Methods and Systems for Bettering 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 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.
1 . An apparatus for market making at low latency, the apparatus comprising:
a processor having parallelized computational resources that implement a bettering 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) streaming derivatives market data, the derivatives market data comprising pricing pertaining to the derivatives, (3) a plurality of pricing parameters pertaining to the derivatives, and (4) a plurality of configuration parameters for operational control of the bettering market making strategy; and
wherein the parallelized computational resources are configured to generate a plurality of quotes for one or more of the derivatives in accordance with the bettering market making strategy based on a plurality of conditions applied to the streaming underlying market data, the streaming derivatives 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 bettering market making strategy, wherein the logic resources implement different portions of the bettering 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 3 wherein the computed theoretical fair prices define exclusion boundaries that govern conditions for decisions to generate the quotes.
5 . The apparatus of claim 2 wherein the configuration parameters include parameters that define a number of tick size increments by which the generated quotes will better an existing quote, and wherein the logic resources include logic that defines conditions for the bettering market making strategy to adjust pricing for the generated quotes by the defined number of tick size increments.
6 . The apparatus of claim 5 wherein the defined number of tick size increments is a single tick increment.
7 . The apparatus of claim 2 wherein the logic resources are configured to generate a quote for a subject derivative that betters pricing for an existing market quote for the subject derivative by a defined number of tick size increments if the bettered pricing for the existing market quote does not fall within an exclusion boundary for the subject derivative as defined by the logic resources, and wherein the logic resources are further configured to define the exclusion boundary for the subject derivative based on a generation of theoretical fair prices for the subject derivative.
8 . The apparatus of claim 2 wherein the logic resources are configured to cancel an existing quote for a quoted derivative if updated current pricing for the quoted derivative as reflected in the streaming derivatives market data falls within an exclusion boundary for the subject derivative as defined by the logic resources, and wherein the logic resources are further configured to define the exclusion boundary for the quoted derivative based on a generation of theoretical fair prices for the quoted derivative.
9 . The apparatus of claim 2 wherein the logic resources are further configured to execute the bettering market making strategy in response to an underlying trigger, a parameter trigger, and/or a new quote trigger.
10 . The apparatus of claim 2 further comprising a quoting boundary memory that is configured to store data defining exclusion boundaries for a plurality of derivatives.
11 . The apparatus of claim 10 wherein the logic resources are further configured to generate a quote for a subject derivative with pricing that betters a new market quote for the subject derivative from the streaming derivatives market data by a defined number of tick size increments if the bettered new market quote has pricing that falls outside the exclusion boundary in the quoting boundary memory for the subject derivative.
12 . The apparatus of claim 11 wherein the logic resources include:
first logic resources configured to process the received streaming underlying market data to generate underlying triggers for a plurality of derivatives in response to changes in pricing for the financial instruments underlying the derivatives;
second logic resources configured to, in response to the generated underlying triggers, generate a plurality of theoretical fair prices for the derivatives, wherein the theoretical fair prices serve as the basis for the exclusion boundaries in the quoting boundary memory with respect to the derivatives, wherein the second logic resources are configured to generate the theoretical fair prices based on (1) first data within the streaming underlying market data that pertain to the financial instruments underlying the derivatives, (2) second data within the streaming pricing parameters that pertain to the derivatives, and (3) third data within the received configuration parameters that pertain to the derivatives;
third logic resources configured to (1) process the received streaming derivatives market data to determine whether there is updated current best bid and offer (BBO) quote pricing for the subject derivative and (2) in response to a determination that there is updated current BBO quote pricing for the subject derivative, generate a bettering trigger for the subject derivative;
fourth logic resources configured to (1) retrieve exclusion boundary data for the subject derivative from the quoting boundary memory and (2) generate a canceling trigger if the updated current BBO quote pricing for the subject derivative as adjusted by the defined number of tick size increments falls within the exclusion boundary defined by the retrieved exclusion boundary data; and
fifth logic resources configured to generate a quote for the subject derivative at the updated current BBO quote pricing as adjusted by the defined number of tick size increments in response to the bettering trigger for the subject derivative unless there is a canceling trigger for the subject derivative, the generated quote for the subject derivative for transmission to one or more derivative trading venues.
13 . The apparatus of claim 12 wherein the first data refreshes at a rate faster than a rate at which the second data refreshes.
14 . The apparatus of claim 12 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.
15 . The apparatus of claim 14 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.
