28 citations · 35 across the 6 of their papers we have counts for
6 papers
Granger Causality Detection with Kolmogorov-Arnold Networks
Hongyu Lin, Mohan Ren, Paolo Barucca +1
Discovering causal relationships in time series data is central in many scientific areas, ranging from economics to climate science. Granger causality is a powerful tool for causal…
Whack-a-mole Online Learning: Physics-Informed Neural Network for Intraday Implied Volatility Surface
Kentaro Hoshisashi, Carolyn E. Phelan, Paolo Barucca
Calibrating the time-dependent Implied Volatility Surface (IVS) using sparse market data is an essential challenge in computational finance, particularly for real-time applications…
Predicting public market behavior from private equity deals
Paolo Barucca, Flaviano Morone
We process private equity transactions to predict public market behavior with a logit model. Specifically, we estimate our model to predict quarterly returns for both the broad mar…
Modelling Equity Transaction Networks as Bursty Processes
Isobel Seabrook, Paolo Barucca, Fabio Caccioli
Trade executions for major stocks come in bursts of activity, which can be partly attributed to the presence of self- and mutual excitations endogenous to the system. In this paper…
The Recurrent Reinforcement Learning Crypto Agent
Gabriel Borrageiro, Nick Firoozye, Paolo Barucca
We demonstrate a novel application of online transfer learning for a digital assets trading agent. This agent uses a powerful feature space representation in the form of an echo st…
Localization in covariance matrices of coupled heterogenous Ornstein-Uhlenbeck processes
Paolo Barucca
We define a random-matrix ensemble given by the infinite-time covariance matrices of Ornstein-Uhlenbeck processes at different temperatures coupled by a Gaussian symmetric matrix.…