The Impact of Using Dimensionality Trading Strategies on Forecasting the Daily Stock Returns of the Panel Data Method.

Subject Areas : Financial engineering

Ehteram Rahdarpoor ¹ , heshmatolah asgari ²

1 - Phd student of economics, Faculty of economics, management and administrative sciences, semnan university, semnan, iran
2 - Department of economics, Faculty of Literature and Human Science, ilam university, ilam, iran.

Received: 2019-08-30 Accepted : 2019-11-04 Published : 2019-12-22

Keywords: Combined Data, Forex Trading Decrease Trading Strategy, Forecasting Stock Market Daily Returns, Trading Volume Decreasing Strategy,

Abstract :

Earnings forecasting systems provide timely decisions by providing timely information. Earnings forecasting by management is widely used in assessing profitability, profit-related risk, stock price judgments, and valuation models (Manfred & Inky, 2014). Our purpose in this study is to investigate and investigate the impact of dimensionality trading strategies on predicting daily stock market returns by the fuzzy logic approach of firms. This study is a library-analytic-causal study based on panel data analysis (panel data). In this study, the financial information of 19 companies listed in Tehran Stock Exchange during the period 2011-2018 was reviewed. The results showed that using stock trading strategy and stock price reduction strategy have significant effect on prediction of daily stock market returns, but trading volume reduction strategy has no significant effect on market forecasting. I hope to accept my article. I suggest the editor remove this restriction on the number of words used in the abstract for the English text.

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