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 sy...
| Main Authors: | , , , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Singapore :
Springer,
2026.
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| Series: | SpringerBriefs in statistics. JSS research series in statistics.
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| Subjects: |
| Summary: | 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. |
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| Physical Description: | 1 online resource (xi, 124 pages) : illustrations. |
| Bibliography: | Includes bibliographical references. |
| ISBN: | 9789819580453 (electronic bk.) 9819580455 |
| ISSN: | 2364-0065 |