Generative Adversarial Networks (GANs) have shown remarkable success as a framework for trainingmodels to produce realistic-looking data. In this work, we propose a GAN to produce realistic real-valued time series, with an emphasis on their application to financial data.Our aim is having a GAN,...

Modeling financial time series is challenging due to their high volatility and unexpected happenings on the market. Most financial models and algorithms trying to fill the lack of historical financial time series struggle to perform and are highly vulnerable to overfitting. As an alternative, we...

This primer is an introduction to time series analysis using the R programming language. Time series analysis is a technique used to analyze and forecast data that is collected over time, and is widely used in fields such as finance, economics, and meteorology. Time series data can be...