The goal of this research is to predict total stock market index of Tehran Stock Exchange, using the compound method of ARIMA and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. First, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

A firm is called to have stock price crash risk if the firm has a tendency to experience a sudden drop in its stock price. In this study, the relation between the firm-level of business strategy and future stock price crash risk Is examined, as well as the effect of stock overvaluation on the relationship between business strategy and crash risk investigated. Using the strategy index and crash ...

Stock market prediction is essential and of great interest because successful prediction of stock prices may promise smart benefits. These tasks are highly complicated and very difficult. Many researchers have made valiant attempts in data mining to devise an efficient system for stock market movement analysis. In this paper, we have developed an efficient approach to stock market prediction by...

We propose and test a simple hedging hypothesis for prediction interval formation in stock price forecasting. In the presence of uncertainty, forecasters hedge their forecasts by adjusting bounds way that reflects forecast average others. This suggests positive relationship between belief wedge, defined as difference subject's others own point forecast, asymmetry interval. Empirical support is ...

This paper examines the predictability of a range of international stock markets where we allow the presence of both local and global predictive factors. Recent research has argued that US returns have predictive power for international stock returns. We expand this line of research, following work on market integration, to include a more general definition of the global factor, based on princi...