| October 1, 2020
Project Overview
Recent work seeks to exploit the mathematical models of temporal point processes in automatic trading. These mathematical models have been studied for many years in a probabilistic framework, but they remain very little studied in association with deep learning [1, 2]. Hawkes’ processes form a special class of temporal point processes that incorporate past events in the current measure of process intensity. The interest of Hawkes’ processes is to provide a very general underlying model that allows them to be applied to a wide variety of phenomena that go far beyond the evolution of stock prices (natural phenomena, epidemiological phenomena, etc.).
References:
[1] Yan, J., Xu, H., & Li, L. (2019). Modeling and Applications for Temporal Point Processes. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 3227-3228. https://doi.org/10.1145/3292500.3332298 [2] Xu, H. (s. d.). Modeling and Applications for Temporal Point Processes—Part I.