Adaptive-Lasso MGARCH for the Volatility Spillover of Transition Finance

Yongdeng Xu, Juyi Lyu () and Khelifa Mazouz ()
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Juyi Lyu: Loughborough University, UK
Khelifa Mazouz: Cardiff University, Cardiff, UK

No E2025/19, Cardiff Economics Working Papers from Cardiff University, Cardiff Business School, Economics Section

Abstract: Most transition-finance assets (green bonds, EU emission allowances, clean-energy equities) have only a few years of daily data and virtually no intraday history, rendering standard spillover tools either infeasible (high-dimensional MGARCH) or inapplicable (realized-variance VARs). We develop an Adaptive-Lasso MGARCH (AL-MGARCH) estimator that applies an L1 penalty with adaptive weights to shrink negligible cross-effects to zero, reducing the active parameter set from O(N^2) to O(N) while retaining oracle-selection properties. We also generalise Diebold–Yilmaz–style connectedness to daily returns, enabling single-step monitoring of transition-risk networks when intraday data are unavailable. Using eight daily series (2018–2025), we document a bond-centred volatility regime before 2022 and a natural-gas- and coal-centred regime after the Russia–Ukraine shock, reconciling mixed evidence on whether green assets hedge or amplify systemic risk.

Keywords: adaptive Lasso; MGARCH; volatility spillovers; green bonds; clean-energy equities; carbon allowances; transition finance (search for similar items in EconPapers)
JEL-codes: C58 G15 Q40 Q54 (search for similar items in EconPapers)
Date: 2025-09
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Persistent link: https://EconPapers.repec.org/RePEc:cdf:wpaper:2025/19

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