16 . The apparatus of claim 12 further comprising a BBO quote memory that is configured to store data from the one or more derivatives trading venues that represent current BBO quote pricing for a plurality of derivatives; and
wherein the third logic resources are further configured to (1) receive new streaming derivatives market data for a derivative, (2) retrieve the current BBO quote pricing for that derivative from the BBO quote memory, (3) compare BBO pricing for that derivative from the received new streaming derivatives market data with the retrieved current BBO quote pricing for that derivative to determine whether there is an update in the current BBO pricing for that derivative, (4) in response to a determination that there is updated current BBO pricing for that derivative, generate the bettering trigger for that derivative, and (5) provide the bettering trigger for that derivative to the fifth logic resources.
17 . The apparatus of claim 12 wherein the second data comprises, for each of a plurality of the derivatives, (1) a reference theoretical price for the derivative, (2) a reference price for the derivative's underlying financial instrument, and (3) the at least one Greek value for the derivative;
wherein the second logic resources are further configured to, for each of a plurality of the derivatives, compute its theoretical fair price based on its reference theoretical price, its at least one Greek value, and the change in pricing for its underlying financial instrument relative to the reference price for its underlying financial instrument.
18 . The apparatus of claim 17 wherein the at least one Greek value for each derivative comprises a delta value that reflects rate of change between pricing for its derivative relative to pricing for the financial instrument underlying that derivative.
19 . The apparatus of claim 17 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 prices, the reference underlying prices, and the at least one Greek values pertaining to the derivatives from the parameter memory.
20 . The apparatus of claim 17 further comprising an underlying price memory configured to store a plurality of prices from the streaming underlying market data for the financial instruments underlying the derivatives, and wherein the second logic resources are further configured to track the changes in pricing in the financial instruments underlying the derivatives based on the prices stored in the underlying price memory.
21 . The apparatus of claim 12 wherein the fifth logic resources are further configured to schedule transmission of the quote for the subject derivative to the one or more derivatives trading venues.
22 . The apparatus of claim 12 wherein the logic resources further include:
sixth logic resources configured to perform tick size quantization on the generated theoretical fair prices to define quote boundaries that are aligned with tick protocols for the one or more derivatives trading venues.
23 . The apparatus of claim 12 wherein the fifth logic resources are further configured to monitor transmission rates with the one or more derivatives trading venues and schedule the transmission of the 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.
24 . The apparatus of claim 12 wherein the fifth logic resources are further configured to (1) queue the generated quotes in a memory while awaiting transmission to the one or more derivatives trading venues and (2) if the fourth logic resources generate a canceling trigger pertaining to a subject quote in the queue, remove the subject quote from the queue.
25 . The apparatus of claim 12 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; and
wherein the second logic resources are further configured to generate theoretical BBO pricing for one or more derivatives in response to the generated parameter trigger.
26 . 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 joining market making strategy generates quotes for the determined derivatives.
27 . The apparatus of claim 26 wherein the logic resources further comprise:
third logic resources configured to define new quoting boundaries the determined derivatives with respect to the joining market making strategy based on the generated new theoretical fair prices for the determined derivatives; and
fourth logic resources configured to generate a plurality of bettering quotes for a plurality of subject derivatives in response to determinations that existing quotes for the subject derivatives have quote pricing that falls within the defined new quoting boundaries for the subject derivatives.
28 . The apparatus of claim 26 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.
29 . The apparatus of claim 26 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.
30 . The apparatus of claim 29 wherein the first data refreshes at a rate faster than a rate at which the second data refreshes.
31 . The apparatus of claim 26 wherein the second logic resources are further configured to refresh the new theoretical fair prices for the determined derivatives at a rate that is not slower than a refresh rate for the new pricing for the financial instruments underlying the determined derivatives.
32 . The apparatus of claim 26 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.
33 . 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.
34 . 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.
35 . 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.
36 . 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.
37 . 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.
38 . The apparatus of claim 1 wherein the generated quotes include single-sided quotes and/or double-sided quotes.
39 . The apparatus of claim 1 wherein the parallelized computational resources generate mass quotes for a plurality of derivatives based on the bettering market making strategy.
40 . 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 streaming derivatives market data, the derivatives market data comprising pricing pertaining to the 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 bettering 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 streaming derivatives market data, the pricing parameters, and the configuration parameters, wherein the generated quotes are for transmission to one or more derivatives trading venues.