METHOD AND SYSTEM FOR A DYNAMIC EXCHANGE SIMULATOR

Abstract

A system for a simulated stock exchange (a digital twin) and methods for a plurality of test users performing forward testing of order transactions are described. The core of the system is comprised of an AI engine to generate and/or update a limit order book (LOB) according to criterion such as received orders, market conditions and time frame, and a matching engine that executes orders according to exchange's order matching rules. Liquidity generator is an optional component that adds large number of realistic orders to the system to increase liquidity. The AI engine is trained with time-stamped historic order data. The test user's access to the system is through a client application and uses open trading protocols to send orders and receive market data updates. The AI model uses deep learning with an autoregressive generative model for LOB transitions.

CPC Classifications