(searched for: Stock Price Forecasting Using A Dependence Structure)
Published: 1 January 2020
Ecology. Economy. Informatics.System analysis and mathematical modeling of ecological and economic systems, Volume 1; https://doi.org/10.23885/2500-395x-2020-1-5-40-44
At present, in contrast to lending and investment services, models for raising additional capital for a company by issuing shares and then placing them on the securities market are becoming more popular. This article discusses the model of issuing shares for a joint-stock company (JSC) and the subsequent purchase of their traders. The model has a two-level hierarchical structure, where the leading party is the JSC, and the lead, in turn, is the shareholders. The company determines the number of shares and their issue price. Depending on the total capitalization of the company and the nominal share price, the company’s revaluation coefficient (P/BV) is formed. This coefficient affects the General mood of shareholders in the market, who use the sale or purchase of shares to change the total capitalization of the company. The price for the current time period consists of the algebraic sum of the price for the previous time period and the total capitalization, thus, through changes in the total turnover of funds, shareholders are able to influence the share price. The main income for a shareholder is the difference between the purchase and sale of shares, as well as the payment of its dividends. For the company, the task is to maximize profits by buying shares on the stock exchange, as well as minimize losses when selling them. After describing the target functions and applying the simulation method, the optimal issue price for a fixed number of shares was found for the company. Unfortunately, the market does not lend itself to accurate forecasts due to the large influence of the human factor. Very often, shareholders can act against the rational and most profitable strategy. Despite this, this model will help to approximate the behavior of players in the stock market in subsequent development, thereby facilitating the study of price movements on the stock exchange.
Applied Network Science, Volume 2; https://doi.org/10.1007/s41109-017-0028-1
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Applied Financial Economics, Volume 17, pp 709-723; https://doi.org/10.1080/09603100600735310
A major issue in financial economics is the behaviour of stock market returns over long horizons. This article provides an empirical investigation of the long-range dependence in the emerging stock markets of Egypt, Jordan, Morocco and Turkey. We use the modified rescaled range statistic (R/S) proposed by Lo ( 1991 Lo, AW . 1991. Long-term memory in stock market prices. Econometrica, 59: 1279–313. [Crossref], [Web of Science ®] [Google Scholar] ) and the rescaled variance statistic (V/S) developed by Giraitis et al . ( 2003 Giraitis, L , Kokoszka, PS , Leipus, R and Teyssiere, G . 2003. Rescaled variance and related tests for long memory in volatility and levels. Journal of Econometrics, 112: 265–94. [Crossref], [Web of Science ®] [Google Scholar] ) to investigate the long memory in the returns and volatility. Significant long memory is demonstrated in the series and implies a fractal market structure in the Middle East and North African (MENA) equity markets. We further investigate whether the long memory is caused by a shift in variance. Interestingly, our findings indicate that the presence of long memory in volatility due to shifts in variance cannot be confirmed for these markets and are consistent with those results obtained by Lobato and Savin ( 1998 Lobato, IN and Savin, NE . 1998. Real and spurious long memory properties of stock-market data. Journal of Business and Economics Statistics, 16: 261–8. [Taylor & Francis Online], [Web of Science ®] [Google Scholar] ) on other markets. Thus, our results should be useful to regulators, practitioners and derivative market participants in the MENA region, whose success depends on the ability to forecast stock price movements over long horizons.