The Dance of Events: Understanding Hawkes Processes
Learn how Hawkes processes model interconnected events in various fields.
― 4 min read
Table of Contents
Hawkes Processes are fascinating tools in the world of statistics and probability. They help model events that happen in bursts rather than at regular intervals. Imagine a party where one person starts dancing, and soon everyone else joins in. That’s kind of how Hawkes processes work!
What Are Hawkes Processes?
At their core, Hawkes processes are random point processes. This means they are used to describe when certain events occur over time. The special thing about them is that past events can influence future events. For example, if an earthquake happens, it might trigger smaller aftershocks, and one aftershock can cause even more aftershocks. So, the excitement (or Intensity) of the events can build up, much like a crowd at a concert!
Types of Hawkes Processes
Hawkes processes can be divided into three main categories based on their "criticality":
Subcritical: These processes are like a calm party. The excitement (or intensity) from past events eventually dies down. You might think of it as a one-hit wonder at a concert; it’s fun for a moment, but soon everyone moves on.
Critical: Here, the energy at the party remains consistent. Past events can still influence new ones, but they don’t lead to an endlessly growing crowd. Think of it as a group of friends at a party who love to keep the energy alive without letting it spiral out of control.
Supercritical: Now, this is where the party really gets wild! The events feed off each other, and one event can lead to many more. It’s like that moment when the music starts pumping, and suddenly the dance floor is packed with people.
What’s the Big Deal?
So why should we care about Hawkes processes? They are useful in many areas like finance, biology, and social science, helping us understand behaviors and trends.
Finance: In trading, when a large purchase is made, it may lead to more purchases. Understanding this helps traders make informed decisions.
Biology: In nature, one event (like a flower blooming) might encourage others around it to bloom too.
Social Science: If a popular figure makes a statement, it can stir up conversations and reactions, leading to a chain of events.
The Long-Run Behavior
The long-term outcomes of Hawkes processes reveal interesting patterns. Researchers have found that the average number of events and how they disperse can dictate how things will go in the future.
In simple terms, some parties might wind down after a bit, while others can carry on in a lively atmosphere, all depending on how excited the guests are!
The Role of Intensity
Intensity is another key concept in Hawkes processes. It refers to the likelihood of events happening at any given moment. In a subcritical process, the intensity might eventually settle down to a steady state, while in a critical or supercritical process, the intensity can keep climbing.
This concept is crucial for understanding how events build off one another, just like how one dance move can inspire another!
The Mathematical Side
For those who enjoy numbers, there are mathematical ways to describe these processes. Scientists use various limit theorems to predict how events will behave in the long run. They analyze how closely events cluster together, based on statistics and probabilities.
While the math can be a bit daunting, the core idea is pretty straightforward: by measuring past events, we can get a good guess about what might happen next!
In Conclusion
Hawkes processes give us a lens to see how events are interconnected. By studying these fascinating tools, we can better understand many naturally occurring phenomena, from financial markets to social dynamics.
Whether at a party or in the world of economics, the way past events influence future actions is something that connects us all. So next time you see a chain reaction in action, remember the humble Hawkes process that helps explain it!
Enjoy the dance floor, but always keep an eye on the chain reactions around you – just like in a Hawkes process, you never know when the next excitement will start!
Title: Functional Limit Theorems for Hawkes Processes
Abstract: We prove that the long-run behavior of Hawkes processes is fully determined by the average number and the dispersion of child events. For subcritical processes we provide FLLNs and FCLTs under minimal conditions on the kernel of the process with the precise form of the limit theorems depending strongly on the dispersion of child events. For a critical Hawkes process with weakly dispersed child events, functional central limit theorems do not hold. Instead, we prove that the rescaled intensity processes and rescaled Hawkes processes behave like CIR-processes without mean-reversion, respectively integrated CIR-processes. We provide the rate of convergence by establishing an upper bound on the Wasserstein distance between the distributions of rescaled Hawkes process and the corresponding limit process. By contrast, critical Hawkes process with heavily dispersed child events share many properties of subcritical ones. In particular, functional limit theorems hold. However, unlike subcritical processes critical ones with heavily dispersed child events display long-range dependencies.
Authors: Ulrich Horst, Wei Xu
Last Update: 2024-12-29 00:00:00
Language: English
Source URL: https://arxiv.org/abs/2401.11495
Source PDF: https://arxiv.org/pdf/2401.11495
Licence: https://creativecommons.org/licenses/by/4.0/
Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.
Thank you to arxiv for use of its open access interoperability.