Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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 joining market making strategies that post and cancel joining quotes on markets. Further still, the joining market making strategies can be driven by low latency derivative pricing.

Abstract: 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.

Abstract: 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 hedging strategies to place hedging orders on markets when defined conditions are met. Such hedging strategies can be combined with aggressing strategies to hedge against aggressing orders placed by the automated trading engine.

Abstract: 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.

Abstract: 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 bettering market making strategies that post and cancel bettering quotes on markets. Further still, the bettering market making strategies can be driven by low latency derivative pricing.

Abstract: 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 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.

Abstract: 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 multiple market making strategies that post and cancel quotes on markets. Examples of market making strategies that can be implemented by the automated trading engine include basic market making, joining market making, and bettering market making. Further still, the market making strategies can be driven by low latency derivative pricing.

Abstract: 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. Further still, the market making strategies can be driven by low latency derivative pricing.

Abstract: Method and Apparatus for High-Speed Processing of Financial Market Depth Data 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.