Image Processing Tools for Financial Time Series Classification

Time series prediction is a challenge for many complex systems, yet in finance predictions are hindered by the very nature of how financial markets work. In efficient markets, the opportunities for stock price predictions leading to profitable trades are supposed to rapidly disappear. In the growing industry of high-frequency trading, the competition over extracting predictions on stock prices from the increasing amount of available information for performing profitable trades is becoming more and more severe. With the development of big data analysis and advanced deep learning methodologies, traders hope to fruitfully analyse market information, e.g. price time series, through machine learning. Spot prices of stocks provide a simple snapshot representation of a financial market. Stock prices fluctuate over time, affected by numerous factors, and the prediction of their changes is at the core of both long-term and short-term financial investing. The collective patterns of price movements are generally referred to as market states. As a paramount example, when stock prices follow an upward trend, it is called a bull market, and when stock prices follow a downward trend is called a bear market