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...

This paper examines the hypothesis that both stock returns and volatility are asymmetrical functions of past information derived from domestic and US stock-market news. By employing a double-threshold regression GARCH model to investigate four major index-return series, we find significant evidence to sustain the asymmetrical hypothesis of stock returns. Specifically, evidence strongly supports...

The present study is being contemplated with the objective of studying the degree of stock market integration. In this study, month-wise average prices of BSE-Sensex, NYSE, NASDAQ, S&P500, HangSeng, Nikkei225, SSE Composite index and FTSE100 have been selected. Multiple Correlations has been computed for the select stock market indices. Statistical Significance of the correlation has been teste...

In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using neural network, TS fuzzy system and hierarchical TS fuzzy techniques. To demonstrate the different techniques, we considered Nasdaq−100 index of Nasdaq Stock Market and the S&P CNX NIFTY stock index. We analyzed 7 year’s Nasdaq 100 main index values and 4 year’s NIFTY index values. ...

OBJECTIVE This study aims to discuss the correlation between daily reported H7N9 cases and stock price indices in China. METHODS Information on daily reported H7N9 cases and stock market sectors indices between February 19, 2013 and March 31, 2014 were collected. A distributed lag non-linear model was used to describe the variation trend for the stock indices. RESULTS The daily reported num...

In order to forecast the stock market more accurately, according to the dynamic property for the stock market, propose the real time modeling forecast via dynamic recurrent neural network and use GA to study online, then it improves the network performance and better describes the dynamic characteristic of stock market. By forecasting Shanghai negotiable securities index, it shows better validi...