eigenvector

The purpose of this study is to predict stock returns and ultimately present a trading strategy based on dynamic analysis.

The behavior of a stock portfolio can be considered as a complex and chaotic dynamic system in which the return of the portfolio is a state variable that reflects the state of the system. Dynamic mode decomposition is one of the methods in which with the help of available data, a linear approximation of the nonlinear operator governing the system is obtained and by calculating the main modes, the system output can be explicitly calculated in terms of time.

The results of research on a portfolio consisting of 14 industries from the Tehran Stock Exchange in the period 1390 to 1399 and considering the 5 main modes of system guidance show that the optimal lag is six and the Sharp ratio obtained from the trading system of two Equivalent to the buy and hold system.

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Therefore, the use of this trading system is recommended for short-term trading.

This paper extends a kind of evaluation process based on fuzzy TOPS IS approach. By focusing on determining the importance and weights of criteria which are effective on decision making, then selecting by lean on Anthropy and eigenvector methods in which comparison between criteria are linguistic and by achieving the weights we try to show the importance for criteria. The application and the mix of several methods in this paper are used to choose the best tickicide and to rank the available alternatives.