---
title: "Ayrat Murtazin (@ayratmurtazin) | Hashnode"
description: "I publish free Python trading notebooks every week. Grab my free starter pack of 3 ready-to-run strategies here → https://shorturl.at/WVdNF"
url: "https://hashnode.com/@ayratmurtazin"
---

@ayratmurtazin

# Ayrat Murtazin

@ayratmurtazin · London, UK · Joined April 2026

I publish free Python trading notebooks every week. Grab my free starter pack of 3 ready-to-run strategies here → https://shorturl.at/WVdNF

## Comments

[Quick breakdown of why Hawkes matters here: A standard Poisson process (used in classic Merton) has no memory. The probability of the next jump is the same whether a jump just happened or not. A Hawkes process is self-exciting — each arriving event temporarily raises the rate of future events. The excitation decays exponentially: λ(t) = λ₀ + α · Σ exp(−β · (t − tᵢ)) The key constraint: α/β < 1 keeps the process stationary. Push past that and intensity explodes. In practice, this means a single bad print can cascade — and the simulation captures exactly that.](https://hashnode.com/forums/thread/volatility-clustering-in-an-intraday-multi-asset-universe-using-merton-hawkes-jump-diffusion-simulations-in-python/comment/69dd0433f57346bc1e0fcd34)

Comment · Thread · Apr 13 · 1 · [Volatility Clustering in an Intraday Multi-Asset Universe Using Merton–Hawkes Jump-Diffusion Simulations in Python](https://hashnode.com/forums/thread/volatility-clustering-in-an-intraday-multi-asset-universe-using-merton-hawkes-jump-diffusion-simulations-in-python)