تعیین آثار ناهنجاری های تقویمی در شرکت‌های صنعت خودرو پذیرفته شده در بورس اوراق بهادار تهران از طریق روش تحلیل چیرگی تصادفی

محورهای موضوعی : پژوهش های مالی و رفتاری در حسابداری

سهند وهابی ¹ , بهاره بنی طالبی دهکردی ^{2 *}

1 - کارشناسی ارشد، گروه حسابداری، واحد شهرکرد ، دانشگاه آزاد اسلامی ، شهرکرد، ایران
2 - عضو هیات علمی، گروه حسابداری، واحد شهرکرد ، دانشگاه آزاد اسلامی ، شهرکرد، ایران

تاریخ دریافت : 1402/01/24 تاریخ پذیرش : 1402/03/17 تاریخ انتشار : 1402/04/01

کلید واژه: ناهنجاری‌های تقویمی, تکنیک الکتره, تحلیلی چیرگی تصادفی, بازده شاخص,

چکیده مقاله :

امروزه داشتن آگاهی و شناخت کافی سرمایه‌گذاران از وجود ناهنجاری‌ها همچنین نوع واکنش صنایع موجود در بازار سرمایه، می‌تواند تاثیر عمده‌ای در رونق اقتصادی بازار سرمایه داشته باشد. از این‌رو، هدف این پژوهش بررسی تأثیر ناهنجاری‌های تقویمی بر بازده شاخص شرکت‌های پذیرفته شده در بورس اوراق بهادار تهران در حوزه صنایع خودرو در بازه زمانی سال‌های 1399-1395 است. پژوهش بر پایه روش تحلیل چیرگی تصادفی و با استفاده از تکنیک الکتره که یک روش نوین در تحقیقات مالی می‌باشد، انجام شده است. یافته‌ها نشان می‌دهد سه فرضیه اصلی مبنی بر وجود تفاوت معنادار بین بازدهی شاخص صنایع خودرو در روزهای شنبه تا چهارشنبه، در هفته‌های اول، دوم، سوم و چهارم هر ماه و در ماه‌های فروردین تا اسفند هر سه رد شدند که نشانگر عدم کارایی شرکت‌های صنعت خودرو بورس اوراق بهادار تهران است. همچنین بر‌اساس یافته‌های پژوهش مشخص گردید در بین روزهای هفته، روز شنبه و در بین هفته‌های هر ماه، هفته اول، مناسب‌ترین روز و هفته جهت سرمایه‌گذاری در صنعت خودرو می‌باشد. علاوه بر این، بهترین ماه برای سرمایه‌گذاری در صنعت خودرو اسفندماه و بدترین ماه نیز خردادماه است.

چکیده انگلیسی:

Today, having enough knowledge and understanding of investors about the existence of anomalies as well as the type of reaction of industries in the capital market can have a major impact on the economic prosperity of the capital market. Therefore, the purpose of this research is to investigate the effect of calendar anomalies on the index returns of companies listed in the Tehran Stock Exchange in the field of automobile industry in the period of 2015-2018. The research was done based on the random dominance analysis method and using the Electra technique, which is a new method in financial research. The findings show that the three main hypotheses that there is a significant difference between the efficiency of the automobile industry index on Saturday to Wednesday, in the first, second, third and fourth weeks of each month and in the months of April to March, all three are rejected. which indicates the inefficiency of automobile industry companies of Tehran Stock Exchange. Also, according to the findings of the research, it was determined that among the days of the week, Saturday and among the weeks of each month, the first week, is the most suitable day and week for investing in the automobile industry. In addition, the best month for investing in the automobile industry is March and the worst month is June.

منابع و مأخذ:

 Abbasian, E., Moradpour Oladi, M., & Abbasiuon, V. (2008). The Impact of Macroeconomic Variables on the Stock Market: Evidence from Tehran Stock Exchange Market. Iranian Journal of Economic Research, 12(36), 135-152. (In Persian)

Aharon, D. Y., & Qadan, M. (2019). Bitcoin and the day-of-the-week effect. Finance Research Letters, 31.

Ali, S., Green, P., & Robb, A. (2015). Information technology investment governance: What is it and does it matter? International Journal of Accounting Information Systems, 18, 1–25.

