Electronic Trading Platform Allocation Using Trader Decline Ratios
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Solution Overview
Problem
Existing electronic trading platforms face challenges in efficiently matching buy and sell orders due to varying trader behaviors and liquidity management, leading to inefficiencies and suboptimal execution of trades.
Innovation Solution
A computer-implemented method that classifies traders into different types based on their decline ratio of previously declined aggressive IOIs and allocates aggressive IOIs dynamically, using a real-time algorithm that considers trader types, decline ratios, and pre-determined criteria to optimize trade execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a trading venue implements its own set of rules and protocols for order submission, then the trading venue can maintain control over order execution, but the complexity of the order submission process increases and liquidity management becomes less efficient
Solution Approach 1:
The system segments traders into different classes (e.g., institutional vs. retail traders) and applies different submission rules to each class. This allows the trading venue to maintain control over order execution while reducing the overall complexity by standardizing rules for specific trader segments rather than applying uniform complex rules to all traders.
Solution Approach 2:
The system dynamically adjusts submission parameters based on trader classification, such as modifying order submission timing, quantity limits, or pricing rules according to the trader's class. This enables the venue to maintain execution control while adapting rules to simplify the submission process for different trader types.
2Reliability
If the trading venue requires transformation of buy/sell orders to meet specific rules and protocols, then the trading venue can ensure compliant order execution, but the time required for order processing increases
Solution Approach 1:
The system performs preliminary classification of traders and pre-configures their submission parameters before order execution is needed. By preparing trader profiles and pre-establishing their specific rules and protocols, the venue can quickly process orders without time-consuming transformation, while still ensuring compliant execution through the pre-defined rules.
3Device complexity
If the trading venue applies uniform rules to all traders, then the system remains simple to manage, but traders with lower decline ratios are not prioritized and liquidity quality deteriorates
Solution Approach 1:
The system applies different rules and treatment levels to different trader classes or segments. By identifying and prioritizing traders with lower decline ratios (indicating higher liquidity quality), the venue can allocate resources and processing priority locally to these preferred traders, thereby improving overall liquidity management efficiency while maintaining relatively simple management through clear class-based differentiation.
Data Source
AI summary
In some embodiments, the instant invention provides for specifically programming a computer machine to perform at lease: receiving, from a trader, a passive indication of interest (IOI) for a financial instrument, where the passive IOI is a bid or an offer and a resting liquidity; classifying the trader as at least: a trading type that is subject to a decline ratio calculation for crossing the passive IOIs, where the decline ratio calculation identifies how many eligible aggressive IOIs have been previously declined by the trader out of a total number of all eligible aggressive IOIs that were offered to such trader; receiving, from another trader, another IOI that is an aggressive IOI, where the aggressive IOI is available to be immediately crossed at the price; and determining, in real-time, an allocation of the aggressive IOI to the trader submitted the passive IOI based on the decline ratio of the trader.