مدلسازی تمایلات سرمایه گذاران با تأکید بر عوامل روانشناختی با استفاده روش دلفی فازی و دیمتل

محورهای موضوعی : اقتصاد سنجی مالی و روش‌های کمّی

محسن فرهادی ¹ , میثم دعائی ²

1 - گروه مدیریت، دانشکده اقتصاد و مدیریت، واحد علوم تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران
2 - گروه مدیریت مالی، واحد اسفراین، دانشگاه آزاد اسلامی، اسفراین، ایران

تاریخ دریافت : 1400/06/08 تاریخ پذیرش : 1400/12/20 تاریخ انتشار : 1400/12/01

کلید واژه: دیمتل, دلفی فازی, عوامل روانشناختی, مدل تمایلات سرمایه گذاران,

چکیده مقاله :

نتایج پژوهش‌های انجام شده در حوزه تأمین مالی بر اساس رویکرد رفتاری، حاکی از آن است که ممکن است سرمایه گذاران، غیر منطقی باشند؛ در نتیجه، سوگیری شناختی یا عوامل روانی سرمایه گذاران، می تواند بر روی تصمیمات آنان، تأثیرگذار باشد. بنابراین، نوسان قیمت سهام، نه تنها به ارزش ذاتی نشان داده شده توسط اطلاعات حسابداری وابسته است، بلکه بر رفتار غیر منطقی سرمایه گذاران نیز متکی می باشد، که می تواند با تمایلات سرمایه گذار، سنجیده شود. از این رو با توجه به اهمیت این حوزه پژوهش حاضر به ارائه مدل تمایلات سرمایه‌گذاران با تأکید بر عوامل روانشناختی با روش دلفی فازی و دیمتل می‌پردازد. این پژوهش از نوع پژوهش‌های داده بنیاد می‌باشد. همچنین این پژوهش از نوع پژوهش‌های آمیخته می‌باشد که در آن از دو رویکرد مورد استفاده در علوم رفتاری یعنی کمی (دیمتل) و کیفی (دلفی فازی) استفاده می‌شود. بر اساس نتایج به دست آمده می‌توان بیان نمود که تعلق خاطر، ابهام گریزی، خود استنادی، اطمینان بیش از حد، محافظه کاری، حسابداری ذهنی، توهم کنترل، پشیمان گریزی، بهینه بینی، داشته بیش نگری، بدبینی، رفتار گله‌ای، کوتاه نگری و واکنش افراطی از جمله عوامل تاثیرگذار تمایلات سرمایه گذاران با تأکید بر عوامل روانشناختی می‌باشند که به عنوان مدل نهایی تمایلات روانشناختی سرمایه گذاران در بورس اوراق بهادار شناخته شده‌اند.

چکیده انگلیسی:

The results of research in the field of financing based on a behavioral approach suggest that investors may be irrational; As a result, investors' cognitive bias or psychological factors can influence their decisions. Thus, stock price volatility depends not only on the intrinsic value shown by accounting information, but also on the irrational behavior of investors, which can be measured by the investor's inclinations. Therefore, considering the importance of this field, the present study presents a model of investors' tendencies with emphasis on psychological factors with fuzzy Delphi and DEMATEL methods. This research is a data foundation research. Also, this research is a type of mixed research in which two approaches used in behavioral sciences, namely quantitative and qualitative, are used. The statistical population of this research is divided into two parts. The first part of the statistical population consists of financial and investment experts, which includes experts in this field, who are consulted to determine the dimensions, components and indicators, and the second part of the statistical population includes all university professors who have a doctorate in finance. And are investments. Using fuzzy Delphi method, the optimal criteria of investors 'tendencies with emphasis on psychological factors were extracted and the final model of the levels of optimal factors of investors' tendencies with emphasis on psychological factors was also drawn. Also, the effect and influence of factors on each other were evaluated using DEMATEL method.

منابع و مأخذ:

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Baker, M., & Wurgler, J. (2007). Investor Sentiment in the Stock Market. Journal of Economic Perspectives, 21(2), 129–151.

Baker, M., Wurgler, J., & Yuan, Y. (2012). Global, local, and contagious investor sentiment. Journal of Financial Economics, 104(2), 272–287.

‌Ball, R., & Brown, P. (1968). An Empirical Evaluation of Accounting Income Numbers. Journal of Accounting Research, 6(2), 159–178.

Barth, M. E., Konchitchki, Y., & Landsman, W. R. (2013). Cost of capital and earnings transparency. Journal of Accounting and Economics, 55(2-3), 206–224.

Batabyal, S., & Killins, R. (2021). Economic policy uncertainty and stock market returns: Evidence from Canada. The Journal of Economic Asymmetries, 24, e00215.

Bathia, D., & Bredin, D. (2018). Investor sentiment: Does it augment the performance of asset pricing models? International Review of Financial Analysis, 59, 290–303.

Brown, G. W., & Cliff, M. T. (2005). Investor Sentiment and Asset Valuation. The Journal of Business, 78(2), 405–440.

