Computer trading in financial markets is a rapidly developing field with a growing number of applications. Automated analysis of news and computation of market sentiment is a related applied research topic which impinges on the methods and models deployed in the former. In this chapter we have...

Due to its significance, forecasting asset volatility has been an active area of research in recent decades. In this whitepaper we aim to take into account the stylised facts of volatility to improve predictive power of a simple GARCH model. We investigate the power of three GARCH models (GARCH,...

Momentum strategy is one of the most popular strategies that market participants use to make investment decisions. In the past two decades, many researchers have shown that momentum strategy beats the market, and provides attractive portfolio returns. In this study we investigate Dow Jones...

The recommendation of financial analysts plays an important role in making investment decisions. The method of constructing a portfolio using such recommendations does not rely on quantitative models instead it relies on research of the analysts and their qualitative views. We explore paradigms...

We report an empirical study of a predictive analysis model for equities; the model uses high frequency (minute-bar) market data and quantified news sentiment data. The purpose of the study is to identify a predictive model which can be used in designing automated trading strategies. Given that...