11106.

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The Study aims to explore the strength of arbitrage pricing model (APT) for determining stock returns of Karachi stock exchange (KSE) across three distinct and structured periods; before financial crisis period (2006-07), during financial crisis period (2008) and after financial crisis period (2009-10). The Study adopted descriptive statistics, Pearson correlation, linear regression, Random effect model for interpretation and execution of data. 253 financial and non-financial listed companies on KSE for the period of (2006-10) are considered as sample firms. Results of regression analysis indicated that models selected for the present study showed poor performance for measuring KSE returns. Independent variables showed significant behavior for measuring KSE returns in pre-financial crisis period; no statistical relationship for measuring KSE returns in during financial crisis period; insignificant nature for measuring KSE returns the post-financial crisis period. The Study has provided understandings about arbitrage theory applicability and financial crisis - 2008 impacts on KSE.

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8

Van Rensburg, Paul. "Macroeconomic identification of the priced APT factors on the Johannesburg Stock Exchange." South African Journal of Business Management 27, no. 4 (December 31, 1996): 104–12. http://dx.doi.org/10.4102/sajbm.v28i4.815.

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Employing prespecified macroeconomic variables as potential priced factors, the Arbitrage Pricing Theory (APT) may be modelled as a non-linear seemingly unrelated regression with across equation restrictions. This portrayal allows for the simultaneous estimation of factor sensitivities and the risk premium associated with each factor. The following macroeconomic variables were tested as potential factors: unexpected movements in (rand) gold returns. (dollar) returns on the Dow-Jones Industrial Index, the term structure of interest rates and inflation expectations together with the 'residual market factor' of Burmeister Wall. Using iterated non-linear seemingly unrelated regression (ITNLSUR) estimation techniques, it was found that all of the above variables except for gold price risk are priced, that is, are associated with statistically significant risk premia.

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9

Van Rensburg, Paul. "Macroeconomic variables and the cross-section of Johannesburg Stock Exchange returns." South African Journal of Business Management 31, no. 1 (March 31, 2000): 31–43. http://dx.doi.org/10.4102/sajbm.v31i1.732.

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This study adopts the Chen, Roll Ross prespecified variable approach to priced arbitrage pricing theory factor (APT) identification on the Johannesburg Stock Exchange (JSE). It is observed that the dichotomy in the return generating processes underlying South African mining and industrial shares leads to cross-sectional correlations in the residual errors of linear factor models that do not employ factor analytically extracted explanatory variables. As a result, a 'two residual market factor' approach is introduced in this study. Employing the iterated non-linear seemingly unrelated regression technique of McElroy Burmeister (1988), it is found that the rand gold price, the rate on long bonds, the Dow-Jones Industrial Index and the level of gold and foreign exchange reserves together with the Industrial and All-Gold residual market factors represent priced sources of risk within the framework of the APT over the period 1985 to 1995. The pricing relationships estimated are found to be inconsistent with those implied by the capital asset pricing model. These results are robust across the 'unconstrained intercept' and 'zero beta' cross-sectional model specifications. The findings of the study, however, imply that the influence of macroeconomic variables on the JSE is most parsimoniously expressed in the two factor APT model of Van Rensburg Slaney (1997).

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10

CHIU, KAI-CHUN, and LEI XU. "NFA FOR FACTOR NUMBER DETERMINATION IN APT." International Journal of Theoretical and Applied Finance 07, no. 03 (May 2004): 253–67. http://dx.doi.org/10.1142/s021902490400244x.

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In the context of quantitative analysis of the arbitrage pricing theory (APT) model, conventional factor analytic approaches such as maximum likelihood factor analysis (MLFA) cannot provide satisfactory answers to two important questions. The first one concerns the correct identification of factor number while the second one is related to the rotation indeterminacy of factor loadings. In the literature, MLFA followed by likelihood ratio (LR) test and the analysis of eigenvalues of sample covariance matrix were two popular approaches used to determine the appropriate number of factors. However, it was shown empirically that both of them suffered from different kinds of biases. We find the recently developed non-gaussian factor analysis (NFA) model by Xu [24] provides a new perspective for the determination of the appropriate factor number k in APT, with promising empirical results demonstrated.

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11

Balaeva, Anastasiasia Yu, and Andrey A. Belyakov. "Algorithm for determining risk-free rates and the size of non-market risks when investing in personnel." Vestnik of Samara University. Economics and Management 11, no. 4 (December 30, 2020): 97–106. http://dx.doi.org/10.18287/2542-0461-2020-11-4-97-106.

