Market Timing by Considering the Investor Sentiment Index in Tehran Stock Exchange

Market timing Investment decisions are made with a mechanical trading strategy based on certain macroeconomic criteria. In this study, investor sentiment index and macroeconomic indicators such as inflation, exchange rate, employment growth and real GDP of representative variables were used to market timing to predict the direction and return of the total index of Tehran Stock Exchange. In this regard, four models of logistic regression, Lasso, Ridge and Elastic Net were used using monthly data in the period 1395 to 1399. In order to develop the sentiment index, using the exploratory factor analysis model, six different emotional variables were used, and finally, three variables of stock ratio in the portfolio of investment funds, Tehran price index and top 50 index were selected. The output of the logistic regression model for forecasting based on a single index was compared with the value of forecasting based on other indicators, which showed that logistics forecasting based on all variables was superior to logistic forecasting based on a single index. Comparison of Lasso, Ridge and Elasticnet models for prediction showed that the strength and accuracy of Ridge regression model was more than the other two models, in addition, Lasso and Elasticnet models were almost equally accurate. The results of this research can be useful for investment companies and portfolio managers, analysts and investors.