Methods and Systems for Market Making at Low Latency
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.
1 . An apparatus for market making at low latency, the apparatus comprising:
a processor having parallelized computational resources that implement a market making strategy;
wherein the processor is configured to receive (1) streaming underlying market data, the underlying market data pertaining to a plurality of financial instruments underlying a plurality of derivatives, (2) a plurality of pricing parameters pertaining to the derivatives, and (3) a plurality of configuration parameters for operational control of the market making strategy; and
wherein the parallelized computational resources are configured to generate a plurality of quotes for one or more of the derivatives based on a plurality of conditions applied to the streaming underlying market data, the pricing parameters, and the configuration parameters, wherein the generated quotes are for transmission to one or more derivatives trading venues.
2 . The apparatus of claim 1 wherein the parallelized computational resources comprise a plurality of logic resources that operate in parallel with each other to implement the market making strategy, wherein the logic resources implement different portions of the market making strategy.
3 . The apparatus of claim 2 wherein the streaming underlying market data includes a plurality of new events for the financial instruments underlying the derivatives, wherein the logic resources are configured to compute theoretical fair prices for derivatives impacted by the new events at a rate that supports a tick to trade latency less than 1 microsecond, and wherein the generated quotes are based on the computed theoretical fair prices.
4 . The apparatus of claim 2 wherein the market making strategy comprises a basic market making strategy.
5 . The apparatus of claim 4 wherein the logic resources include:
first logic resources configured to process the received streaming underlying market data to generate an underlying trigger for a subject derivative in response to a change in pricing for the financial instrument underlying the subject derivative; and
second logic resources configured to generate theoretical fair pricing for the subject derivative in response to the generated underlying trigger, wherein the second logic resources are configured to generate the theoretical fair pricing based on (1) first data within the streaming underlying market data that pertains to the financial instrument underlying the subject derivative, (2) second data within the streaming pricing parameters that pertains to the subject derivative, and (3) third data within the received configuration parameters that pertain to the subject derivative, wherein the generated quotes include a best bid and/or offer price based on the generated theoretical fair pricing.
6 . The apparatus of claim 5 wherein the logic resources further include a plurality of instances of the second logic resources for generating a plurality of theoretical fair prices for a plurality of subject derivatives in parallel with each other.
7 . The apparatus of claim 6 wherein the logic resources include additional logic resources to determine a plurality of derivatives that are impacted by a new price for a financial instrument within the streaming underlying market data, and wherein a plurality of the instances of the second logic resources are configured to compute the new theoretical fair prices for a plurality of the determined impacted derivatives in parallel.
8 . The apparatus of claim 5 wherein the second data comprises (1) a reference theoretical price for the subject derivative, (2) a reference price for the financial instrument underlying the subject derivative, and (3) at least one Greek value pertaining to pricing for the subject derivative relative to pricing for the underlying financial instrument, wherein the second logic resources are further configured to compute the theoretical fair pricing based on the reference theoretical price, the at least one Greek value, and a change in pricing for the financial instrument underlying the subject derivative relative to the reference underlying financial instrument price.
9 . The apparatus of claim 8 further comprising a parameter memory configured to store (1) a plurality of reference theoretical prices for a plurality of derivatives, (2) a plurality of reference prices for the financial instruments underlying the derivatives, and (3) a set of Greek values for the derivatives, and wherein the second logic resources are configured to retrieve the reference theoretical price, the reference underlying financial instrument price, and at least one the Greek value pertaining to the subject derivative from the parameter memory.
10 . The apparatus of claim 5 wherein the logic resources further include:
third logic resources configured to (1) generate the quote for the subject derivative and (2) schedule transmission of the generated quote for the subject derivative to the one or more derivatives trading venues.
11 . The apparatus of claim 10 wherein the third logic resources are further configured to (1) monitor transmission rates with the one or more derivatives trading venues and (2) schedule the transmission of generated quotes to the one or more derivatives trading venues based on the monitored transmission rates as compared to permitted transmission rate limits with the one or more derivatives trading venues.
