Pattern Explanation of Micro and Macro variables on Return of Stock Trading Strategies

Advances in Mathematical Finance and Applications

مقاله 11، دوره 7، شماره 4، دی 2022، صفحه 997-1011   

نوع مقاله: َApplied-Research Paper

شناسه دیجیتال (DOI): 10.22034/amfa.2021.1912667.1501

نویسندگان

atefeh yazdani varzi^{* 1}؛ Erfan memarian²؛ Seyed Ali Nabavi Chashmi³

¹Faculty of Humanities, Management, Islamic Azad University, Babol Branch, Iran

²Faculty of Humanities, Islamic Azad University, Babol, Iran

³Department of Financial Management Babol Branch, Islamic Azad University, Babol

چکیده

In the research, pattern explanation of micro and macro variables on return on stock trading strategies has been dealt with. Based on data collected, existence of momentum and contrarian strategies in Tehran Stock Exchange market has been studied. To collect data and make statistical analysis, Excel Spread Sheet software, and statistical SPSS and R software packages have been used. Through usage made of various statistical models, the relationship between variable of return on stock and other variables added has been studied so that based on which stock trading strategy would be predicted, for the next 12 months. To do so, three statistical models of autoregressive time series (with no auxiliary variable), linear regression, and Markov-switching have been applied. Using the model’s fit criteria, these three models have been compared and best of them has been selected. Based on selected model, stock trading strategy for the next 12 months has been predicted. Markov model showed that within next 12 months, using contrarian strategy i.e. selling previous winners and purchasing previous losers can be profitable. According to the research findings, from among micro variables (base volume, trade volume, institutional investment, and free float) and from among macro variables (currency and inflation rates), only three variables of the first (base volume, institutional investment, and free float) are effective on stock trading strategy; and, they can be used as auxiliary variables to predict return on stock and to specify stock trading strategy in future as a result.

کلیدواژه‌ها

Stock trading strategy؛ Micro factors؛ Macro factors

مراجع

[1] As’adi, A., and Imantalab, H., The relationship between flee float and return on stock, liquidity and value of companies, Financial Engineering and Stock Exchange Management Quarterly, 2018, (in Persian).

[2] Abbasinejad, H., Mohammadi, Sh., and Ebrahimi, S., Relationship dynamics of macro variables and stock market index, Asset Management and Financing for the Fifth Year Spring 2017, (in Persian).

[3] Chang, R., Ko K., Nakano, S., and Rhee S., Residual momentum in Japan, Journal of Empirical Finance, 2017, Doi:10.1016/j.jempfin.2017.11.005.

 

[4] Dehong, L., Yucong L., Lili, Z., and Peter, L., Rizwan Ullah, Implied volatility forecast and option trading strategy ,International Review of Economics and Finance, 2021, P. 943-954.

 

[5] Davoodi Kasbi, A., Dadashi, I., and Azinfar, K., Stock Price Prediction Using the Chaid Rule-Based
Algorithm and Particle Swarm Optimization (PSO), Advances in Mathematical Finance and Applications,
2020, 5(2), P.197-213. Doi: 10.22034/amfa.2019.585043.1184, (in Persian).

 

 [6] Ehsani, M., Izadi, R., and Kurdatbar, H, "Investigating the Effect of Stock Market Development on Economic Growth: A Case Study in Group D8 Countries. Quarterly Journal of Fiscal and Economic Policies, 2014, 6, P. 105-222, (in Persian).

 

[7] Fernandez, A., Frijns, B., and Tourani-Rad, A., When no news is good news – the decrease in investor fear after the FOMC announcement. Journal of Empirical Finance, 2017, 41, P. 187–199, (in Persian).

 

[8] Jalilian, J., and Taherkhani, N., the pair trading strategy in the Iranian stock market (Case study of stocks of stock exchange investment companies), Business Reviews August and September 2017, (in Persian).

 

[9] Hao,Y., Chou, K., Ko ,K., and Yang, N., “The 52-week high, momentum, and investor sentiment”. International Review of Financial Analysis Finance, 2018, Doi: 10.1016/j.irfa.2018.01.014.

 

[10] Hamido, F., Investor heterogeneity and momentum-based trading strategies in China, International Review of Financial AnalysisAvailable. 2020, (in Persian).

 

[11] LioGalvani, M., and Valentina, A., Market states, sentiment, and momentum in the corporate bond Market, Journal of Banking and Finance, 2018, 89, P. 249-265.

