Sep 9 in New Ideas and Innovation
Advanced Post: Hawkes Processes and Modeling Latency Between CME and BrokerTec for Basis Trading
In the world of high-frequency trading, latency—the delay between two systems—is crucial, especially for highly sensitive trades like Treasury futures basis trading. One of the best tools we have to model and understand this latency is the Hawkes process. In this post, we’ll explore what Hawkes processes are, how they work, and how we can apply them to model the latency between two important trading venues: the CME and BrokerTec.
What is a Hawkes Process?
A Hawkes process is a type of stochastic process that is self-exciting, meaning that events have the potential to trigger further events in the near future. Think of it like aftershocks from an earthquake—one event can cause a cascade of others, with the timing and probability of these follow-on events depending on the original one.
In mathematical terms, a Hawkes process models the occurrence of events (such as trades or quotes) with a time-varying intensity function, where the intensity depends on both exogenous factors and past events. The process is “self-exciting” because each event increases the likelihood of more events happening shortly after.
Latency and Basis Trading Between CME and BrokerTec
In the context of Treasury futures basis trading, traders often look for pricing inefficiencies between two venues—CME, where Treasury futures are traded, and BrokerTec, the dominant platform for cash Treasury trading. These inefficiencies, which are typically short-lived, create arbitrage opportunities for traders who can execute quickly.
The challenge here is that the two platforms operate with different latency profiles. If a trader at CME observes a price change in the cash Treasuries market on BrokerTec with a delay, they may miss the arbitrage opportunity. Understanding and modeling this latency between the two venues is crucial for executing profitable trades.
How Hawkes Processes Can Help
Here’s where the Hawkes process comes in. It allows us to model the event arrivals on both platforms—like trade executions or price updates—as a self-exciting process. In this case, we can model how events on BrokerTec (such as price changes) influence events on CME (such as the corresponding futures price change).
By setting up a bi-dimensional Hawkes process, we can model the relationship between the two markets. Here’s how it works:
- Event Influence: Each event (price update) on BrokerTec can increase the intensity of events on CME. This reflects the idea that price changes in cash Treasuries influence future prices.
- Lag and Latency: The Hawkes process can incorporate the time delay (latency) between events on BrokerTec and CME. This helps in estimating the latency between price updates on both platforms.
- Self-Excitation: Each price change on CME can also self-excite future price changes within the futures market. The process reflects how price changes cascade through the market, with some trades triggering others as market participants react.
Practical Application for Basis Trading
For a basis trader, the goal is to identify and exploit pricing differences between cash Treasuries and futures before the market corrects them. Using a Hawkes process to model the latency between CME and BrokerTec allows traders to:
- Estimate Latency: By modeling the self-exciting behavior of price changes across both venues, the Hawkes process helps traders estimate the real-time latency between the two platforms.
- Optimize Execution Timing: With this model, traders can better time their trades by anticipating how long it will take for futures prices on CME to reflect price changes on BrokerTec, allowing them to jump ahead of slower participants.
- Risk Management: The model can also help traders understand the risks associated with latency arbitrage—such as the risk of prices changing faster than expected, leading to missed opportunities or losses.
Extending the Model
The bi-dimensional Hawkes process can also be extended to incorporate more complex relationships, such as the influence of macroeconomic announcements or large institutional orders. Additionally, traders could apply intensity functions to account for varying market conditions, such as periods of high volatility where latency effects may be exaggerated.
Conclusion
Hawkes processes provide a robust framework for modeling the complex and dynamic relationships between high-frequency trading venues like CME and BrokerTec. By understanding how price changes on one platform influence the other and modeling the latency between these events, traders can optimize their basis trading strategies. This not only leads to more efficient execution but also helps manage the risks associated with latency arbitrage.
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Advanced Post: Hawkes Processes and Modeling Latency Between CME and BrokerTec for Basis Trading
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