12 . The apparatus of claim 10 wherein the third logic resources are further configured to (1) queue generated quotes in a memory while awaiting transmission to the one or more derivatives trading venues and (2) if the second logic resources generate new theoretical fair pricing pertaining to a subject quote in the queue, update the queued subject quote based on the new theoretical fair pricing.
13 . The apparatus of claim 10 wherein the logic resources further include:
fourth logic resources configured to perform tick size quantization on the generated theoretical fair prices for the subject derivative to generate BBO pricing for the quote for the subject derivative that includes one or more defined offsets relative to the theoretical fair pricing for the subject derivative and is aligned with tick protocols for the one or more derivatives trading venues.
14 . The apparatus of claim 5 wherein the logic resources further include:
additional logic resources configured to process the received parameters to determine whether to generate a parameter trigger in response to a change in state of one or more of the pricing parameters and/or configuration parameters; and
wherein the second logic resources are further configured to generate theoretical fair pricing for one or more derivatives with respect to one or more new quotes in response to the generated parameter trigger.
15 . The apparatus of claim 2 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; and
second logic resources configured to generate new theoretical fair prices for the determined derivatives based on the new pricing for the subject financial instrument, wherein the new theoretical fair prices impact how the market making strategy generates quotes for the determined derivatives.
16 . The apparatus of claim 15 wherein the market making strategy comprises a basic market making strategy, and wherein the logic resources further comprise:
third logic resources configured to generate quotes for the determined derivatives at quote prices based on the generated new theoretical fair prices for the determined derivatives as adjusted by defined offsets.
17 . The apparatus of claim 16 wherein the defined offsets establish minimum spreads for the generated quotes.
18 . The apparatus of claim 15 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.
19 . The apparatus of claim 15 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.
20 . The apparatus of claim 15 wherein the second logic resources are further configured to refresh the new theoretical fair prices for the determined derivatives at a computational latency of 5 to 50 nanoseconds.
21 . The apparatus of claim 1 wherein the processor comprises a field programmable gate array (FPGA), and wherein the parallelized computational resources are 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 parallelized computational resources are 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 parallelized computational resources are implemented on the GPU.
24 . The apparatus of claim 1 wherein the parallelized computational resources are further configured to analyze a plurality of the generated quotes in parallel to prioritize the quotes for scheduled transmission to a trading venue.
25 . The apparatus of claim 1 wherein the parallelized computational resources comprise a plurality of logic resources that operate in a parallelized and pipelined manner to achieve a tick to trade latency of 50 nanoseconds to 500 nanoseconds.
26 . The apparatus of claim 25 wherein the parallelized computational resources comprise a plurality of logic resources that operate in a parallelized and pipelined manner to achieve sustained throughputs of at least 10 million messages per second.
27 . The apparatus of claim 1 wherein the processor further comprises one or more feed handlers that ingest streaming market data from one or more trading venues, the streaming market data including the streaming underlying market data, and wherein the one or more feed handlers are configured to (1) normalize and extract fields from the streaming market data and (2) provide the normalized and extracted fields to the parallelized computational resources.
28 . The apparatus of claim 1 further comprising a plurality of the processors, wherein the parallelized computational resources of the processors operate on different sets of derivatives.
29 . The apparatus of claim 1 wherein the generated quotes include single-sided quotes and/or double-sided quotes.
30 . A method for market making at low latency, the method comprising:
receiving streaming underlying market data, the underlying market data pertaining to a plurality of financial instruments underlying a plurality of derivatives;
receiving a plurality of pricing parameters pertaining to the derivatives;
receiving a plurality of configuration parameters for operational control of a market making engine deployed in parallelized computational resources; and
the parallelized computational resources implementing a market making strategy to generate a plurality of quotes for one or more of the derivatives based on a plurality of conditions applied to the streaming underlying market data, the pricing parameters, and the configuration parameters, wherein the generated quotes are for transmission to one or more derivatives trading venues.