Message elimination in multi-model risk correlation system

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 third asset model for cross asset correlation for the first asset and the second asset;
• and
• calculate a plurality of messages that separate the overlaid calculation from the non-overlaid calculation for a margin requirement based on the first performance vector, the second performance vector and the third performance vector, wherein a quantity for the plurality of messages is reduced for the margin requirement calculation due to the first performance vector, the second performance vector and the third performance vector,
• wherein as asset class margin (Λk) for each of the plurality of asset classifications (Ak) is calculated according to:
• Λk=PercentileΘ (P&L),
• wherein Percentile is a function that returns a margin value for the asset class margin (Λk) according to a probability distribution for a profit and loss derived from one or more simulations,
• wherein the joint margin (Λjoint) is calculated according to:
• Λjoint=PercentileΘ (P&L),
• wherein Percentile is a function that returns a margin value for the joint asset margin (Λjoint) according to a probability distribution for the profit and loss (P&L) derived from the one or more simulations,
• wherein a reduced initial margin (IM) is calculated according to:
• IM=Λk−wk·Λjoint
• wherein the asset class margin (Λk) is reduced by a contribution wk portion of the joint asset margin (Λjoint),
• wherein the reduced IM decreases a computation time for the trading system to process the plurality of portfolios.

A cross asset overlay apparatus comprising:

• a memory;
• and
• a processor disposed in communication with said memory, and configured to issue a plurality of processing instructions stored in the memory, execution of the instructions causing the processor to
• receive portfolio data for a plurality of portfolios;
• store the portfolio data in the 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 portfolio data to only the most recent transactions via the storage operations;
• perform a non-overlaid calculation by calculating a single portfolio performance vector for each of the plurality of portfolios based on a portfolio specific model;
• perform an overlaid calculation by:
• determine an alphanumeric code for each of the plurality of asset classes (Ak);
• compiling a request message for an external database storing one or more joint models for the plurality of asset classes (Ak), where the request message includes the alphanumeric code for each of the plurality of asset classes (Ak), the external database facilitating non-local storage of the one or more joint models for the plurality of asset classes (Ak);
• receiving, responsive to the request message, the one or more joint models for the plurality of asset classes (Ak);
• calculating, based on the one or more joint models for the plurality of asset classes (Ak), a joint portfolio performance vector for the plurality of portfolios based on portfolio specific models;
• and
• calculating, for each portfolio, a portfolio specific scalar based on the single portfolio performance vector and the joint portfolio performance vector;
• and
• generate 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 as asset class margin (Λk) for each of the plurality of asset classes (Ak) is calculated according to:
• Λk=PercentileΘ (P&L),
• wherein Percentile is a function that returns a margin value for the asset class margin (Λk) according to a probability distribution for a profit and loss derived from a first plurality of simulations for the portfolio data,
• wherein the joint margin (Λjoint) is calculated according to:
• Λjoint=PercentileΘ (P&L),
• wherein Percentile is a function that returns a margin value for the joint asset margin (Λjoint) according to a probability distribution for the profit and loss (P&L) derived from a second plurality of simulations for the portfolio data,
• wherein a reduced initial margin (IM) is calculated according to:
• IM=Λk−wk·Λjoint
• wherein the asset class margin (Λk) is reduced by a contribution wk portion of the joint asset margin (Λjoint),
• wherein the reduced IM decreases a computation time for the trading system to process the plurality of portfolios.