Exegy Incorporated

IP Reservoir, LLC

Jeremy Walter Whatley

David E Taylor

Scott Parsons

Kwame Gyang

Michael DeWulf

Timothy Gorham

Richard Bradley

Michael Dewulf

E Taylor David

Disclosed herein are automated trading engine embodiments that operate on market data and re-engineer trading logic to operate on computational resources that are capable of providing highly parallelized and pipelined processing operations to improve tick to trade latency. As an example, logic resources for the automated trading engine can compute updated theoretical fair prices for derivatives at low latency. The automated trading engine can then use such real-time derivative pricing to better drive decision-making by trading strategies implemented by the automated trading engine, such as market making strategies and aggressing strategies.

Methods and systems for pricing derivatives at low latency

Automated trading engine embodiments operate on market data and re-engineer trading logic to operate on computational resources that are capable of providing highly parallelized and pipelined processing operations to improve tick to trade latency. As an example, logic resources for the automated trading engine can perform multiple types of trading strategies such as (1) market making strategies that post and cancel quotes on markets, (2) aggressing strategies that place aggressing orders on markets when defined conditions are met, (3) hedging strategies that place hedging orders on markets to hedge against aggressing orders, and/or (4) canceling strategies to cancel quotes and/or orders on markets when defined conditions are met. Further still, one or more of the trading strategies can be driven by low latency derivative pricing.

Methods and systems for low latency automated trading

Disclosed herein are automated trading engine embodiments that operate on market data and re-engineer trading logic to operate on computational resources that are capable of providing highly parallelized and pipelined processing operations to improve tick to trade latency. As an example, logic resources for the automated trading engine can implement market making strategies that post and cancel quotes on markets. These logic resources can include logic for scheduling the transmissions of quotes to the markets according to various criteria.

Methods and systems for mass quoting at low latency

A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books and price books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order and price books.

Method and apparatus for high-speed processing of financial market depth data

Disclosed herein are automated trading engine embodiments that operate on market data and re-engineer trading logic to operate on computational resources that are capable of providing highly parallelized processing operations to improve tick to trade latency. As an example, logic resources for the automated trading engine can implement aggressing strategies to place aggressing orders on markets when defined conditions are met. Further still, the aggressing strategies can be driven by low latency derivative pricing.

Disclosed herein are automated trading engine embodiments that operate on market data and re-engineer trading logic to operate on computational resources that are capable of providing highly parallelized and pipelined processing operations to improve tick to trade latency. As an example, logic resources for the automated trading engine can implement canceling strategies to cancel quotes and/or orders on markets when defined conditions are met. For example, if new trades indicate that existing quotes and/or orders are no longer advantageous, the logic resources can act quickly to cancel those quotes and/or orders.

Methods and systems for low latency automated trading using a canceling strategy

Disclosed herein are automated trading engine embodiments that operate on market data and re-engineer trading logic to operate on computational resources that are capable of providing highly parallelized and pipelined processing operations to improve tick to trade latency. As an example, logic resources for the automated trading engine can implement aggressing strategies to place aggressing orders on markets when defined conditions are met. Further still, the aggressing strategies can be driven by low latency derivative pricing.

Methods and systems for low latency automated trading using an aggressing strategy

A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.

A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to generate a quote event in response to a limit order event being determined to modify the top of an order book.

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Ballwin, MO, United States of America

Jeremy Walter Whatley