Financial Econometrics
Financial econometrics has developed into a very fruitful and vibrant research area in the last two decades. The availability of good data promotes research in this area, specially aided by online data and high-frequency data. These two characteristics of financial data also create challenges for re...
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| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
MDPI - Multidisciplinary Digital Publishing Institute
2019
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| Subjects: | |
| Online Access: | DOAB: download the publication DOAB: description of the publication |
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| 020 | |a 9783039216260 | ||
| 020 | |a 9783039216277 | ||
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| 024 | 7 | |a 10.3390/books978-3-03921-627-7 |c doi | |
| 041 | 0 | |a eng | |
| 042 | |a dc | ||
| 100 | 1 | |a Tse, Yiu-Kuen |4 auth | |
| 245 | 1 | 0 | |a Financial Econometrics |
| 260 | |b MDPI - Multidisciplinary Digital Publishing Institute |c 2019 | ||
| 300 | |a 1 electronic resource (136 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a Financial econometrics has developed into a very fruitful and vibrant research area in the last two decades. The availability of good data promotes research in this area, specially aided by online data and high-frequency data. These two characteristics of financial data also create challenges for researchers that are different from classical macro-econometric and micro-econometric problems. This Special Issue is dedicated to research topics that are relevant for analyzing financial data. We have gathered six articles under this theme. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 653 | |a tuning parameter choice | ||
| 653 | |a Markov process | ||
| 653 | |a model averaging | ||
| 653 | |a n/a | ||
| 653 | |a steady state distributions | ||
| 653 | |a realized volatility | ||
| 653 | |a threshold | ||
| 653 | |a risk prices | ||
| 653 | |a threshold auto-regression | ||
| 653 | |a bond risk premia | ||
| 653 | |a linear programming estimator | ||
| 653 | |a volatility forecasting | ||
| 653 | |a Bayesian inference | ||
| 653 | |a asset price bubbles | ||
| 653 | |a stationarity | ||
| 653 | |a deviance information criterion | ||
| 653 | |a model selection | ||
| 653 | |a probability integral transform | ||
| 653 | |a forecast comparisons | ||
| 653 | |a Markov-Chain Monte Carlo | ||
| 653 | |a explosive regimes | ||
| 653 | |a multivariate nonlinear time series | ||
| 653 | |a Tukey's power transformation | ||
| 653 | |a affine term structure models | ||
| 653 | |a Mallows criterion | ||
| 653 | |a nonlinear nonnegative autoregression | ||
| 653 | |a TVAR models | ||
| 653 | |a stochastic conditional duration | ||
| 653 | |a shrinkage | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/1701 |7 0 |z DOAB: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/47666 |7 0 |z DOAB: description of the publication |