The stock market domain is a dynamic and unpredictable environment. Traditional techniques, such as fundamental and technical analysis can provide investors with some tools for managing their stocks and predicting their prices. However, these techniques cannot discover all the possible relations between stocks and thus there is a need for a different approach that will provide a deeper kind of ...

This study proposed a novel Nonlinear Auto Regressive eXogenous Neural Network (NARXNN) with Tracking Signal (TS) approach and seeks to investigate the various training functions to forecast the closing index of the stock market. A novel approach strives to adjust the number of hidden neurons of a NARXNN model with different training functions. It uses the Tracking Signal (TS) and rejects all m...

This research brings forward the Pleione Formosana Hayata Orchid product market demand forecasting system to assist the traditional market personnel to forecast the demand of its customer in the future. The characteristic of Pleione Formosana orchid is one bulb with one leaf only. It sells by the bulbs. By the time for harvesting the operating personnel need spend much capital on the stock of b...

The relevance of risk preference and forecasting accuracy to the survival of investors is an issue that has recently attracted a number of recent theoretical studies. At one extreme, it has been shown that risk preference can be entirely irrelevant, and that in the long run what distinguishes the agents who survive from those who vanish is just their forecasting accuracy. Being in line with the...

We take up the challenge of forecasting out-of-sample monthly returns on stock market indices. Recent contributions show that a wide range of popular predictors poorly forecast the US equity premium when the performance is compared to the average predictor. We revisit these findings focusing on three aspects. First, we report results for four major stock markets: US, UK, Germany and Japan. We f...

Financial markets all over the world have witnessed growing integration within as well as across boundaries, spurred by deregulation, globalization and advances in information technology. However, none of the researches have investigated the trading profitability of models that employed the financial market integration information as input variables especially in the case of day trading. Moreov...

Most procedures for modeling and forecasting financial asset return volatilities rely on restrictive and complicated parametric GARCH or stochastic volatility models. The method of realized volatility constructed from high-frequency intraday returns is an alternative choice for volatility measurement. In this paper we make an empirical analysis on Chinese stock index data by using the method of...