The formation of the investment optimal portfolio based on the approach of the analysis of Social channels in Iran’s equities market (Quantitative and qualitative attitude)

Subject Areas : Financial Knowledge of Securities Analysis

mahshid esfahanian ¹ ( Ph.D. student Department of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran )
hamidreza vakilifard ² ( Associate Professor Department of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran. (Corresponding author) )
Shadi Shahverdiani ³ ( Assistant Professor Department of Business Administration. Shahr -e- Quds Branch, Islamic Azad university, Tehran, Iran, and Department of Management and Economics, Islamic Azad University , Science and Research Branch, Tehran, Iran. )
Mohammad Hassan Janani ⁴ ( Assistant Professor Department of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran )

Received: 2022-10-17 Accepted : 2023-01-01 Published : 2023-05-22

Keywords: Social network, Equities portfolio, optimal, investment,

Abstract :

This research point is to check the approach of analyzing social networks to form the investment optimal portfolio in Iran’s equities market. This research based on surveying-exploratory of the gathered sectional data. This research has been done in three phases, which includes studying theoretical basics and the literature review, exploratory research, Delphi method and using a questionnaire through a process that was completed in 20 levels. In qualitative part and in respect to Delphi 15 experts in the first phase and 25 experts in the second phase interviewed. For quantitative approach, 384 persons considered as the total sample of persons to be taken into account for Cochran formula and sampling method. The results showed that, assuming all the other conditions are constant; the investors were not affected by the political news in social networks, but were affected by the economical and corporate news.

References:

تقی زاده، مهران،1394،فراتحلیلی پیرامون نقش ریسک سازمانی در سازمان های قرن بیست و یکم،اولین همایش بین المللی علوم مدیریت پیشرفت ها، نوآوری ها و چالش ها. https://civilica.com/doc/560642

دهقان نیری، محمود و دوسری، فریبا،1396،انتخاب پرتفوی بهینه با رویکرد مدلسازی ریاضی چندهدفه احتمالی (مورد مطالعه: بورس اوراق بهادار تهران)،دومین کنفرانس بین المللی مدیریتصنعتی،بابلسر. https://civilica.com/doc/633369

راعی, رضا, حسینی, سید فرهنگ, کیانی هرچگانی, مائده. (1395). بررسی توانایی نظرات کاربران شبکه های اجتماعی بر پیش بینی جهت و قیمت سهام در بورس اوراق بهادار تهران. دانش سرمایه‌گذاری, 5(19), 107-128.

تقی زاده, کامران, صالحی, اله کرم, ملاعلیزاده زواردهی, صابر, & محمودی راد, علی. (1400). ارزیابی سبد پرتفوی بهینه با کاربرد معیارهای حسابداری با استفاده از معیارهای تصمیم گیری چند معیاره تحت شرایط عدم قطعیت در بازار سرمایه ایران. دانش مالی تحلیل اوراق بهادار14(51), 133-156. Doi: 10.30495/jfksa.2021.19256.

Auer, B. R., & Schuhmacher, F. (2016). Do socially (ir) responsible investments pay? New evidence from international ESG data, The Quarterly Review of Economics and Finance, 59(2016), 51–62.

Alimi.A, Zandieh.M, Amiri.M (٢٠١٢) Multy-objective portfolio of mutual funds under downside risk measure using fuzzy theory, journal of industrial engineering computations, (pp ٨٥٩-٨٧٢) 

Alvarez, S., Larkin, S. L., & Ropicki, A. (2017). Optimizing provision of ecosystem services using modern portfolio theory. Ecosystem Services, 27(Part A), 25–37.

Baker, H. K., &Nofsinger, J. R. (Eds.). (2010). Behavioral finance: investors, corporations, and markets (Vol. 6). John Wiley & Sons.

Bollen, J., Mao, H., &Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8. 

Bruni, R., Cesarone, F., Scozzari, A., & Tardella, F. (2016). Real-world datasets for portfolio selection and solutions of some stochastic dominance portfolio models. Data in Brief, 8, 858–862.

Geva, T., &Zahavi, J. (2014). Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news. Decision Support Systems, 57, 212-223.

Hirshleifer, D., & Hong Teoh, S. (2003). Herd behavior and cascading in capital markets: A review and synthesis. European Financial Management, 9(1), 25-66.

