1 citations · 3 across the 13 of their papers we have counts for
15 papers
The Anatomy of Commodity Risk: Micro, Market, and Economy-Wide Sources
Nektarios Aslanidis, Aurelio Bariviera, George Kapetanios +2
We study the anatomy of commodity risk by distinguishing micro, market-level, and economy-wide sources. We develop a two-stage "divide-and-conquer" framework that allows sensitivit…
Nonlinear Boosting with Multiple Testing in High-Dimensional Generalised Linear Models with Binary Responses
Charisios Grivas, George Kapetanios, Zacharias Psaradakis +3
This paper proposes a nonlinear boosting with multiple testing (BMT) approach to variable selection in high-dimensional generalised linear models with binary responses. At each sta…
Estimation and Inference for Latent Dual Networks Using High-Dimensional IV Screening
Arturas Juodis, George Kapetanios, Vasilis Sarafidis
We develop a novel methodology for estimation and inference in high-dimensional panel network models with latent dual structures. The framework allows outcomes to be affected simul…
Grow and Pollute but Invest and Clean: Dynamic Associations between Parent Firm Characteristics and Facility Toxic Releases
George Kapetanios, Steven Ongena, Alexia Ventouri +1
This paper examines how relationships between parent-firm characteristics and facility-level toxic releases evolve over time. Using 238,304 observations for 7,447 U.S. manufacturin…
Network Effects in Corporate Emissions: Evidence from a Data-Dependent Spatial Panel Model
Stylianos Asimakopoulos, George Kapetanios, Vasilis Sarafidis +1
We study spillover effects in corporate toxic emissions using a heterogeneous panel network of U.S. industrial facilities from 2000-2023. Rather than imposing a network structure a…
Model Selection in High-Dimensional Linear Regression using Boosting with Multiple Testing
George Kapetanios, Vasilis Sarafidis, Alexia Ventouri
High-dimensional regression specification and analysis is a complex and active area of research in statistics, machine learning, and econometrics. This paper proposes a new approac…
Detecting Network Instability via Multiscale Detrended Cross-Correlations and MST Topology
Jose De Leon Miranda, Marina Dolfin, George Kapetanios +1
We introduce a multiscale measure of network instability based on the joint use of Detrended Cross-Correlation Analysis (DCCA) and Minimum Spanning Tree (MST) filtering. The propos…
Unlocking the Regression Space
Liudas Giraitis, George Kapetanios, Yufei Li +1
This paper introduces and analyzes a framework that accommodates general heterogeneity in regression modeling. It demonstrates that regression models with fixed or time-varying par…
Heterogeneous Exposures to Systematic and Idiosyncratic Risk across Crypto Assets: A Divide-and-Conquer Approach
Nektarios Aslanidis, Aurelio Bariviera, George Kapetanios +1
This paper analyzes realized return behavior across a broad set of crypto assets by estimating heterogeneous exposures to idiosyncratic and systematic risk. A key challenge arises…
Investor behavior and multiscale cross-correlations: Unveiling regime shifts in global financial markets
Marina Dolfin, George Kapetanios, Leone Leonida +1
We propose an algorithm to capture emergent patterns in the cross-correlations of financial markets, highlighting regime changes on a global scale. In our approach, financial marke…
Heterogeneous Grouping Structures in Panel Data
Katerina Chrysikou, George Kapetanios
In this paper we examine the existence of heterogeneity within a group, in panels with latent grouping structure. The assumption of within group homogeneity is prevalent in this li…
Deep Neural Network Estimation in Panel Data Models
Ilias Chronopoulos, Katerina Chrysikou, George Kapetanios +2
In this paper we study neural networks and their approximating power in panel data models. We provide asymptotic guarantees on deep feed-forward neural network estimation of the co…
A New Test for Market Efficiency and Uncovered Interest Parity
Richard T. Baillie, Francis X. Diebold, George Kapetanios +1
We suggest a new single-equation test for Uncovered Interest Parity (UIP) based on a dynamic regression approach. The method provides consistent and asymptotically efficient parame…
High Dimensional Generalised Penalised Least Squares
Ilias Chronopoulos, Katerina Chrysikou, George Kapetanios
In this paper we develop inference for high dimensional linear models, with serially correlated errors. We examine Lasso under the assumption of strong mixing in the covariates and…
On Robust Inference in Time Series Regression
Richard T. Baillie, Francis X. Diebold, George Kapetanios +2
Least squares regression with heteroskedasticity consistent standard errors ("OLS-HC regression") has proved very useful in cross section environments. However, several major diffi…