The Overnight Jump: Disentangling Microstructural and Informational Volatility in TOCOM Rubber Futures
The systematic failure of standard Value-at-Risk (VaR) models for the Tokyo Commodity Exchange (TOCOM) rubber futures contract poses significant challenges for risk management. This study addresses the issue by examining the market’s split trading sessions, which induce distinct overnight and intraday volatility regimes. We decompose daily returns into these two components and apply tailored Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models. Our empirical results, strengthened by extensive robustness checks using EGARCH, IGARCH, and GJR-GARCH specifications, reveal that intraday volatility is persistent and influenced by leverage effects, whereas overnight volatility behaves as a jump-driven process unaccounted for by conventional models. Comprehensive VaR backtesting confirms that while traditional models accurately capture intraday risk, all standard daily models—including asymmetric variants—systematically and severely underestimate overnight risk. These findings demonstrate that aggregating returns into a single daily series conflates different volatility dynamics, leading to model failures. We propose a two-tiered risk management framework that separately applies conventional models to intraday risk and jump-aware measures for overnight risk. This approach aligns risk assessment with underlying market microstructure, improving model validity and capital adequacy for TOCOM rubber futures.
Authors
- Rattikan Saelim (ORCID: https://orcid.org/0000-0003-2998-8297)
- Salang Musikasuwan (ORCID: https://orcid.org/0000-0002-8733-9626)
- Chu Chu (ORCID: https://orcid.org/0009-0001-7501-1981)
Institutions
- Prince of Songkla University (TH)
Publication Details
- Journal
- Journal of risk and financial management
- Published
- 2025-11-06
- DOI
- https://doi.org/10.3390/jrfm18110620
- Primary Topic
- Financial Markets and Investment Strategies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Prince of Songkla University