Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data

doi:10.3390/books978-3-0365-0853-5

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https://mdpi.com/books/pdfview/book/3961

Contributor(s)

Swanson, Norman R. (editor)

Yang, Xiye (editor)

Language

English

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Abstract

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.

URI

https://directory.doabooks.org/handle/20.500.12854/76515

Keywords

level, slope, and curvature of the yield curve; Nelson-Siegel factors; supervised factor models; combining forecasts; principal components; Minimum variance portfolio; risk; shrinkage; S& P 500; high-frequency; volatility; forecasting; realized measures; bivariate GARCH; Japanese candlestick; ordered fuzzy number; Kosiński’s number; oriented fuzzy number; dynamic analysis of securities; integrated volatility; high-frequency data; jumps; realized skewness; cross-sectional stock returns; signed jump variation; long-range dependence; log periodogram regression; smoothed periodogram; subsampling; intraday returns; portfolio selection; maximum diversification; regularization