DQTools is our software library that allows us to quickly build custom crypto-trading reporting solutions for our customers for items such as risk, P&L and margin. Using DQTools, we can build RAD solutions using Microsoft Excel or Google Sheets, and Python Jupyter Notebooks, as well as traditional n-tier solutions.

Sheets Interface

The DQTools analytics library is available in both Google Sheets and Microsoft XL. You have access to all the standard reports, with your own or with Live positions and market data. You can easily define your own pivot tables/graphs to produce custom reports for your own needs.

Historic VaR

Value-at-risk is a statistical measure of the riskiness of a portfolio of assets. It is defined as the maximum amount expected to be lost over a given time horizon, at a pre-defined confidence level. Expected shortfall, an alternative risk measure, aims at mitigating some of VAR’s flaws. Expected shortfall is defined in a similar manner to VAR, but instead of taking the 95% confidence value, we take the mean of the losses over the 5% from 95% to 100%. This mitigates, to a large extent, the 'fat-tails' flaw of VAR. This video demonstrates how to calculate a simple Historic VaR and Expected Shortfall using DQTools.


DQRisk is our flagship product for professional crypto traders. It takes your cash and derivative trades across multiple crypto exchanges, and calculates the risk sensitivities and P&L on your aggregate positions. You can also use DQRisk to view the impact of different scenarios, and its P&L Explain feature lets you analyse the performance of your trading strategies. See a demo of DQRisk


DQLabs is our incubator for new products that we are working on. Currently, DQLabs is working on a product for backtesting crypto-trading strategies.