Under the growth of the stock market sector and the widespread of stock market applications, the stock market prediction has become one of the most important and challenging tasks in the stock market. Many data mining techniques are exploited to predict the stock prices in order to help investors in making investing decisions. One of the most common and widely used techniques is Artificial Neur...

Modeling and forecasting volatility of capital markets has been important area of inquiry and research in financial economics with the recognition of time-varying volatility, volatility clusturing, and asymmetric response of volatility to market movements. Given the anticipated growth of the Nepalese stock market and increasing interest of investors towards investment in Nepalese stock market, ...

Correspondence: [email protected] School of Computer Science, University of Birmingham, Edgbaston, B15 2TT Birmingham, United Kingdom Full list of author information is available at the end of the article Abstract Predicting investors reactions to financial and political news is important for the early detection of stock market jitters. Evidence from several recent studies suggests that o...

This paper studies the link between population age structure, net outflows (dividends plus repurchases less net issues) from the stock market, and stock market returns in an overlapping generations framework. I find support for the traditional lifecycle models — the outflows from the stock market are positively correlated with the changes in the fraction of old people (65 and over) and negative...

This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market ...

Objective: There is a large theoretical literature regarding stock market manipulation. However, empirical evidence of manipulation remains scare especially in emerging markets like Iran. So, it is vital to detect and prevent. Manipulation distorts prices, thereby reducing market efficiency and harms public confidence. Distorted prices increase market volatility and risk. This study empirically...

The focal objective of this study is to analyze and explore the Co-movement of Pakistan stock market (KSE-100) with the stock market of developed countries (US, UK, Canada, Australia, Germany, Japan, France and Neither land) which have portfolio investment in Pakistan by applying co-integration approach using Johansen and Juselius multivariate and bi variate co-integration. Secondary data of st...

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...

We consider a model of optimal investment and consumption with both habit-formation and partial observations in incomplete Itô processes markets. The individual investor develops addictive consumption habits gradually while he can only observe the market stock prices but not the instantaneous rates of return, which follow Ornstein-Uhlenbeck processes. Applying the Kalman-Bucy filtering theorem ...