Rule-Based Exchange Simulator for Financial Strategy Testing
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Solution Overview
Problem
The complexity of financial management in the growing financial services industry makes it difficult to predict stock market conditions, necessitating a simulated market exchange to determine effective financial portfolio strategies.
Innovation Solution
A rule-based exchange simulator that processes orders based on predefined rules, such as fill, cancel, reject, and market data rules, stored in a rules engine, to simulate market operations and determine order fulfillment status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a simulated market exchange is created to test financial strategies, then the ability to predict and test strategies improves, but the system complexity increases
Solution Approach 1:
The patent creates a simulated exchange that copies real exchange operations and market conditions in a virtual environment. This allows testing of financial strategies against simulated market data without risking real capital, thereby improving prediction reliability while keeping the actual financial system simple and unchanged
Solution Approach 2:
The simulated exchange is divided into separate functional components including order processing modules, market data generation modules, and strategy testing modules. This segmentation allows each component to be independently configured and tested, managing overall system complexity while providing comprehensive strategy validation
2Measurement precision
If multiple rules are implemented for order processing, then the accuracy of simulating real market conditions improves, but the processing time increases
Solution Approach 1:
The system pre-configures multiple market rules, pricing models, and order processing logic before actual order processing begins. Market data and pricing parameters are pre-calculated and stored, allowing orders to be processed by simply matching against pre-established rules rather than computing everything in real-time
Solution Approach 2:
The system uses parameterized rules where market conditions, pricing multipliers, and order processing thresholds can be adjusted without changing the underlying processing logic. This allows accurate simulation of different market scenarios by simply changing parameters rather than implementing separate processing paths for each scenario
Data Source
AI summary
Methods, systems, and computer-readable media for providing a rule based exchange simulator are presented. A plurality of rules may be received at an exchange simulator that define how orders should be processed at the exchange simulator. The received rules may be stored, for instance, at a rules engine. For example, rules may comprise a fill rule, a cancel rule, a reject rule, a no acknowledgment rule, and a market data rule. An order that comprises a stock exchange order may be received at the exchange simulator. For example, an order may comprise a buy or sell order for a particular instrument, such as a stock, and may comprise a particular quantity. Based on the one or more rules stored in the rules engine, the received order may be fully filled, partially filled, or not filled.