Econometrics, Finance, and Time Series Analysis

This book provides a new contemporary time series approach for econometrics and finance. In a concrete manner a very general divergence between spectra is introduced, resulting in the development of a statistical inference that is efficient and robust, and leads to a new perspective. A measure of systemic risk is also developed in the energy market,which quantifies the cost of energy asset distress vis-à-vis the broader economy during crises, and examines the dynamic interaction between solvency and funding liquidity risk in banks using a panel vector autoregressive (VAR) model. This step shows that a forward-looking measure of capital shortfall under stress is both a predictor and an outcome of funding liquidity risk. Additionally, a new integrated likelihood-based approach for estimating nonlinear panel data models is described. Unlike existing integrated likelihoods, the new integrated likelihood is closer to a genuine likelihood. The book explains why this is due to first-order information unbiasedness, and why it seems to matter more for inference than for estimation. Results of studies in econometrics are provided for support.

• Erscheinungsdatum: 15.07.2026
• Autor/Autorin: Masanobu Taniguchi,Diane Pierret,Martin Schumann,Thomas A. Severini,Gautam Tripathi,Yujie Xue
• Reihe: Mathematics and Statistics (R0)
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 3.4 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 124 Seiten
• ISBN: 9789819580453
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.

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