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Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data
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Recently, considerable attention has been placed on the development and application of tools useful for the analysis of the high-dimensional and/or high-frequency datasets that now dominate the landscape. The purpose of this Special Issue is to collect both methodological and empirical papers that develop and utilize state-of-the-art econometric techniques for the analysis of such data.
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Keywords
- bivariate GARCH
- combining forecasts
- cross-sectional stock returns
- dynamic analysis of securities
- Economics, finance, business & management
- Forecasting
- high-frequency
- high-frequency data
- integrated volatility
- intraday returns
- Japanese candlestick
- jumps
- Kosiński’s number
- level, slope, and curvature of the yield curve
- log periodogram regression
- long-range dependence
- maximum diversification
- Minimum variance portfolio
- Nelson-Siegel factors
- ordered fuzzy number
- oriented fuzzy number
- P 500
- portfolio selection
- principal components
- realized measures
- realized skewness
- regularization
- Risk
- S&
- shrinkage
- signed jump variation
- smoothed periodogram
- subsampling
- supervised factor models
- thema EDItEUR::K Economics, Finance, Business and Management
- volatility
Links
DOI: 10.3390/books978-3-0365-0853-5Editions