Imaxe de Portada

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

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 d...

Descrición completa

Gardado en:
Formato: Online
Idioma:inglés
Publicado: MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
level, slope, and curvature of the yield curve
Nelson-Siegel factors
supervised factor models
combining forecasts
principal components
Minimum variance portfolio
risk
shrinkage
S&amp
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
thema EDItEUR::K Economics, Finance, Business and Management
Acceso en liña:ONIX_20220111_9783036508528_251
Tags: Engadir etiqueta
Sen Etiquetas, Sexa o primeiro en etiquetar este rexistro!
Summary: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.

Títulos similares