Cagli, E. C., Can Ergün, Z., & Durukan, M. B. (2020). The causal linkages between investor sentiment and excess returns on Borsa Istanbul. Borsa Istanbul Review, 20(3), 214–223.

Chiu, J., Chung, H., Ho, K.-Y., & Wu, C.-C. (2018). Investor sentiment and evaporating liquidity during the financial crisis. International Review of Economics & Finance, 55, 21–36.

Cornell, B., Landsman, W. R., & Stubben, S. R. (2017). Accounting Information, Investor Sentiment, and Market Pricing. Journal of Law, Finance, and Accounting, 2(2), 325–345.

Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory into Practice, 39(3), 124–130.

Dhar, R., & Zhu, N. (2006). Up Close and Personal: Investor Sophistication and the Disposition Effect. Management Science, 52(5), 726–740.

Fang, Y., Yuan, J., Yang, J. J., & Ying, S. (2022). Crash-based quantitative trading strategies: Perspective of behavioral finance. Finance Research Letters, 45, 102185.

Feng, L., & Seasholes, M. S. (2005). Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets? Review of Finance, 9(3), 305–351.

Frino, A., Lepone, G., & Wright, D. (2015). Investor characteristics and the disposition effect. Pacific-Basin Finance Journal, 31, 1–12.

Igual, M. G., & Santamaría, T. C. (2017). Overconfidence, loss aversion and irrational investor behavior: a conceptual map. Journal of Economic & Management Perspectives, 11(1), 273-290.‏

Janvrin, D. J., & Wang, T. (2019). Implications of Cybersecurity on Accounting Information. Journal of Information Systems, 33(3), A1–A2.

Jonsson, S., Söderberg, I.-L., & Wilhelmsson, M. (2017). An investigation of the impact of financial literacy, risk attitude, and saving motives on the attenuation of mutual fund investors’ disposition bias. Managerial Finance, 43(3), 282–298.

Lan, Y., Huang, Y., & Yan, C. (2021). Investor sentiment and stock price: Empirical evidence from Chinese SEOs. Economic Modelling, 94, 703–714.

Lee, C.-F., & Rahman, S. (1990). Market Timing, Selectivity, and Mutual Fund Performance: An Empirical Investigation. The Journal of Business, 63(2), 261.

Ni, Z.-X., Wang, D.-Z., & Xue, W.-J. (2015). Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model. Economic Modelling, 50, 266–274.

Pástor, Ľ., & Stambaugh, Robert F. (2003). Liquidity Risk and Expected Stock Returns. Journal of Political Economy, 111(3), 642–685.

Rahman, M. L., & Shamsuddin, A. (2019). Investor sentiment and the price-earnings ratio in the G7 stock markets. Pacific-Basin Finance Journal, 55, 46–62

Sajjadi, S F, (2021), Behavioral biases and financial decisions A review of studies conducted, 4th International Conference on Science and Technology of the Third Millennium of Iranian Economy, Management and Accounting, Tehran, [In Persian].

Schmeling, M. (2009). Investor sentiment and stock returns: Some international evidence. Journal of Empirical Finance, 16(3), 394–408.

Shefrin, H. (2008).A behavioral approach to asset pricing. Academic Press/Elsevier.

Stambaugh, R. F., Yu, J., & Yuan, Y. (2012). The short of it: Investor sentiment and anomalies. Journal of Financial Economics, 104(2), 288–302.

Takamatsu, R. T., & Lopes Fávero, L. P. (2019). Financial indicators, informational environment of emerging markets and stock returns. RAUSP Management Journal, 54(3), 253–268.

Venezia, I., & Shapira, Z. (2007). On the behavioral differences between professional and amateur investors after the weekend. Journal of Banking & Finance, 31(5), 1417–1426.

Wang, W., & Duxbury, D. (2021). Institutional investor sentiment and the mean-variance relationship: Global evidence. Journal of Economic Behavior & Organization, 191, 415–441.

‌Zhu, B., & Niu, F. (2016). Investor sentiment, accounting information and stock price: Evidence from China. Pacific-Basin Finance Journal, 38, 125–134.

Zhuo, J., Li, X., & Yu, C. (2021). Parameter behavioral finance model of investor groups based on statistical approaches. The Quarterly Review of Economics and Finance, 80, 74–79.

Akhtar, S., Faff, R., Oliver, B., & Subrahmanyam, A. (2011). The power of bad: The negativity bias in Australian consumer sentiment announcements on stock returns. Journal of Banking & Finance, 35(5), 1239–1249.

Baker, M., & Wurgler, J. (2007). Investor Sentiment in the Stock Market. Journal of Economic Perspectives, 21(2), 129–151.

Baker, M., Wurgler, J., & Yuan, Y. (2012). Global, local, and contagious investor sentiment. Journal of Financial Economics, 104(2), 272–287.

‌Ball, R., & Brown, P. (1968). An Empirical Evaluation of Accounting Income Numbers. Journal of Accounting Research, 6(2), 159–178.

