Simplified Avellaneda-Stoikov Market Making

Welcome back to Crypto Chassis! Recently we have worked very hard on a brand new product line designed specifically for liquidity providers: an optimal end-to-end solution to market making. We spent a lot of time studying the available solutions already present on the internet and made our best efforts to stand on the shoulders of those giants to become a better player by addressing three important gaps (and sometimes even defects) that we have identified in the process: a. Algorithm-Interpretability, b. Paper-Tradability, and c. Backtest-Ability. This article will explain our work on Algorithm-Interpretability: long story short we simplified Avellaneda-Stoikov inventory control strategy to make its input parameters intuitive enough to understand and reason about from a practical trader’s perspective. A future article will explain our work on Paper-Tradability and Backtest-Ability: long story short we took an event-driven approach rather than a time-driven approach to cope with temporal heterogeneous tick data as opposed to temporal homogeneous bar data. Anyway, our application is live and ready to use: https://github.com/crypto-chassis/ccapi#spot-market-making-beta.

In 2008, Marco Avellaneda and Sasha Stoikov published a seminal academic paper on the subject of market making: https://www.math.nyu.edu/~avellane/HighFrequencyTrading.pdf. The article itself involves a lot of very complicated mathematical equations, which at a first glance certainly overwhelms any practical traders who don’t plan to become university professors. The central proposals from Avellaneda & Stoikov are to address two major concerns from a market maker’s perspective: how to deal with inventory risks and how to find the optimal bid-ask spreads. The mathematical derivations that they went through were lengthy, but the conclusions and insights that they arrived at can be made neat and crisp:

• To minimize inventory risk, prices should be skewed to favor the inventory to come back to its targeted ideal balance point.
• To maximize trade profitability, spreads should be enlarged such that the expected future value of the account is maximized.

Happy coding! To sum up, we have released a spot market making application based on classical Avellaneda-Stoikov strategy as an end-to-end solution for liquidity providers. If you are interested in our work or collaborating with us, join us on Discord https://discord.gg/b5EKcp9s8T. 🎉

Disclaimer: This is an educational post rather than investment/financial advice.

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