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Hawkes processes in finance
The dataset is used to study the properties of the Hawkes process, a self-exciting point process that models the dynamics of financial prices. -
Intra-day seasonalities in financial markets
The dataset is used to study the properties of the volatility process, including the fat-tails and time-reversal asymmetry. -
Quadratic Hawkes processes for financial prices
The dataset is used to study the properties of the Quadratic Hawkes process, a generalization of the Hawkes process that includes quadratic feedback effects. -
Market Returns and Volatility
The dataset used in this paper is a time series of monthly excess returns and volatility from 1927 to 2019. -
Merton Jump Diffusion Synthetic Data
The dataset used in this paper is a collection of synthetic market data generated via a Merton jump diffusion. -
Geometric Brownian Motion Synthetic Data
The dataset used in this paper is a collection of synthetic market data generated via a geometric Brownian motion. -
SPY Index Log-Returns
The dataset used in this paper is a collection of one-hourly log-returns rS associated to the SPY index from 2005-01-03 to 2020-12-31. -
Financial dataset
Real-world financial dataset used in experiments, sourced from reputable financial databases and APIs like Yahoo Finance and Alpaca News API.
