< 1 min read
In this video we will see how to calculate VaR using Monte-Carlo techniques and our library, DQTools. Using historical market data, we calculate a high-dimensional multivariate distribution based on crypto derivative risk factors,. Then, using samples from that distribution, calculate 95% confidence 1-day VaR and the associated expected-shortfall.
< 1 min read
In this video, we take a look at using DQTools to calculate Historic VaR for Crypto Derivatives. When considering futures and options, we need to model changes in future prices as well as the volatility surface.
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We are pleased to announce that DQTools is now integrated with CCXT giving access to live positions across more than 50 exchanges!
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In this short video, we demonstrate how DQTools can be used to construct a simple historic VaR and Expected Shortfall analaysis for crypto portfolios in just a few lines of code using a Jupyter Notebook.
< 1 min read
For decentralised exchanges, impermanent loss is an additional risk factor that needs to be considered carefully. This article provides an introduction to the basic concepts, viewed through a mathematical lens, with some graphs.