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At the present stage of development, many companies treat investments in the development of the company personnel as investments in the creation of intangible assets that contribute to improving the level of competitiveness of the organization. The authors previously proposed an economic and mathematical model of investing in personnel based on the formation of an investment portfolio, which can be used to assess the financial effectiveness of investments in employee development; to get a clear, reliable tool for monitoring the effectiveness of personnel development activities; make the human factor and its impact on the company's performance more measurable; increase transparency and, consequently, the manageability of the organization. The goal of the article is to develop the risk-free rates and non-market risk rates search algorithm during engineering of investment portfolio through arbitrage pricing theory for investment in personnel to return on investment. The authors fully provide risk-free rate of return description and comprise risk-free rates of assets, too. They give an explanation of how to seek and valuate them. Also the expected risk-free returns of assets calculation method and ways of non-market risks management while investing in personnel is described.

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12

Balaeva, Anastasia Yu, and Andrey A. Belyakov. "Methodology for calculating risk factors and assessing the sensitivity of portfolio asset returns when investing in personnel." Vestnik of Samara University. Economics and Management 12, no. 2 (August 5, 2021): 171–79. http://dx.doi.org/10.18287/2542-0461-2021-12-2-171-179.

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The authors previously proposed an economic and mathematical model of investing in personnel and also the algorithm for determining of risk-free and the size of non-market risks. The goals of the article are to develop the threat rates and risk sensitive search methods during engineering of investment portfolio through arbitrage pricing theory for investment in personnel to return on investment. Questions of risk evaluation when choosing assets to invest in human capital of a company are fully provided. The covariance structure of allocation of funds of risk-free part of investment portfoliois addressed, that helps to calculate covariance between return on assets and threat rates of investment patterns that is necessary to find factor betas of portfolio. Also, the matrix of budget sharpening is offered that shows the detail investment budgets risk-free pieces split for all assets having regard to risks. The elements got standard interpretation. Then there is the balance condition that is to implement the proof of calculation. Finally, the method of how to calculate and estimate them is given.

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13

Miller, Edward M. "Arbitrage pricing theory." Journal of Portfolio Management 18, no. 1 (October 31, 1991): 72–76. http://dx.doi.org/10.3905/jpm.1991.409392.

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14

Reisman, Haim. "Intertemporal Arbitrage Pricing Theory." Review of Financial Studies 5, no. 1 (January 1992): 105–22. http://dx.doi.org/10.1093/rfs/5.1.105.

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15

Carassus, Laurence, and Miklós Rásonyi. "Risk-Neutral Pricing for Arbitrage Pricing Theory." Journal of Optimization Theory and Applications 186, no. 1 (June 23, 2020): 248–63. http://dx.doi.org/10.1007/s10957-020-01699-6.

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16

Chang, Shih-Kang, and Latha Shanker. "OPTION PRICING AND THE ARBITRAGE PRICING THEORY." Financial Review 21, no. 3 (August 1986): 17. http://dx.doi.org/10.1111/j.1540-6288.1986.tb00681.x.

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17

Chang, Jack S. K., and Latha Shanker. "OPTION PRICING AND THE ARBITRAGE PRICING THEORY." Journal of Financial Research 10, no. 1 (March 1987): 1–16. http://dx.doi.org/10.1111/j.1475-6803.1987.tb00470.x.

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18

Gilles, Christian, and Stephen F. LeRoy. "On the arbitrage pricing theory." Economic Theory 1, no. 3 (September 1991): 213–29. http://dx.doi.org/10.1007/bf01210561.

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19

Stapleton, Richard, Gregory Connor, Marti G. Subrahmanyam, and Bernd P. Luedecke. "Arbitrage Pricing Theory: The Way Forward." Australian Journal of Management 10, no. 1 (June 1985): 109–30. http://dx.doi.org/10.1177/031289628501000108.

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20

LATHAM, MARK. "The Arbitrage Pricing Theory and Supershares." Journal of Finance 44, no. 2 (June 1989): 263–82. http://dx.doi.org/10.1111/j.1540-6261.1989.tb05057.x.

