Newest papers

Modeling interest rate swap volatility with GARCH processes

Michał Balcerek, Michał Wronka · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2609.25965 · cited by 0 works (OpenAlex) · open-access PDF

Portuguese

Examinamos a dinâmica da volatilidade condicional da taxa de swap do USD 1Yx10Y usando GARCH(1,1), GJR-GARCH(1,1), e um modelo de GARCH com comutação de dois regimes (MSGARCH). A análise utiliza dados diários de 2007 a 2023 e incorpora medidas implicadas pelo mercado (volatilidade de swap do ATM e o SRVIX in-dex) juntamente com um amplo conjunto de testes de diagnóstico. Os modelos GARCH padrão e GJR-GARCH mostram parâmetros de curta duração estáveis, mas o intercept ω varia significativamente em todas as janelas de rolamento, causando instabilidade na variável de longa duração implícita. Este padrão, confirmado pelo teste de Nyblom, motiva a adoção de uma

Machine translation (Meta M2M100); the English original follows.

Abstract

We examine the conditional volatility dynamics of the USD 1Yx10Y forward swap rate using GARCH(1,1), GJR-GARCH(1,1), and a two-regime Markov-switching GARCH (MSGARCH) model. The analysis uses daily data from 2007 to 2023 and incorporates market-implied measures (ATM swaption volatility and the SRVIX in- dex) together with a broad set of diagnostic tests. Standard GARCH and GJR- GARCH models show stable short-run parameters, but the intercept ω varies markedly across rolling windows, causing instability in the implied long-run vari- ance. This pattern, confirmed by the Nyblom test, motivates adopting a regime- switching specification. MSGARCH mitigates this issue by keeping regime-specific parameters stable and capturing time variation through filtered regime probabili- ties. It delivers the highest log-likelihood and lowest AIC, whereas BIC favours the more parsimonious GJR-GARCH. One-step-ahead backtesting indicates comparable short-horizon accuracy across models, but MSGARCH offers a clearer structural in- terpretation by isolating high- and low-volatility regimes aligned with major market events.

Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese

Topics: Econometrics, Volatility (finance), Autoregressive conditional heteroskedasticity, Interest rate swap, Swap (finance), Economics

Is this paper real? This page was built from OpenAlex and arXiv records, not generated. Software can verify any reference in one call: GET https://store.agentexchange.work/gw/papers/verify?title=...&year=... (0.003 USD), fetch this record as JSON with /gw/papers/paper?id=2609.25965, or list what it cites with /gw/papers/references?id=.... Pay per call in USDC (x402) or with a 19 USD card key for 1,000 calls. Catalogue · llms.txt

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange