Methods and Systems for Low Latency Automated Trading Using a Hedging 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 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.
1 . An apparatus for supporting automated trading at low latency, the apparatus comprising:
a processor having parallelized computational resources that implement an automated trading engine;
wherein the processor is configured to receive (1) streaming market data, the market data pertaining to a plurality of financial instruments and (2) a plurality of parameters for operational control of the automated trading engine; and
wherein the automated trading engine is configured to implement a hedging strategy to generate a plurality of hedging orders for one or more of the financial instruments based on a plurality of conditions applied to the streaming market data and the parameters, wherein the generated hedging orders are for transmission to one or more trading venues.
2 . The apparatus of claim 1 wherein the automated trading engine comprises a plurality of logic resources that operate in parallel with each other to implement the hedging strategy, wherein the logic resources implement different portions of the hedging strategy.
3 . The apparatus of claim 2 wherein the received parameters comprise a plurality hedging parameters, and wherein the logic resources are configured to decide whether to generate a hedging order with respect to a subject financial instrument based on (1) an aggregate change in position for the subject financial instrument and (2) the hedging parameters.
4 . The apparatus of claim 3 wherein the hedging parameters include a hedging ratio.
5 . The apparatus of claim 3 wherein the streaming market data comprises an order fill from a market gateway with respect to one or more previous orders for the subject financial instrument by the automated trading engine, and wherein the logic resources are further configured to (1) determine the aggregate change in position for the subject financial instrument based on the order fill, (2) update a position for the subject financial instrument in a position memory based on the determined aggregate change, (3) retrieve hedging parameters from a parameters memory for the subject financial instrument, (4) retrieve a hedge position for a hedging instrument with respect to the subject financial instrument, (5) determine a hedging action based on the determined aggregate change, the retrieved hedge position, and the retrieved hedging parameters, and (6) generate a hedging order for the hedging instrument based on the determined hedging action.
6 . The apparatus of claim 5 wherein the hedging parameters include a hedging ratio for the subject financial instrument, and wherein the logic resources are further configured to determine the hedging action by (1) comparing a current ratio of the updated position for the subject financial instrument to the retrieved hedge position with the hedging ratio and (2) in response to a determination that the current ratio does not match the hedging ratio, determine the hedging action so that the generated hedging order will achieve the hedging ratio.
7 . The apparatus of claim 5 wherein the hedging instrument is the same financial instrument as the subject financial instrument.
8 . The apparatus of claim 1 wherein the financial instruments include derivatives.
9 . The apparatus of claim 1 wherein the automated trading engine comprises implements the hedging strategy in combination with an aggressing strategy.
10 . The apparatus of claim 9 wherein the automated trading engine comprises a plurality of logic resources that operate in parallel with each other to implement the hedging strategy in combination with the aggressing strategy, wherein the logic resources implement different portions of the hedging and aggressing strategies.
11 . The apparatus of claim 10 wherein the received parameters comprise configuration parameters for operational control of the automated trading engine;
wherein the streaming market data comprises (1) streaming derivatives market data, the derivatives market data pertaining to a plurality of derivatives of the financial instruments, (2) streaming underlying market data, the underlying market data pertaining to the financial instruments underlying the derivatives, and (3) streaming order fill data from one or more derivatives trading venues, the order fill data comprising a plurality of order fills for a plurality of orders pertaining to derivatives that were previously placed by the automated trading engine;
wherein the processor is configured to receive a plurality of pricing parameters pertaining to the derivatives and the underlying financial instruments;
wherein the logic resources are configured to implement the aggressing strategy to generate a plurality of aggressing orders for one or more derivatives based a plurality of conditions applied to the streaming derivatives market data, the streaming underlying market data, the pricing parameters, and the configuration parameters, wherein the generated aggressing orders are for transmission to the one or more derivatives trading venues; and
wherein the hedging orders operate to hedge against the generated aggressing orders.
12 . The apparatus of claim 11 wherein the logic resources comprise:
first logic resources configured to determine a plurality of derivatives that are impacted by new pricing for a subject financial instrument that is present in the streaming underlying market data;
second logic resources configured to generate new theoretical fair prices for the determined derivatives based on the new pricing for the subject financial instrument; and
third logic resources configured to define new aggressing zones for the determined derivatives with respect to the aggressing strategy based on the generated new theoretical fair prices for the determined derivatives.
13 . The apparatus of claim 12 wherein the logic resources further comprise a plurality of parallel instances of the second logic resources for computing new theoretical fair prices for a plurality of the determined derivatives in parallel.
14 . The apparatus of claim 13 wherein the logic resources further comprise a plurality of parallel instances of the third logic resources for defining new aggressing zones for a plurality of the determined derivatives in parallel based on the generated new theoretical fair prices for the determined derivatives.
15 . The apparatus of claim 12 wherein the second logic resources are further configured to generate the new theoretical fair prices based on (1) first data within the streaming underlying market data that pertain to the financial instruments underlying the determined derivatives, (2) second data within the streaming pricing parameters that pertain to the determined derivatives, and (3) third data within the received configuration parameters that pertain to the determined derivatives;
16 . The apparatus of claim 15 wherein the first data refreshes at a rate faster than a rate at which the second data refreshes.
17 . The apparatus of claim 12 wherein the logic resources further comprise:
fourth logic resources configured to generate the aggressing orders for a plurality of subject derivatives in response to detections of existing quotes and/or orders for the subject derivatives that lie within the defined new aggressing zones.
18 . The apparatus of claim 17 further comprising (1) a position memory configured to store positions in the subject derivatives and (2) a parameters memory configured to store hedging parameters for the subject derivatives, wherein the hedging parameters comprise hedging ratios for the subject derivatives, and wherein the logic resources further comprise:
fourth logic resources configured to (1) process the order fills to determine aggregate changes in position for the subject derivatives and (2) update positions in the position memory for the subject derivatives based on the determined aggregate changes; and
fifth logic resources configured to (1) retrieve hedging parameters from the parameters memory for the subject derivatives, wherein the retrieved hedging parameters include hedging ratios for the subject derivatives, (2) retrieve hedge positions for hedging instruments with respect to the subject derivatives, (3) for each of a plurality of the subject derivatives, (i) compare a current ratio of the updated position for that subject derivative to the retrieved hedge position for that subject derivative with the hedging ratio for that subject derivative and (ii) in response to a determination that the current ratio does not match the hedging ratio, generate a hedging order for the hedging instrument for that subject derivative that will achieve the hedging ratio for that subject derivative.
19 . The apparatus of claim 18 wherein the hedging instruments are the same financial instruments as the subject derivatives.
20 . The apparatus of claim 10 wherein the logic resources are configured to generate a hedging order according to the hedging strategy in response to an aggressing order according to the aggressing strategy, wherein the aggressing order comprises an order that takes a long position in a financial instrument at a price per share, and wherein the hedging order comprises an order to buy a put option on the financial instrument at a strike price of the price per share.
21 . The apparatus of claim 1 wherein the processor comprises a field programmable gate array (FPGA), and wherein the automated trading engine is implemented as a hardware logic engine on the FPGA.
22 . The apparatus of claim 1 wherein the processor comprises an application-specific integrated circuit (ASIC), and wherein the automated trading engine is implemented as a hardware logic engine on the ASIC.
23 . The apparatus of claim 1 wherein the processor comprises a graphics processing unit (GPU), and wherein the automated trading engine is implemented on the GPU.
24 . A method for automated trading at low latency, the method comprising:
receiving streaming market data, the market data pertaining to a plurality of financial instruments;
receiving a plurality of parameters for operational control of a hedging strategy deployed in parallelized computational resources; and
the parallelized computational resources implementing the hedging strategy to generate a plurality of hedging orders for one or more financial instruments based on a plurality of conditions applied to the streaming market data and the parameters, wherein the generated hedging orders are for transmission to one or more trading venues.