129 citations · 137 across the 7 of their papers we have counts for
8 papers
Deep differentiable reinforcement learning and optimal trading
Thibault Jaisson
In many reinforcement learning applications, the underlying environment reward and transition functions are explicitly known differentiable functions. This enables us to use recent…
Liquidity and Impact in Fair Markets
Thibault Jaisson
We develop a theory which applies to any market dynamics that satisfy a fair market assumption on the nullity of the average profit of simple market making strategies. We show that…
Rough fractional diffusions as scaling limits of nearly unstable heavy tailed Hawkes processes
Thibault Jaisson, Mathieu Rosenbaum
We investigate the asymptotic behavior as time goes to infinity of Hawkes processes whose regression kernel has norm close to one and power law tail of the form ,…
The different asymptotic regimes of nearly unstable autoregressive processes
Thibault Jaisson, Mathieu Rosenbaum
We extend classical results about the convergence of nearly unstable AR(p) processes to the infinite order case. To do so, we proceed as in recent works about Hawkes processes by u…
Estimation of slowly decreasing Hawkes kernels: Application to high frequency order book modelling
Emmanuel Bacry, Thibault Jaisson, Jean-Francois Muzy
We present a modified version of the non parametric Hawkes kernel estimation procedure studied in arXiv:1401.0903 that is adapted to slowly decreasing kernels. We show on numerical…
Volatility is rough
Jim Gatheral, Thibault Jaisson, Mathieu Rosenbaum
Estimating volatility from recent high frequency data, we revisit the question of the smoothness of the volatility process. Our main result is that log-volatility behaves essential…