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21

FRAHM, GABRIEL. "ARBITRAGE PRICING THEORY IN ERGODIC MARKETS." International Journal of Theoretical and Applied Finance 21, no. 05 (August 2018): 1850036. http://dx.doi.org/10.1142/s021902491850036x.

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Traditional approaches to Arbitrage Pricing Theory (APT) propose a factor model, but empirical applications of APT are, nowadays, based on seemingly unrelated regression. I drop the factor model and assume only that the market is ergodic. This enables me to apply the theory of Hilbert spaces in a natural way. The expected return on any asset can always be approximated by an affine-linear function of its betas and we are able to estimate the relative number of assets that violate the APT equation by taking the expected returns and betas in the market into account. I present a simple sufficient condition for the APT equation in its inexact form. Further, I show that the APT equation holds true in its exact form if and only if an equilibrium market is exhaustive, which means that it must be possible to replicate the betas and idiosyncratic risk of each asset by some strategy that diversifies away all approximation errors in the market.

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22

Leković, Miljan. "Scope of the arbitrage pricing theory." Anali Ekonomskog fakulteta u Subotici, no. 42 (2019): 129–45. http://dx.doi.org/10.5937/aneksub1942129l.

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23

French, Jordan. "Macroeconomic Forces and Arbitrage Pricing Theory." Journal of Comparative Asian Development 16, no. 1 (January 2, 2017): 1–20. http://dx.doi.org/10.1080/15339114.2017.1297245.

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24

�etin, Umut, Robert A. Jarrow, and Philip Protter. "Liquidity risk and arbitrage pricing theory." Finance and Stochastics 8, no. 3 (August 1, 2004): 311–41. http://dx.doi.org/10.1007/s00780-004-0123-x.

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25

McKiernan, Barbara. "Uncertainty and the arbitrage pricing theory." Atlantic Economic Journal 25, no. 3 (September 1997): 307–11. http://dx.doi.org/10.1007/bf02298412.

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26

Sick, Gordon, and William T. Ziemba. "Arbitrage theory: Introductory lectures on arbitrage-based financial asset pricing." European Journal of Operational Research 27, no. 2 (October 1986): 255–56. http://dx.doi.org/10.1016/0377-2217(86)90072-x.

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27

Geweke, John, and Guofu Zhou. "Measuring the Pricing Error of the Arbitrage Pricing Theory." Review of Financial Studies 9, no. 2 (April 1996): 557–87. http://dx.doi.org/10.1093/rfs/9.2.557.

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28

Carvajal, Andrés. "Arbitrage pricing in non-Walrasian financial markets." Economic Theory 66, no. 4 (September 8, 2017): 951–78. http://dx.doi.org/10.1007/s00199-017-1074-8.

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29

Abeysekera, Sarath P., and Arvind Mahajan. "International Arbitrage Pricing Theory: An Empirical Investigation." Southern Economic Journal 56, no. 3 (January 1990): 760. http://dx.doi.org/10.2307/1059376.

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30

Clyman, Dana R. "International arbitrage pricing theory: Relating risk premia." International Review of Financial Analysis 6, no. 1 (January 1997): 13–20. http://dx.doi.org/10.1016/s1057-5219(97)90016-8.

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31

Parhizgari, A. M., K. Dandapani, and A. J. Prakash. "ARBITRAGE PRICING THEORY AND THE INVESTMENT HORIZON." Journal of Business Finance & Accounting 20, no. 1 (January 1993): 27–40. http://dx.doi.org/10.1111/j.1468-5957.1993.tb00248.x.

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32

Burzoni, Matteo, Marco Frittelli, Zhaoxu Hou, Marco Maggis, and Jan Obłój. "Pointwise Arbitrage Pricing Theory in Discrete Time." Mathematics of Operations Research 44, no. 3 (August 2019): 1034–57. http://dx.doi.org/10.1287/moor.2018.0956.

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33

CHO, D. CHINHYUNG, CHEOL S. EUN, and LEMMA W. SENBET. "International Arbitrage Pricing Theory: An Empirical Investigation." Journal of Finance 41, no. 2 (June 1986): 313–29. http://dx.doi.org/10.1111/j.1540-6261.1986.tb05038.x.

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34

van Rensburg, P. "Investment Basics: XXXIV. The arbitrage pricing theory." Investment Analysts Journal 26, no. 46 (January 1997): 60–64. http://dx.doi.org/10.1080/10293523.1997.11082381.

