12 citations · 18 across the 7 of their papers we have counts for
8 papers
Consistent Causal Inference for High-Dimensional Time Series
Francesco Cordoni, Alessio Sancetta
A methodology for high dimensional causal inference in a time series context is introduced. It is assumed that there is a monotonic transformation of the data such that the dynamic…
Estimation of an Order Book Dependent Hawkes Process for Large Datasets
Luca Mucciante, Alessio Sancetta
A point process for event arrivals in high frequency trading is presented. The intensity is the product of a Hawkes process and high dimensional functions of covariates derived fro…
Action-State Dependent Dynamic Model Selection
Francesco Cordoni, Alessio Sancetta
A model among many may only be best under certain states of the world. Switching from a model to another can also be costly. Finding a procedure to dynamically choose a model in th…
Consistency Results for Stationary Autoregressive Processes with Constrained Coefficients
Alessio Sancetta
We consider stationary autoregressive processes with coefficients restricted to an ellipsoid, which includes autoregressive processes with absolutely summable coefficients. We prov…
Estimation for the Prediction of Point Processes with Many Covariates
Alessio Sancetta
Estimation of the intensity of a point process is considered within a nonparametric framework. The intensity measure is unknown and depends on covariates, possibly many more than t…
Inference for Additive Models in the Presence of Possibly Infinite Dimensional Nuisance Parameters
Alessio Sancetta
A framework for estimation and hypothesis testing of functional restrictions against general alternatives is proposed. The parameter space is a reproducing kernel Hilbert space (RK…