Financial markets have always been a point of interest for automated systems. Due to their complex nature, financial algorithms and fintech frameworks require vast amounts data accurately respond market fluctuations. This availability is tied the daily evolution, so it impossible accelerate its acquisition. In this article, we discuss several solutions augmenting datasets via synthesizing reali...

Predicting asset price trends is often posed as a classification problem, where are classified positive or negative. Since series noisy and volatile, it difficult to distinguish true from short-term fluctuations. To this end, several trend definitions have been proposed in the literature, but yet be known how these affect performance of algorithms designed learn such labels historical data. In ...

Control charts are widely used in finding the process out of control. In the context of financial time series ,change points occurrence is dependent on the sentiments of the traders, hence identification of change point in the financial time series is generally subjective. In this information age, emphasis is on the algorithmic trading where machine has to take trading decisions. In this paper ...