The test of the Fama-MacBeth model to measure the relationship between the expected investment risk metrics and the expected rate of return for knowledge-based companies active in the Tehran Stock Exchange
الموضوعات :
Shabnam Shayestehfar
1
1 - Department of Accounting, Faculty of Management, Tehran University, Tehran, Iran
تاريخ الإرسال : 17 الثلاثاء , جمادى الثانية, 1444
تاريخ التأكيد : 11 الإثنين , شوال, 1444
تاريخ الإصدار : 12 الخميس , ذو القعدة, 1444
الکلمات المفتاحية:
Knowledge-Based Companies,
Expected Return,
McBeth Fama Model,
Risk Indexes,
ملخص المقالة :
The main purpose of this research is to measure investment risk indicators (standard deviation risk, half standarddeviation, parametric and historical value at risk and parametric and historical; HR) and test their relationship withthe expected price return rate for knowledge-based companies active in the stock market. For this purpose, a sampleconsisting of 31 knowledge-based companies active in the Tehran Stock Exchange was selected during the period of2016 to 2021 and the risk indicators of standard deviation, half standard deviation and value at risk were selectedbased on We tested the McBeth Fama model in relation to the expected rate of return. The research results show thatthere is a significant relationship between volatility risk indicators and adverse risk for the expected rate of return.Also, the research findings showed that controlling factors such as company size, financial leverage, book value tomarket value, liquidity, momentum and inverse are not able to change the positive relationship of the risk criteriaexamined on the expected return.
المصادر:
Eslami Bigdali, Gholamreza; Shahsoni, Dawood (2013); "Evaluation of the ability of the model based on stock characteristics compared to the three-factor model of Fama and French in explaining the difference in stock returns." 2014 - Companies admitted to the Tehran Stock Exchange in the period of 2016. Accounting and Auditing Research Quarterly. Iran Accounting Association, fourth year. Number thirteen. Spring.
Radpour, Maitham, and Abdo Tabrizi, Hossein (2008) Market risk measurement and management, value at risk approach, Aghaz Publications, 1st edition.
Namazi, Mohammad, and Shokrollahi Khajovi (2017) The usefulness of accounting variables in predicting the Tehran Stock Exchange. Systematic risk accounting reviews of companies accepted in, year 11, number 37, pp. audit and. 119-93.
Li, Rodney N. Sullivan, Luis Garcia-Feijoo (2020); “The Low-volatility Anomaly: Market Evidence on Systematic Risk Versus Mispricing”, Forthcoming, Financial Analysis Journal.
Rahat, Achtani. (2019), “The low volatility anomaly in the U.S and in India – An Evaluation in light of difference”, MSc in Financial Markets 2012-2013.
Turan G.Bali, & Nusret Cakici (2018): “Value at Risk and Expected Stock Returns”, Financial Analysts Journal, Vol. 60, No. 2, pp. 57-73.
Ang, Andrew., Hodrick, Robert J., Xing, Yuhang., & Zhang, Xiaoyan. (2009). “High idiosyncratic volatility and low returns: International and further U.S. evidence”. Journal of Financial Economics, 91(1), 1-23.
Blitz, D., & Van Vliet, P. (2007). “The volatility effect: Lower risk without lower return”. Journal of Portfolio Management, 34, 102–113.
Drew, Michael E., Marsden, Alastair., & Veeraraghavan, Madhu. (2007). “Does Idiosyncratic Volatility Matter? New Zealand Evidence”. Review of Pacific Basin Financial Markets and Policies (RPBFMP), 10(03), 289-308.
Fama E.F. (1968). “The Behavior of Stock Market Prices”. Journal of Business.38, 34-105.
Ang, Andrew., Hodrick, Robert J., Xing, Yuhang., & Zhang, Xiaoyan. (2006). “The Cross-Section of Volatility and Expected Return”. The Journal of Finance, 61, 259-299.
Amihud, Yakov, (2002), “Illiquidity and stock returns: cross-section and timeseries effects”, Journal of Financial Markets, 5, 31-56.
Bali, T., & Cakici, N. (2004). “Value at risk and expected stock returns”. Financial Analysts. Journal, 60, 57–73.
Baker, M., Bradley, B., & Wurgler, J. (2011). “Benchmarks as limits to arbitrage: Understanding the low-volatility anomaly”. Financial Analysts Journal, 67, 40–54.
Fu, F. (2009). “Idiosyncratic risk and the cross-section of expected stock returns”. Journal of Financial Economics 91 (1), 24–37.
Robin, A., & Zhang, H. (2015). Do industry-specialist auditors influence stock price crash risk? Forthcoming in auditing. A Journal of Practice & Theory (AJPT). 34(3):
47