TriSNAR: A Three-Layer Sparse Estimator for Large-Scale Network AutoRegressive Models

57 Pages Posted: 6 May 2020

See all articles by Simon Trimborn

Simon Trimborn

University of Amsterdam - Amsterdam School of Economics (ASE); University of Amsterdam - CeNDEF

Ying Chen

National University of Singapore

Ray-Bing Chen

National Cheng Kung University

Date Written: April 11, 2020

Abstract

Understanding multi-market interactions and identifying leading markets in the global financial network is of interest to investors, regulators and policymakers. To discover the essential dynamic dependencies of digital currency exchanges, we propose TriSNAR, a three-layer sparse estimator for large-scale network autoregressive models, which imposes a structure on the lag-, network/group- and individual-level effects. We determine the asymptotic properties of the sparse estimator and investigate its finite-sample performance in extensive simulations. Numerical analysis shows that TriSNAR obtains a higher accuracy with less computational time per model contestant. We explore the applicability of TriSNAR on a network of 26 cryptocurrency exchanges with hourly pricing information. TriSNAR not only provides good out-of-sample prediction accuracy, but also exactly detects each leading exchange in North America, Europe and Asia.

Keywords: High-Dimensions, Dimension Reduction, Structure Detection, Network Analysis, Bitcoin Exchanges

JEL Classification: C01, C52, C53, C55, C58

Suggested Citation

Trimborn, Simon and Chen, Ying and Chen, Ray-Bing, TriSNAR: A Three-Layer Sparse Estimator for Large-Scale Network AutoRegressive Models (April 11, 2020). Available at SSRN: https://ssrn.com/abstract=3573336 or http://dx.doi.org/10.2139/ssrn.3573336

Simon Trimborn (Contact Author)

University of Amsterdam - Amsterdam School of Economics (ASE) ( email )

Roetersstraat 11
Amsterdam, North Holland 1018 WB
Netherlands

University of Amsterdam - CeNDEF ( email )

Roetersstraat 11
Amsterdam, NL-1018WB
Netherlands

Ying Chen

National University of Singapore ( email )

Department of Mathematics, Faculty of Science
Block S17, Level 4, 10 Lower Kent Ridge Road
Singapore, Singapore 119076
Singapore

Ray-Bing Chen

National Cheng Kung University

No.1, University Road
Tainan
Taiwan

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