Financial Econometrics

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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Bibliographic Details
Main Author: Tse, Yiu-Kuen (auth)
Format: Book Chapter
Published: MDPI - Multidisciplinary Digital Publishing Institute 2019
Subjects:
tuning parameter choice
Markov process
model averaging
n/a
steady state distributions
realized volatility
threshold
risk prices
threshold auto-regression
bond risk premia
linear programming estimator
volatility forecasting
Bayesian inference
asset price bubbles
stationarity
deviance information criterion
model selection
probability integral transform
forecast comparisons
Markov-Chain Monte Carlo
explosive regimes
multivariate nonlinear time series
Tukey's power transformation
affine term structure models
Mallows criterion
nonlinear nonnegative autoregression
TVAR models
stochastic conditional duration
shrinkage
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Description
Summary: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.
Physical Description:1 electronic resource (136 p.)
ISBN:books978-3-03921-627-7
9783039216260
9783039216277
Access:Open Access

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