Anderson, T. W. (2011). The statistical analysis of time series. John Wiley & Sons.

Anjum, S. (2020). Impact of market anomalies on stock exchange: a comparative study of KSE and PSX. Future Business Journal, 6(1).

Ataei, M. (2009). Multi-criteria Decision Making (M. Keneshlou, Ed.). Shahrood University of Technology. (In Persian)

Azimi, J., Mineindeen, M., & Zadeh, H. T. (2012). Calendar and non-calendar anomalies, reasons for weakening the efficient market hypothesis. Accounting and Social Interests, 2(4), 23–37. (In Persian)

BahadoriFar, S., & Majidi, M. J. (2015). Car selection prioritization using ELECTRE technique. National Congress of Pivotal Issues in Management. (In Persian)

Baron, A. R., Bennour, E., & Harris, N. P. (1990). Proposed Usaid/Yemen Population Strategy Statement.

Bianchi, F., Mercuri, L., & Rroji, E. (2022). Portfolio Selection with Irregular Time Grids: an example using an ICA-COGARCH (1, 1) approach. Financial Markets and Portfolio Management, 36, 57–85.

Bildik, R. (2004). Are Calendar Anomalies Still Alive?: Evidence from Istanbul Stock Exchange. SSRN Electronic Journal.

Boyle, D., & Kalita, J. (2023). Spatiotemporal Transformer for Stock Movement Prediction.  SSRN Electronic Journal.

Bräker, J., Osterbrink, A., Semmann, M., & Wiesche, M. (2023). User-Centered Requirements for Augmented Reality as a Cognitive Assistant for Safety-Critical Services. Business & Information Systems Engineering, 65(2), 161–178.

Chang, R. P., McLeavey, D. W., & Rhee, S. G. (1995). Short term abnormal returns of the contrarian strategy in the Japanese stock market. Journal of Business Finance & Accounting, 22(7), 1035–1048.

Chhabra, D., & Gupta, M. (2022). Calendar anomalies in commodity markets for natural resources: Evidence from India. Resources Policy, 79, 103019.

Cross, F. (1973). The Behavior of Stock Prices on Fridays and Mondays. Financial Analysts Journal, 29(6), 67–69.

Di Gaspero, L., Di Tollo, G., Roli, A., & Schaerf, A. (2007). Hybrid Local Search for Constrained Financial Portfolio Selection Problems.4510, 44–58.

Emsakpur, H., Kheradyar, S., Homayonfar, M., & Eshkiki, M. (2021). The role of quarterly earnings announcements on the relationship between traders’ trading speed and cumulative abnormal stock returns. Financial Knowledge of Securities Analysis, 13(48), 1–14. (In Persian)

Fama, E. F. (1965). The Behavior of Stock-Market Prices. The Journal of Business, 38(1), 34–105.

Fama, E. F., & French, K. R. (2004). The Capital Asset Pricing Model: Theory and Evidence. Journal of Economic Perspectives, 18(3), 25–46.

Fields, M. J. (1934). Security Prices and Stock Exchange Holidays in Relation to Short Selling. The Journal of Business, 7, 328.

Gayaker, S., Yalcin, Y., & Berument, M. H. (2020). The day of the week effect and interest rates. Borsa Istanbul Review, 20(1), 55–63.

Golder, S. A., & Macy, M. W. (2011). Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures. Science, 333(6051), 1878–1881.

Gultekin, M. N., & Gultekin, N. B. (1983). Stock market seasonality: International Evidence. Journal of Financial Economics, 12(4), 469–481.

Hashemi, S. A., Kiani, G. H., & Rouhollahi, V. (2014). Investigating Behavioral and Rational Expectations Views in Describing the Accruals Anomaly. Financial Accounting Research, 6(4), 37–54. (In Persian)

Hayes, A. F., & Preacher, K. J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67, 451–470.

Hsu, Y.-T., Koedijk, K. G., Liu, H.-C., & Wang, J.-N. (2022). Further evidence on calendar anomalies. European Financial Management, 28,(2) 545–566.

Irtiza, M. S., Khan, S., Baig, N., Tirmizi, S. M. A., & Ahmad, I. (2021). The turn-of-the-month effect in Pakistani stock market. Future Business Journal, 7(43).

