Message elimination in multi-model risk correlation system

Patent metadata

Field	Value
Publication number	US-11908006-B2
Application number	US-201816227674-A
Country	US
Kind code	B2
Filing date	Dec 20, 2018
Priority date	Dec 20, 2018
Publication date	Feb 20, 2024
Grant date	Feb 20, 2024

Abstract

A computer implemented method for cross asset correlation includes receiving, by a processor, portfolio data for a plurality of portfolios, determining, by the processor, a single portfolio performance vector for each of the plurality of portfolios based on a portfolio specific model, determining, by the processor, a joint portfolio performance vector for the plurality of portfolios based on portfolio specific models, determining, by the processor, for each portfolio, a portfolio specific scalar based on the single portfolio performance vector and the joint portfolio performance vector; and modifying, by the processor, a portfolio risk based on the portfolio specific model and the portfolio specific scalar.

First claim

The invention claimed is:

1. A computer implemented method for cross asset correlation and margining in a trading system, comprising:
receiving, by a processor, portfolio data for a plurality of portfolios;
storing the portfolio data in memory, the memory implemented via one or more storage operations which implement local storage control via a rolling storage scheme storing portfolio data for a set of most recent transactions, thereby filtering the stored portfolio data to only the most recent transactions via the storage operations;
calculating a first plurality of simulations for the each of the plurality of portfolios;
performing a non-overlaid calculation by determining, by the processor, a single portfolio performance vector for each of the plurality of portfolios based on a portfolio specific model and results of the first plurality of simulations;
calculating a second plurality of simulations for the each of the plurality of portfolios;
performing an overlaid calculation by:
determining, by the processor, an alphanumeric code for each of the plurality of asset classes (A k );

compiling, by the processor, a request message for an external database storing one or more joint models for the plurality of asset classes (A k ), where the request message includes the alphanumeric code for each of the plurality of asset classes (A k ), the external database facilitating non-local storage of the one or more joint models for the plurality of asset classes (A k );
receiving, by the processor and responsive to the request message, the one or more joint models for the plurality of asset classes (A k );
determining, by the processor and based on the one or more joint models, a joint portfolio performance vector for the plurality of portfolios based on portfolio specific models and results of the second plurality of simulations; and
determining, by the processor, for each portfolio, a portfolio specific scalar based on the single portfolio performance vector and the joint portfolio performance vector; and

generating a plurality of messages that separate the overlaid calculation from the non-overlaid calculation for an initial margin for the plurality of portfolios based on the portfolio specific model and the portfolio specific scalar, wherein the number of the plurality of messages for the trading system is reduced for margin requirements due to the portfolio specific model and the portfolio specific scalar,
wherein as asset class margin (Λ k ) for each of the plurality of asset classes (A k ) is calculated according to:
Λ k =Percentile Θ (P&L),

wherein Percentile is a function that returns a margin value for the asset class margin (Λ k ) according to a probability distribution for a profit and loss derived from the first plurality of simulations,
wherein the joint margin (Λ joint ) is calculated according to:
Λ joint =Percentile Θ (P&L),

wherein Percentile is a function that returns a margin value for the joint asset margin (Λ joint ) according to a probability distribution for the profit and loss (P&L) derived from the second plurality of simulations,
wherein a reduced initial margin (IM) is calculated according to:
IM=Λ k −w k ·Λ joint

wherein the asset class margin (Λ k ) is reduced by a contribution w k portion of the joint asset margin (Λ joint ),
wherein the reduced IM decreases a computation time for the trading system to process the plurality of portfolios.

2. The computer implemented method of claim 1 , further comprising:
calculating a first margin value for each of the first plurality of simulations; and
calculating a second margin value for each of the second plurality of simulations.

3. The computer implemented method of claim 1 , wherein the Percentile returns the P&L according to a probability (P):
P ( X>Λ joint )=1− CF

wherein CF is a confidence level.

4. The computer implemented method of claim 1 , wherein an offset (θ) for a joint distribution for the first margin and the second margin is calculated according to:

θ
=

Λ
joint

∑

i
=
1

K

Λ
i

5. The computer implemented method of claim 1 , wherein the plurality of portfolios includes at least one portfolio of a first classification and at least one portfolio of a second classification, wherein the joint portfolio performance vector includes values for the first classification and values for the second classification.

6. The computer implemented method of claim 1 , further comprising:
generating an instruction that does not move at least one position from the plurality of portfolios, wherein a single portfolio risk calculated from the single portfolio performance vector would indicate movement of the at least one position of the plurality of portfolios.

7. The computer implemented method of claim 1 , wherein the portfolio risk based on the portfolio specific model and the portfolio specific scalar is independent of a delta value for assets of the plurality of portfolios.

8. The computer implemented method of claim 7 , wherein the delta value is a change in one or more assets compared to a change in a price of a derivative associated with the one or more assets.

9. The computer implemented method of claim 1 , further comprising:
calculating a first allocation of the portfolio risk for a first asset of the plurality of portfolio based on an initial margin for the first asset; and
calculating a second allocation of the portfolio risk for a second asset of the plurality of portfolio based on an initial margin for the second asset, wherein a sum of the first allocation and the allocation corresponds to the portfolio risk.

10. A non-transitory computer readable medium storing processor-issuable instructions that, when executed by at least one processor, cause the at least one processor to:
receive, at a trading system, portfolio data for a plurality of asset classifications;
store the portfolio data in rolling storage via one or more storage operations which implement local storage control allowing storage of a set of most recent transactions, thereby filtering the portfolio data to only the most recent transactions via the storage operations;
perform a non-overlaid calculation by:
calculating a first performance vector for the first asset of the plurality of asset classifications based on a first asset model; and
calculating a second performance vector for the second asset of the plurality of asset classifications based on a second asset model;

perform an overlaid calculation by:
determining an alphanumeric code for each of the plurality of asset classifications;
compiling a request message for an external database storing a third asset model for cross asset correlation for the first asset and the second asset, where the request message includes the alphanumeric code for each of the plurality of asset classifications, the external database facilitating non-local storage of the third asset model for cross asset correlation for the first asset and the second asset;
receiving, responsive to the request message, the third asset model for cross asset correlation for the first asset and the second asset; and
calculating a third performance vector based on the

Assignees

• Chicago Mercantile Exchange Inc

Inventors

• Huchedé Florian
• Hayes Robert
• Gory Abdoulaye
• Nicolay David Henri

Classifications

• G06Q40/04 Primary

  Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange · CPC title

• G06F17/16

  Matrix or vector computation {, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization (matrix transposition G06F7/78)} · CPC title

• G06Q40/06 Primary

  Asset management; Financial planning or analysis · CPC title