Post-Trade Allocation Method for Fair P&L Distribution
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Solution Overview
Problem
Existing methods for post-trade allocation between multiple accounts, especially in exchanges that do not recognize average prices, result in biased allocations due to rounding of contract sizes, failing to guarantee fair convergence of returns across accounts.
Innovation Solution
A computerized method that computes trade allocations to ensure fair and optimal distribution of cumulative profit and loss across accounts based on their relative allocation factors, using a processor to generate a legitimate starting allocation and perturbations, ensuring all accounts have the same sign and optimal allocation, even when rounding is applied.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If rounding of contract sizes is applied in post-trade allocation, then allocation can be implemented in exchanges that do not recognize average prices, but bias in trade allocation occurs
Solution Approach 1:
The patent changes the allocation parameters by using cumulative profit and loss data combined with allocation factors to determine trade allocations. Instead of relying on average prices or simple rounding, the system calculates allocations based on the relationship between cumulative P&L changes and account allocation factors, thereby maintaining accuracy without requiring average price recognition by the exchange.
Solution Approach 2:
The patent replaces the mechanical rounding system with a computational allocation system. Rather than simply rounding contract sizes to nearest integers, the system uses processor-based calculations involving cumulative profit and loss, allocation factors, and iterative adjustments to determine fair allocations, substituting mathematical computation for mechanical rounding rules.
2Ease of operation
If alternative allocation procedures are used for exchanges not recognizing average prices, then allocation can be performed, but convergence towards appropriate allocated portion of returns is not guaranteed
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors cumulative profit and loss across accounts and adjusts allocations iteratively. The allocation process uses feedback from previous allocations and cumulative P&L data to converge towards fair distributions, ensuring that as the number of filled orders grows, the allocations naturally converge to the appropriate allocated portions for each account.
Solution Approach 2:
The patent employs dynamic allocation procedures where allocation factors and cumulative P&L data are continuously updated and reprocessed. Rather than static allocation rules, the system dynamically adjusts allocations based on changing market conditions, account performance, and cumulative results, allowing the system to adapt and converge towards fair outcomes over time.
3Device complexity
If the High Account High Price methodology is used, then allocation can be simplified, but fair outcome is not necessarily guaranteed
Solution Approach 1:
The patent performs preliminary calculations of cumulative profit and loss and allocation factors before executing the actual trade allocation. By pre-computing these essential parameters and establishing the relationship between cumulative P&L changes and account allocations, the system simplifies the subsequent allocation process while ensuring fairness through the predetermined mathematical relationships.
Solution Approach 2:
The patent segments the allocation process into distinct computational steps: calculating cumulative profit and loss, determining allocation factors, computing trade allocations based on these factors, and verifying convergence. This segmentation allows the complex allocation problem to be broken down into manageable computational tasks while maintaining overall fairness through the systematic application of allocation factors at each segment.
Data Source
AI summary
A computer-implemented method for providing an allocation of a filled order made at a particular time, that involves receiving at least a price of a filled order made at a later time; generating a starting allocation across multiple managed accounts based at least in part on allocation factors of each of the multiple managed accounts; generating at least one additional allocation based at least in part on the starting allocation; determining a closest-fitting allocation according to a metric from amongst the starting allocation and the at least one additional allocation, the metric being based at least in part on the price of the filled order made at the later time and on a price of the filled order made at the particular time; and outputting the closest-fitting allocation.