Jami, M., & Iraninejad, J. (2019). Examining the relationship between the calendar events of the weekdays and the stock returns of the companies admitted to the Tehran Stock Exchange. New Applied Studies in Management, Economics & Accounting. (In Persian)

Kamstra, M. J., Kramer, L. A., Levi, M. D., & Wermers, R. (2017). Seasonal Asset Allocation: Evidence from Mutual Fund Flows. Journal of Financial and Quantitative Analysis, 52(1), 71–109.

Kohli, Raj K., & Kohers, T. (1992). The week-of-the-month effect in stock returns: The evidence from the S&P Composite Index. Journal of Economics and Finance, 16, 129–137.

Kudryavtsev, A. (2019). Holiday Effect on Large Stock Price Changes. Annals of Economics and Finance, 20, 633–660.

Kunkel, R. A., Compton, W. S., & Beyer, S. (2003). The turn-of-the-month effect still lives: the international evidence. International Review of Financial Analysis, 12(2), 207–221.

Lakonishok, J., & Smidt, S. (1988). Are Seasonal Anomalies Real? A Ninety-Year Perspective. Review of Financial Studies, 1(4), 403–425.

Liu, L. (2013). The Turn-Of-The-Month Effect In The S&P 500 (2001-2011). Journal of Business & Economics Research (JBER), 11, 269.    

Lo, A. W. (2016). What Is an Index? The Journal of Portfolio Management, 42(2), 21–36.

Madureira, L. L., & Leal, R. P. C. (2001). Elusive anomalies in the Brazilian stock market. International Review of Financial Analysis, 10(2), 123–134.

Olson, D., Mossman, C., & Chou, N. T. (2015). The evolution of the weekend effect in US markets. The Quarterly Review of Economics and Finance, 58, 56–63.

Plastun, A., Sibande, X., Gupta, R., & G, R. (2019). Rise and fall of calendar anomalies over a century. North American Journal of Economics and Finance, 49(2), 181–205.

Qiao, K., & Dam, L. (2020). The overnight return puzzle and the “T+1” trading rule in Chinese stock markets. Journal of Financial Markets, 50, 100534.

Raee, R., & Shirzadi, S. (2008). Calendar and non- calendar Anomalies in Financial Markets. Journal of Securities Exchange, 1(1), 101. (In Persian)

Reinganum, M. R. (1983). The anomalous stock market behavior of small firms in January. Journal of Financial Economics, 12(1), 89–104.

Rozeff, M. S., & Kinney, W. R. (1976). Capital market seasonality: The case of stock returns. Journal of Financial Economics, 3(4), 379–402.

Semi-Annual Survey of the Iranian Economy. (2022). Economic Research Department, Middle East Bank.

Shariat Panahi, S. M. (2003). Assessment of Companies' Performance and Mechanism of Controlling the Managers' behavior: Representation Theory. Empirical Studies in Financial Accounting, 1(1), 85–108. (In Persian)

Sinaei, H. A., & Mohammadi, P. (2017). Testing Weak-Form Efficient Capital Market Case Study: TSE and DJUS Indices. Quarterly Journal of Quantitative Economics, 14(2), 167–192. (In Persian)

Tehrani, R., & Bayginia, H. (2012). The religious months effect on the stock market return, volatility and volume in the stock exchange of Tehran. Journal of Investment Knowledge, 1, 1–26. (In Persian)

Ţilică, E. V., & Oprea, D. (2014). Seasonality in the Romanian Stock Market: The-day-of-the-Week Effect. Procedia Economics and Finance, 15, 704–710. .

Vahabi, S., & Dehkordi, B. B. (2023). Applying the ELECTRE Method to Determine the Effects of Calendar Anomalies on the Index Returns of Banks Listed on the Tehran Stock Exchange. Advances in Mathematical Finance and Applications.13(51), 24-39.  (In Persian)

Walters, A. A. (1970). Statistical Inference. In An Introduction to Econometrics. Palgrave Macmillan UK. 32–78.

Weigerding, M., & Hanke, M. (2018). Drivers of seasonal return patterns in German stocks. Business Research, 11, 173–196.

Zhang, J., Lai, Y., & Lin, J. (2017). The day-of-the-Week effects of stock markets in different countries. Finance Research Letters, 20, 47–62.