This paper investigates the relative pricing performance between constant volatility and stochastic volatility pricing models, based on a comprehensive sample of options on four currencies, including the British pound, Deutsche mark, Japanese yen and Swiss franc, traded frequently in the Philadelphia Stock Exchange (PHLX) from 1994 to 2001. The results show that the model of Heston (1993) outpe...

Around the world, trading in the stock market has gained huge attractiveness as a means through which, one can obtain vast profits. Attempting to profitably and precisely predict the financial market has long engrossed the interests and attention of bankers, economists and scientists alike. Stock market prediction is the act of trying, to determine the future value of a company’s stock or other...

In this paper, we have proposed artificial neural network for the prediction of Saudi stock market. The proposed predictions model, with its high degree of accuracy, could be used as investment advisor for the investors and traders in the Saudi stock market. The proposed model is based mainly on Saudi Stock market historical data covering a large span of time. Achieving reasonable accuracy rate...

One of the most prominent features of the U.S. stock market is the close connection between aggregate stock market volatility and the development of the business cycle. Figure 1 depicts the statistical relation between stock market volatility and the industrial production growth rate over the last sixty years, which shows that stock volatility is largely countercyclical, being larger in bad tim...

The cross-correlations between price fluctuations of 201 frequently traded stocks in the National Stock Exchange (NSE) of India are analyzed in this paper. We use daily closing prices for the period 1996-2006, which coincides with the period of rapid transformation of the market following liberalization. The eigenvalue distribution of the cross-correlation matrix, C, of NSE is found to be simil...

there are two major methods in predincing the pattern of share value in the stock market: fundamental analysis and technical analysis. i this study we developed a novel model for fundamental analysis of share price and validated it by predicting the behavior of phrama share price in tehran stock market. the efficiency of the fundamental method was compared with that of indicator-based technical...

Billions of dollars worth of shares are traded in the stock market on a daily basis. Many people depend on the stock market as their primary source of income while others have their retirement funds tied to the stock market. The importance of “good” performance of the stock market is obvious. History has shown that a downturn in stock prices can cause major disturbances in the lives of many. Al...

This paper surveys recent literature in the domain of machine learning techniques and artificial intelligence used to predict stock market movements. Artificial Neural Networks (ANNs) are identified to be the dominant machine learning technique in stock market prediction area. Keywords— Artificial Neural Networks (ANNs); Stock Market; Prediction

With trend of globalization in the international financial market, a more intimate relationship of capital flows is being formed day by day in capital market. Thus, it is important to understand the relationship of individual country with others in the international stock markets. The main purpose of this study is to explore the relationship of Stock Indices among China, US, and Japan. The stud...