2 citations · 2 across the 11 of their papers we have counts for
11 papers
Online detection of distributional changes for time series in metric spaces
B. Cooper Boniece, Lajos Horváth, Lorenzo Trapani
We propose an online testing framework for detecting distributional changes in serially dependent data with values in a separable metric space. Based on two-sample -statistics,…
Sequential monitoring for distributional changepoints using degenerate U-statistics
B. Cooper Boniece, Lajos Horváth, Lorenzo Trapani
We investigate the online detection of changepoints in the distribution of a sequence of observations using a class of degenerate \textit{U}-statistic-type processes. We consider a…
Debiased Kernel Estimation of Spot Volatility in the Presence of Infinite Variation Jumps
B. Cooper Boniece, José E. Figueroa-López, Tianwei Zhou
Volatility estimation is a central problem in financial econometrics, but becomes particularly challenging when jump activity is high, a phenomenon observed empirically in highly t…
Data-driven fixed-point tuning for truncated realized variations
B. Cooper Boniece, José E. Figueroa-López, Yuchen Han
Many methods for estimating integrated volatility and related functionals of semimartingales in the presence of jumps require specification of tuning parameters for their use in pr…
Efficient Integrated Volatility Estimation in the Presence of Infinite Variation Jumps via Debiased Truncated Realized Variations
B. Cooper Boniece, José E. Figueroa-López, Yuchen Han
Statistical inference for stochastic processes based on high-frequency observations has been an active research area for more than two decades. One of the most well-known and widel…
Efficient Volatility Estimation for Lévy Processes with Jumps of Unbounded Variation
B. Cooper Boniece, José E. Figueroa-López, Yuchen Han
Statistical inference for stochastic processes based on high-frequency observations has been an active research area for more than a decade. One of the most well-known and widely s…
Wavelet eigenvalue regression in high dimensions
Patrice Abry, B. Cooper Boniece, Gustavo Didier +1
In this paper, we construct the wavelet eigenvalue regression methodology in high dimensions. We assume that possibly non-Gaussian, finite-variance -variate measurements are mad…
On high-dimensional wavelet eigenanalysis
Patrice Abry, B. Cooper Boniece, Gustavo Didier +1
In this paper, we characterize the asymptotic and large scale behavior of the eigenvalues of wavelet random matrices in high dimensions. We assume that possibly non-Gaussian, finit…
On operator fractional Lévy motion: integral representations and time reversibility
Benjamin Cooper Boniece, Gustavo Didier
In this paper, we construct operator fractional Lévy motion (ofLm), a broad class of non-Gaussian stochastic processes that are covariance operator self-similar, have wide-sense st…
On fractional Lévy processes: tempering, sample path properties and stochastic integration
Benjamin Cooper Boniece, Gustavo Didier, Farzad Sabzikar
We define two new classes of stochastic processes, called tempered fractional Lévy process of the first and second kinds (TFLP and TFLP , respectively). TFLP and TFLP …
Tempered fractional Brownian motion: wavelet estimation, modeling and testing
B. Cooper Boniece, Gustavo Didier, Farzad Sabzikar
The Davenport spectrum is a modification of the classical Kolmogorov spectrum for the inertial range of turbulence that accounts for non-scaling low frequency behavior. Like the cl…