Algorithm Architecture

Making Markets, Made Simple.

Centralized Market Making Architecture for Multi-Exchange Operations with Statistical Modelling Integration

Our industry, a robust and intelligent system is pivotal for sustaining market efficiency. Our centralized market making architecture is designed to manage multi-exchange operations in real-time while utilizing machine learning for enhanced decision-making. This document delineates the architecture's components, functionalities, and the efficient structuring of order books on individual exchanges.

Keywords

• Centralized Controller

• Real-Time Data Monitoring

• Arbitrage

• Statistical modelling

Introduction

The architecture focuses on centralizing control logic while allowing for decentralized execution of market making strategies, specific to any pair, across multiple exchanges. The design is plug-and-play, ensuring compatibility with any of our supported exchanges, and is enhanced by statistical modelling for data analysis and decision-making.

Architecture

Centralized Control Unit

The centralized control unit is the brain of the architecture, responsible for:

1. Data Aggregation: Gathering and standardizing real-time public bid, ask, and index data from all supported exchanges.

2. Anomaly and Opportunity Detection: Utilizing statistical modelling to analyse the aggregated data for spotting price anomalies, risks, and arbitrage opportunities more accurately.

3. Instruction Dispatch: Based on the analysis, directives are sent out to individual market making instances for action.

   

Market Making Instances

Each market making instance on individual exchanges takes care of:

1. Order Management: Executes directives for creating, modifying, or cancelling orders.

2. Trade Execution: Fulfils trades when the conditions set by the centralized unit are met.

3. Data Reporting: Sends real-time updates on order book status and executed trades back to the centralized unit.

   

Interaction Flow

1. Centralized unit collects real-time data from every supported exchange.

2. Machine learning algorithms within the centralized unit analyse this data for abnormal conditions or trading opportunities.

3. Based on the analysis, the unit dispatches appropriate instructions to each market making instance.

   

Efficient Order Book Structure

In each exchange, the Order Book is optimized to cumulatively scale with orders at fixed spreads. This ensures:

1. A consistent bid-ask spread

2. Minimized slippage

3. Enhanced price discovery

Cumulative orders at fixed spreads allow the system to handle an increase in trading volume efficiently, thereby ensuring a healthy, stable order book.

Conclusion

Our centralized market-making architecture uniquely combines centralized control, decentralized execution. It offers a sophisticated approach to manage and make decisions across multiple exchanges. By incorporating statistical modelling into real-time data analysis, the architecture goes beyond traditional rule-based systems, offering an agile and intelligent solution for today's volatile cryptocurrency markets.