A number of research had been carried out to forecast stock price based on technical indicators, which rely purely on historical stock price data. Nevertheless, their performance is not always satisfactory. In this paper, the effect of using hybrid market indicators of technical, fundamental indicators and experts opinion for stock price prediction is examined. Input variables extracted from th...

Employing the dataset of WTI oil spot price and stock price index in China Brazil, India, US, German, France, UK and Japan, this paper obtains five subinterval of whole sample range through a nonparametric multiple change point algorithms. Furthermore, it analyses dependence between oil spot price and stock price index through copula model and computes the value of VaR and ES based on simulatio...

in this paper we investigate the effect of oil price shocks on stock market index in iran, by using of a structural var (svar) approach. we used four variables in the model namely kilian index, global oil supply, real oil price and real stock market index. the data are monthly and spanning the period 1997m10-2014m12. we identify the effect of four different shocks on stock market including oil ...

Motivated by the behavior of internet stock prices in 1998-2000, we present a continuous time equilibrium model of bubbles where overconfidence generates agreements to disagree among agents about asset fundamentals. With a short-sale constraint, an asset owner has an option to sell the asset to other agents when they have more optimistic beliefs. This re-sale option has a recursive structure, t...

Asset-price bubbles challenge the explanatory and predictive power of standard economic theory, suggesting that neuroeconomic measures should be explored as potential tools for improving the predictive power of standard theory. We begin this exploration by reviewing results from functional magnetic resonance imaging (fMRI) studies of lab asset-price bubbles and herding behavior (i.e., following...

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 r t i c l e i n f o JEL classification: C22 E44 G11 Keywords: Causality Rank test Threshold error-correction model (TECM) Wealth effect Credit price effect Using the non-parametric rank tests proposed by Breitung (2001), we set out in this study to determine whether any non-linear long-run equilibrium relationship exists between the stock and real estate markets of Western European countries....

Asset market experiments are analyzed by distinguishing, ex post facto, participants who trade on fundamentals versus those who trade on momentum (i.e., buying when price is rising). The distinction is made when prices are above fundamental value, so that (in each period) those who have more offers than bids (net offerers) are classified as fundamentalists while those who have more bids than of...