Capturing common components in high-frequency financial time series: a multivariate stochastic multiplicative error model

DOI10.1016/J.JEDC.2008.01.009zbMath1181.91345OpenAlexW2015598502MaRDI QIDQ2654438

Nikolaus Hautsch

Publication date: 19 January 2010

Published in: Journal of Economic Dynamics \& Control (Search for Journal in Brave)

Full work available at URL: http://publikationen.ub.uni-frankfurt.de/files/3558/07_25.pdf

zbMATH Keywords

common factorefficient importance samplingmultiplicative error modelintra-day trading process

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70)

Related Items (10)

Evaluating multiplicative error models: a residual-based approach ⋮ The impact of transaction duration, volume and direction on price dynamics and volatility ⋮ The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data ⋮ Testing weak exogeneity in multiplicative error models ⋮ Diagnostic checking of the vector multiplicative error model ⋮ Bootstrap prediction intervals for autoregressive conditional duration models ⋮ Adaptive Lasso for vector Multiplicative Error Models ⋮ A Markov-switching multifractal inter-trade duration model, with application to US equities ⋮ Disentangling systematic and idiosyncratic dynamics in panels of volatility measures ⋮ Evaluating vector multiplicative error models with the Hosking-Ljung-Box Portmanteau test and kernel-based test statistics

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