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...

This paper uses the smooth transition regression (STR) model to study the nonlinear relation between the consumer price index (CPI) and the composite index of Shanghai Stock Market in China from 1999 to 2011. The results show that there exists one way Granger causality relation from CPI to stock market in China; the internal relation between the CPI and stock market’s composite index appears as...

In the absence of market frictions, the cost of carry model of stock index futures pricing predicts that returns on the underlying stock index and the associated stock index futures contract will be perfectly contemporaneously correlated. Evidence suggests, however, that this prediction is violated with clear evidence that the stock index futures market leads the stock market. We argue that tra...