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35

Jarrow, Robert A. "Preferences, Continuity, and the Arbitrage Pricing Theory." Review of Financial Studies 1, no. 2 (April 1988): 159–72. http://dx.doi.org/10.1093/rfs/1.2.159.

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36

Connor, Gregory, and Robert A. Korajczyk. "Performance measurement with the arbitrage pricing theory." Journal of Financial Economics 15, no. 3 (March 1986): 373–94. http://dx.doi.org/10.1016/0304-405x(86)90027-9.

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37

Thorbecke, Willem, and Geoff Chisholm. "Nonfarm employment and the arbitrage pricing theory." Economics Letters 47, no. 2 (February 1995): 193–98. http://dx.doi.org/10.1016/0165-1765(94)00537-c.

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38

Rásonyi, Miklós. "Arbitrage pricing theory and risk-neutral measures." Decisions in Economics and Finance 27, no. 2 (December 2004): 109–23. http://dx.doi.org/10.1007/s10203-004-0047-0.

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39

Chang, Jack S. K., Jean C. H. Loo, and Carolyn C. Wu Chang. "THE PRICING OF FUTURES CONTRACTS AND THE ARBITRAGE PRICING THEORY." Journal of Financial Research 13, no. 4 (December 1990): 297–306. http://dx.doi.org/10.1111/j.1475-6803.1990.tb00634.x.

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40

Robin, Ashok, and Ravi Shukla. "THE MAGNITUDE OF PRICING ERRORS IN THE ARBITRAGE PRICING THEORY." Journal of Financial Research 14, no. 1 (March 1991): 65–82. http://dx.doi.org/10.1111/j.1475-6803.1991.tb00645.x.

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41

Hartoyo, Puji. "Perbandingan Pengujian Capital Asset Pricing Model dan Arbitrage Pricing Theory." Indonesian Treasury Review Jurnal Perbendaharaan Keuangan Negara dan Kebijakan Publik 1, no. 1 (June 30, 2016): 51–66. http://dx.doi.org/10.33105/itr.v1i1.60.

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The purposes of this study are to assess the effect of each risk on stock returns and to investigate the equilibrum model that has a smaller standard error. The verificative type of this research used is to verify the hypothesis through data processing and statistical testing. Research data were obtained from secondary data of Indonesia Stock Exchange. The results show that the markert risk and exchange rate premium variables have significant effects as shown in the hypothesis; on the contrary, the SMB, HML and premium inflation variables are not the determinants of stock returns. Meanwhile, the Mean Average Deviation test has proven that the CAPM has a smaller standard error rate than the APT; nevertheless, the average difference test has shown insignificant different rate. This research suggests that market risk and exchange rate premium factors are the main determinants of investment decision. In addition, to maintain the confidence of the investors, a company should maintain the stability of income because the SMB and HML factors are neglected in the investment decision. Abstrak Tujuan penelitian ini untuk mengkaji pengaruh masing – masing risiko terhadap return saham serta melihat model keseimbangan mana yang mempunyai standard error yang lebih kecil. Jenis penelitian ini adalah verifikatif yaitu dengan melakukan hipotesis melalui pengolahan data dan pengujian secara statistik. Data penelitian diperoleh dari data sekunder. Dari hasil penelitian, diperoleh hasil bahwa variabel risiko pasar dan premi kurs berpengaruh secara signifikan dan sesuai dengan hipotesis, sedangkan variabel SMB, HML dan premi inflasi bukan determinan return saham. Hasi pengujian lain dengan menggunakan Mean Average Deviation membuktikan bahwa model keseimbangan CAPM mempunyai tingkat standard error yang lebih kecil daripada APT, namun dengan uji beda rata-rata menunjukkan perbedaan yang tidak signifikan. Penelitian ini memberikan masukan kepada investor bahwa faktor yang perlu untuk diperhatikan sebelum melakukan investasi saham adalah dengan lebih memperhatikan faktor risiko pasar dan premi kurs. Sedangkan bagi perusahaan agar tetap mengusahan stabilitas laba untuk menjaga kepercayaan investor, karena faktor SMB dan HML kurang diperhatikan investor dalam mengambil keputusan berinvestasi.

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42

Hartoyo, Puji. "Perbandingan Pengujian Capital Asset Pricing Model dan Arbitrage Pricing Theory." Indonesian Treasury Review Jurnal Perbendaharaan Keuangan Negara dan Kebijakan Publik 1, no. 1 (June 30, 2016): 51–66. http://dx.doi.org/10.33105/itrev.v1i1.60.