Barth, M. E., Konchitchki, Y., & Landsman, W. R. (2013). Cost of capital and earnings transparency. Journal of Accounting and Economics, 55(2-3), 206–224.

Batabyal, S., & Killins, R. (2021). Economic policy uncertainty and stock market returns: Evidence from Canada. The Journal of Economic Asymmetries, 24, e00215.

Bathia, D., & Bredin, D. (2018). Investor sentiment: Does it augment the performance of asset pricing models? International Review of Financial Analysis, 59, 290–303.

Brown, G. W., & Cliff, M. T. (2005). Investor Sentiment and Asset Valuation. The Journal of Business, 78(2), 405–440.

Cagli, E. C., Can Ergün, Z., & Durukan, M. B. (2020). The causal linkages between investor sentiment and excess returns on Borsa Istanbul. Borsa Istanbul Review, 20(3), 214–223.

Chiu, J., Chung, H., Ho, K.-Y., & Wu, C.-C. (2018). Investor sentiment and evaporating liquidity during the financial crisis. International Review of Economics & Finance, 55, 21–36.

Cornell, B., Landsman, W. R., & Stubben, S. R. (2017). Accounting Information, Investor Sentiment, and Market Pricing. Journal of Law, Finance, and Accounting, 2(2), 325–345.

Creswell, J. W., & Miller, D. L. (2000). Determining Validity in Qualitative Inquiry. Theory into Practice, 39(3), 124–130.

Dhar, R., & Zhu, N. (2006). Up Close and Personal: Investor Sophistication and the Disposition Effect. Management Science, 52(5), 726–740.

Fang, Y., Yuan, J., Yang, J. J., & Ying, S. (2022). Crash-based quantitative trading strategies: Perspective of behavioral finance. Finance Research Letters, 45, 102185.

Feng, L., & Seasholes, M. S. (2005). Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets? Review of Finance, 9(3), 305–351.

Frino, A., Lepone, G., & Wright, D. (2015). Investor characteristics and the disposition effect. Pacific-Basin Finance Journal, 31, 1–12.

Igual, M. G., & Santamaría, T. C. (2017). Overconfidence, loss aversion and irrational investor behavior: a conceptual map. Journal of Economic & Management Perspectives, 11(1), 273-290.‏

Janvrin, D. J., & Wang, T. (2019). Implications of Cybersecurity on Accounting Information. Journal of Information Systems, 33(3), A1–A2.

Jonsson, S., Söderberg, I.-L., & Wilhelmsson, M. (2017). An investigation of the impact of financial literacy, risk attitude, and saving motives on the attenuation of mutual fund investors’ disposition bias. Managerial Finance, 43(3), 282–298.

Lan, Y., Huang, Y., & Yan, C. (2021). Investor sentiment and stock price: Empirical evidence from Chinese SEOs. Economic Modelling, 94, 703–714.

Lee, C.-F., & Rahman, S. (1990). Market Timing, Selectivity, and Mutual Fund Performance: An Empirical Investigation. The Journal of Business, 63(2), 261.

Ni, Z.-X., Wang, D.-Z., & Xue, W.-J. (2015). Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model. Economic Modelling, 50, 266–274.

Pástor, Ľ., & Stambaugh, Robert F. (2003). Liquidity Risk and Expected Stock Returns. Journal of Political Economy, 111(3), 642–685.

Rahman, M. L., & Shamsuddin, A. (2019). Investor sentiment and the price-earnings ratio in the G7 stock markets. Pacific-Basin Finance Journal, 55, 46–62

Sajjadi, S F, (2021), Behavioral biases and financial decisions A review of studies conducted, 4th International Conference on Science and Technology of the Third Millennium of Iranian Economy, Management and Accounting, Tehran, [In Persian].

Schmeling, M. (2009). Investor sentiment and stock returns: Some international evidence. Journal of Empirical Finance, 16(3), 394–408.

Shefrin, H. (2008).A behavioral approach to asset pricing. Academic Press/Elsevier.

Stambaugh, R. F., Yu, J., & Yuan, Y. (2012). The short of it: Investor sentiment and anomalies. Journal of Financial Economics, 104(2), 288–302.

Takamatsu, R. T., & Lopes Fávero, L. P. (2019). Financial indicators, informational environment of emerging markets and stock returns. RAUSP Management Journal, 54(3), 253–268.

Venezia, I., & Shapira, Z. (2007). On the behavioral differences between professional and amateur investors after the weekend. Journal of Banking & Finance, 31(5), 1417–1426.

Wang, W., & Duxbury, D. (2021). Institutional investor sentiment and the mean-variance relationship: Global evidence. Journal of Economic Behavior & Organization, 191, 415–441.

‌Zhu, B., & Niu, F. (2016). Investor sentiment, accounting information and stock price: Evidence from China. Pacific-Basin Finance Journal, 38, 125–134.

Zhuo, J., Li, X., & Yu, C. (2021). Parameter behavioral finance model of investor groups based on statistical approaches. The Quarterly Review of Economics and Finance, 80, 74–79.