Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is ...

One of the features of a financial market, the stock market, in particular, is the market sentiment which is the overall attitude of investors toward a particular security or financial market. Investors always seek to create a portfolio with minimum risk while maintaining the expected return level. Therefore, perceiving the relationship between the stock returns and markets returns can be helpf...

The paper presents computer system, named Stock Market Electronic Expert (SMEE), for Stock Market Analysis. It is developed as friendly, useful and credible computer program giving advises concerning investment policy on Stock Market. Fundamental and technical analysis are made automatically, and – on the base of obtained partial results – system produces evaluation of companies’ attractiveness...

Financial time series analyses have played an important role in developing some of the fundamental economic theories. However, many of the published analyses of financial time series focus on long-term average behavior of a market, and thus shed little light on the temporal evolution of a market, which from time to time may be interrupted by stock crashes and financial crises. Consequently, in ...

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...