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The purposes of this study are to assess the effect of each risk on stock returns and to investigate the equilibrum model that has a smaller standard error. The verificative type of this research used is to verify the hypothesis through data processing and statistical testing. Research data were obtained from secondary data of Indonesia Stock Exchange. The results show that the markert risk and exchange rate premium variables have significant effects as shown in the hypothesis; on the contrary, the SMB, HML and premium inflation variables are not the determinants of stock returns. Meanwhile, the Mean Average Deviation test has proven that the CAPM has a smaller standard error rate than the APT; nevertheless, the average difference test has shown insignificant different rate. This research suggests that market risk and exchange rate premium factors are the main determinants of investment decision. In addition, to maintain the confidence of the investors, a company should maintain the stability of income because the SMB and HML factors are neglected in the investment decision. Abstrak Tujuan penelitian ini untuk mengkaji pengaruh masing – masing risiko terhadap return saham serta melihat model keseimbangan mana yang mempunyai standard error yang lebih kecil. Jenis penelitian ini adalah verifikatif yaitu dengan melakukan hipotesis melalui pengolahan data dan pengujian secara statistik. Data penelitian diperoleh dari data sekunder. Dari hasil penelitian, diperoleh hasil bahwa variabel risiko pasar dan premi kurs berpengaruh secara signifikan dan sesuai dengan hipotesis, sedangkan variabel SMB, HML dan premi inflasi bukan determinan return saham. Hasi pengujian lain dengan menggunakan Mean Average Deviation membuktikan bahwa model keseimbangan CAPM mempunyai tingkat standard error yang lebih kecil daripada APT, namun dengan uji beda rata-rata menunjukkan perbedaan yang tidak signifikan. Penelitian ini memberikan masukan kepada investor bahwa faktor yang perlu untuk diperhatikan sebelum melakukan investasi saham adalah dengan lebih memperhatikan faktor risiko pasar dan premi kurs. Sedangkan bagi perusahaan agar tetap mengusahan stabilitas laba untuk menjaga kepercayaan investor, karena faktor SMB dan HML kurang diperhatikan investor dalam mengambil keputusan berinvestasi.

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43

Khan, M. A., and Y. Sun. "The capital-asset-pricing model and arbitrage pricing theory: A unification." Proceedings of the National Academy of Sciences 94, no. 8 (April 15, 1997): 4229–32. http://dx.doi.org/10.1073/pnas.94.8.4229.

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Burmeister, Edwin, and Kent D. Wall. "THE ARBITRAGE PRICING THEORY AND MACROECONOMIC FACTOR MEASURES." Financial Review 20, no. 3 (August 1985): 19. http://dx.doi.org/10.1111/j.1540-6288.1985.tb00197.x.

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Burmeister, Edwin, and Kent D. Wall. "THE ARBITRAGE PRICING THEORY AND MACROECONOMIC FACTOR MEASURES." Financial Review 21, no. 1 (February 1986): 1–20. http://dx.doi.org/10.1111/j.1540-6288.1986.tb01103.x.

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SHANKEN, JAY. "The Current State of the Arbitrage Pricing Theory." Journal of Finance 47, no. 4 (September 1992): 1569–74. http://dx.doi.org/10.1111/j.1540-6261.1992.tb04671.x.

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MEI, JIANPING. "A Semiautoregression Approach to the Arbitrage Pricing Theory." Journal of Finance 48, no. 2 (June 1993): 599–620. http://dx.doi.org/10.1111/j.1540-6261.1993.tb04729.x.

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Hamao, Yasushi. "An empirical examination of the Arbitrage Pricing Theory." Japan and the World Economy 1, no. 1 (October 1988): 45–61. http://dx.doi.org/10.1016/0922-1425(88)90005-9.

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Lehmann, Bruce N., and David M. Modest. "The empirical foundations of the arbitrage pricing theory." Journal of Financial Economics 21, no. 2 (September 1988): 213–54. http://dx.doi.org/10.1016/0304-405x(88)90061-x.

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Caporale, Tony, and Willem Thorbecke. "The budget deficit and the arbitrage pricing theory." Economics Letters 41, no. 3 (January 1993): 313–17. http://dx.doi.org/10.1016/0165-1765(93)90159-a.

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