 

[12] Zanjirdar, M. Overview of Portfolio Optimization Models. Advances in Mathematical Finance and Applications, 2020; 5(4), P. 419-435. Doi: 10.22034/amfa.2020.674941

[13] Laem, A., Tom, M., the effect of stock trading volume on capital asset pricing, Journal of Applied Econometrics, 2010, P. 551-565.

 

[14] Munir Q., and Mansur K., Is Malaysian stock market efficient? Evidence from threshold unit root tests, Economics Bulletin, 2013, P. 167-174.

 

[15] Mousavi, S., Salehi, M., Mehdi, Shakeri, M., and Bakhshian, A., Profitability of momentum strategy and effect of stock trading volume on it in Tehran Stock Exchange, Financial Enginnering and Stock Exchange Management (portfolio management), 2015, P.107-123, (in Persian).

 

[16] MansooLakvarj, K., Taheri, E., and Yahyatabar, F., Studying the relationship between institutional investors and return on stock in companies listed in Tehran Stock Exchange, Journal of Quantitative Studies in Management, summer, 2011, P. 180-194.

 

[17] Malekian, E., Fakhari, H., Ghasemi, J., and Farzad, S., Predict the Stock Price of Crash Risk by Using Firefly Algorithm and Comparison with Regression, Advances in mathematical finance and applications, 2018, 3(2), P.43-58. Doi:10.22034/amfa.540830.

 

[18] Ne’mati, A., Hamed, T., and Naiempoor, R., Studying institutional ownership and stock price, trading volume, and return on stock of companies listed in Tehran Stock Exchange, Second International Conference on Accounting, Management, and Innovation in Business, Rasht, California Lutheran University, Municipality of Rasht. 2016.

 

[19] Nowruzi, H., and Khalili Iraqi, M., Acceleration Strategies and Emotional Tendencies of Investors in Real Estate Investment Companies Listed on the Stock Exchange, Financial Management Strategy,2017, 3(22), P. 167 - 188.

 

[20] Ogruk,G, Carry Trade Strategles With Factor Augmented Macro Fundamentals: A Dynamic Markov-Switching Factor Model, The International Journal of Business and Finance Research, 2016, P.11-28.

 

[21] Pasandideh, P., and Sarraf, F., Financial Statement Comparability and the Expected Crash Risk of Stock Prices, Advances in mathematical finance and applications, 2018, 3(3), P.77-93. Doi:10.22034/amfa.544951.

 

[22] Qing.Ye., Shengjie, Z., and Jie., Z, Short-selling, margin-trading, and stock liquidity: Evidence from the Chinese stock markets, International Review of Financial Analysis. 2020.

 

[23] Rahmani, A., Sarhangi, H., Analyzing factors effective on trading strategies based on return on stock, Financial Engineering and Stock Exchange Management Quarterly, 2011, P. 79-104.

[24] Samadi, S., and Bayani, O., Investigating the Relationship between Macroeconomic Variables and Stock Returns in Tehran Stock Exchange, Quarterly Journal of Economic Sciences, 2011, P.

 

[25] Sinaie, H., and Azhdarpoor, L., Scientific-research Financial Accounting Quarterly, 2014, P. 29-50

 

[26] Sharma, N., Causal relation between stock return and exchange rate: Evidence from India, Global Journal of Management and Business Research, 2016, 15(11), P. 26-32.

 

[27] Suk Bitak, P., and Hongvenia, A, The effect of trading volume on market efficiency, Research in International Business and Finance, 2016, 3, P. 41–51.

 

[28] Sernioasan, M., the effect of macroeconomic variables information on stock prices in South Korea, Intelligent systems in accounting, finance and management, 2015, 21(2), P. 209-223

 

[29] Yunita, I., Nurhakim, A., and Iradianty, A, The effect of profitability and inflation on stock return at pharmaceutical industry at BEI in the period of 2011-2014, First International Conference on Advanced Business and Social Sciences. 2016.

 

[30] Xing. W., Haolei, C., Jianjia, W., Luigi, T., and Vincenzo L., Adaptive stock trading strategies with deep reinforcement learning methods. Information Sciences, 2020, P.142-158.

 

[31] Vakilifard, H., Joula, J.,and  Babaie, H., Studying effect of base volume on amount of return on stock and liquidity of companies listed in Tehran Stock Exchange, Financial management strategy quarterly, 2014, P.59-73.