Kocadag˘lı.  Ozan, Keskin.  Rıdvan, (٢٠١٥) A novel portfolio selection model based on fuzzy goal programming with different importance and priorities, Expert Systems with Applications٤٢ (pp ٦٨٩٨-٦٩١٢) 

Li, Q., Wang, T., Li, P., Liu, L., Gong, Q., & Chen, Y. (2014). The effect of news and public mood on stock movements. Information Sciences, 278, 826-840. (b)

Li, X., Xie, H., Chen, L., Wang, J., & Deng, X. (2014). News impact on stock price return via sentiment analysis. Knowledge-Based Systems. 

Liagkouras, K., Metaxiotis, K. & Tsihrintzis, G. Incorporating environmental and social considerations into the portfolio optimization process. Ann Oper Res (2020). https://doi.org/10.1007/s10479-020-03554-3

Moradi, Mohammad, Sadollah, Ali, Eskandar, Hoda and Eskandar, Hadi. (2017). The application of water cycle algorithm to portfolio selection. Economic Research, 30(1): 1277–1299.

Nagar, A., &Hahsler, M. (2012). Using Text and Data Mining Techniques to extract Stock Market Sentiment from Live News Streams. International Proceedings of Computer Science & Information Technology, 47.

Oliveira, N., Cortez, P., & Areal, N. (2013). On the Predictability of Stock Market Behavior Using StockTwits Sentiment and Posting Volume. In Progress in Artificial Intelligence (pp. 355-365). Springer Berlin Heidelberg.

Ramelona, E., Kleiman, P., Gruenstein, D.,1997, Market returns and mutual fund   flows, FRBNY Economic Policy Review , 33–52, Federal Reserve Bank of New York

Shepard, J. M. (2012). Cengage Advantage Books: Sociology. Cengage Learning.

Wu, Kai and Lai, Seiwai and Sun, He, It Pays to Have Guanxi: Social Networks and Household Income in China (February 24, 2021). Available at SSRN: https://ssrn.com/abstract=3649302 or http://dx.doi.org/10.2139/ssrn.3649302

 Xiangtong. Meng, W. Zhang, Y. Li, et al., Social media effect, investor recognition and the cross-section of stock returns, International Review of Financial nalysis(2019), https://doi.org/10.1016/j.irfa.2019.101432

Zhou, R., Yang, Z., Yu, M., Ralescu, D. A., A (2015), portfolio optimization model based on information entropy and fuzzy time series. Fuzzy Optimization and Decision Making, 14(4), 381-397. 2015.

10. Liu and Q. Ma (2020), "Portfolio-Based Ranking of Traders for Social Trading," in IEEE Access, vol. 8, pp. 145363-145371, 2020, doi: 10.1109/ACCESS.2020.3011713.

Zimao. Liu and Q. Ma (2019), "Unsupervised method for discovering expert traders on social trading services", Proc. IEEE Int. Conf. Big Data Smart Compute. (Big Comp), pp. 1-8, Feb. 2019.

Yoshino, O., Taghizadeh-Hesary, F. Otsuka, M. (2021). Covid-19 and Optimal Portfolio Selection for Investment in Sustainable Development Goals. Finance Research Letters. 38, 1025-42.

Becker, K; Lee, JW (2019). Organizational Usage of Social Media for Corporate Reputation Management. Journal of Asian Finance Economics and Business, Vol.6 No.1, pp. 231-240. DOI: http://doi.org/10.13106/jafeb.2019.

Fallahgoul, H. (2021). Inside the Mind of Investors during the COVID-19 Pandemic: Evidence from the Stock Twits Data. The Journal of Financial Data Science Spring 2021, 3 (2) 134-148; DOI: https://doi.org/10.3905/jfds.2021.1.058.

Chahine, S. and Malhotra, N.K. (2018), "Impact of social media strategies on stock price: the case of Twitter", European Journal of Marketing, Vol. 52 No. 7/8, pp. 1526-1549. https://doi.org/10.1108/EJM-10-2017-0718.

Koumou, G.B. Diversification and portfolio theory: a review. Finance Mark Portf Manag 34, 267–312 (2020). https://doi.org/10.1007/s11408-020-00352-6.