hamaadshah / market_risk_gan_tensorflow

Using Bidirectional Generative Adversarial Networks to estimate Value-at-Risk for Market Risk Management using TensorFlow.

Using Bidirectional Generative Adversarial Networks to estimate Value-at-Risk for Market Risk Management

We will explore the use of Bidirectional Generative Adversarial Networks (BiGAN) for market risk management: Estimation of portfolio risk measures such as Value-at-Risk (VaR). Generative Adversarial Networks (GAN) allow us to implicitly maximize the likelihood of a potentially complex distribution. Dealing with high dimensional data potentially coming from a complex distribution is a key aspect to market risk management among many other financial services use cases. GAN, specifically BiGAN, will allow us to deal with potentially complex financial services data such that we do not have to explicitly specify a distribution such as a multidimensional Gaussian distribution.

Python environment

pip3 install -r requirements.txt