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Faezinia, Vahid, Khajeh Mahmoudabadi, Hamid, Askarzadeh Darreh, Gholamreza, Abtahi, Seyyed Yahya. (1402). Study of the CoAnomaly in Tehran Stock Exchange. , 8(29), 221-238. doi: 10.30495/ijfma.2022.64105.1749
Vahid Faezinia; Hamid Khajeh Mahmoudabadi; Gholamreza Askarzadeh Darreh; Seyyed Yahya Abtahi. "Study of the CoAnomaly in Tehran Stock Exchange". , 8, 29, 1402, 221-238. doi: 10.30495/ijfma.2022.64105.1749
Faezinia, Vahid, Khajeh Mahmoudabadi, Hamid, Askarzadeh Darreh, Gholamreza, Abtahi, Seyyed Yahya. (1402). 'Study of the CoAnomaly in Tehran Stock Exchange', , 8(29), pp. 221-238. doi: 10.30495/ijfma.2022.64105.1749
Faezinia, Vahid, Khajeh Mahmoudabadi, Hamid, Askarzadeh Darreh, Gholamreza, Abtahi, Seyyed Yahya. Study of the CoAnomaly in Tehran Stock Exchange. , 1402; 8(29): 221-238. doi: 10.30495/ijfma.2022.64105.1749

Study of the CoAnomaly in Tehran Stock Exchange

International Journal of Finance & Managerial Accounting
دوره 8، شماره 29، تیر 2023، صفحه 221-238  XML اصل مقاله (468.22 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.30495/ijfma.2022.64105.1749
نویسندگان
Vahid Faezinia1؛ Hamid Khajeh Mahmoudabadi email 2؛ Gholamreza Askarzadeh Darreh2؛ Seyyed Yahya Abtahi2
1Ph.D. Student in Financial Engineering, Islamic Azad University, Yazd Branch,
2Assistant Professor, Department of Finance, Faculty of Management, Economics and Accounting, Islamic Azad University, Yazd Branch,
چکیده
Anomaly correlation is among the essential topics that must be paid attention to in investment. Given the investment portfolio, the return is considered to be more than the expected return, and the premium risk of portfolio components, and portfolio components, and the correlation between portfolio components are investigated so that one can eventually achieve the optimal portfolio. The present study investigates the CoAnomaly in Tehran Stock Exchange. For this purpose, a simple measure of time series risk was presented as CoAnomaly (anomaly correlation) for stock market trade anomalies. This measure is the mean time-varying made up of 12 anomalies. Since the correlation between the underlying assets determines the portfolio variance, CoAnomaly is an important state variable for arbitrators that have a diverse anomaly portfolio to enhance performance. The information and data required in this study were obtained from the information on the firms listed in Tehran Stock Exchange over 2011-2020. Empirically, We show that, CoAnomaly is persistent and forecasts long-run aggregate volatility of the diversified anomaly portfolio. CoAnomaly positively predicts future average anomaly returns in the time series. On the other hand, results revealed that an increase in the CoAnomaly increases anomaly variance over the short term and long term.
کلیدواژه‌ها
portfolio risk؛ portfolio return؛ anomaly correlation (CoAnomaly)
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