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References (49)
-
W. Schmid, Dobromir Tzotchev (2004)
Statistical Surveillance of the Parameters of a One-Factor Cox–Ingersoll–Ross ModelSequential Analysis, 23
-
H. Ngai, Jian Zhang (2001)
MULTIVARIATE CUMULATIVE SUM CONTROL CHARTS BASED ON PROJECTION PURSUIT -
Olha Bodnar, W. Schmid (2007)
Surveillance of the mean behavior of multivariate time seriesStatistica Neerlandica, 61
-
Xiaohu Li, Zhengcheng Zhang, Yudan Wu (2009)
Some new results involving general standby systemsApplied Stochastic Models in Business and Industry, 25
-
RC Merton (1980)
On estimating the expected return on the market, 8
-
S. Taylor (2005)
Asset Price Dynamics, Volatility, and Prediction -
H. Kramer, L. Schmid (1997)
Ewma charts for multivariate time seriesSequential Analysis, 16
-
R. Engle, Kenneth Kroner (1995)
Multivariate Simultaneous Generalized ARCHEconometric Theory, 11
-
Elena Andreou, Eric Ghysels (2006)
Quality Control for Structural Credit Risk ModelsEconometrics eJournal
-
Vasyl Golosnoy, S. Ragulin, W. Schmid (2009)
Multivariate CUSUM chart: properties and enhancementsAStA Advances in Statistical Analysis, 93
-
H. Herwartz, Hans-Eggert Reimers (2002)
Empirical modelling of the DEM/USD and DEM/JPY foreign exchange rate: Structural shifts in GARCH‐models and their implicationsApplied Stochastic Models in Business and Industry, 18
-
E Andreou, E Ghysels (2006)
Monitoring disruptions in financial markets, 135
-
K. Zamba, Douglas Hawkins (2006)
A Multivariate Change-Point Model for Statistical Process ControlTechnometrics, 48
-
S Bersimis, S Psarakis, J Panaretos (2007)
Multivariate statistical process control: an overview, 23
-
D. Montgomery (1985)
Introduction to Statistical Quality Control -
H. Hotelling (1947)
Multivariate Quality Control-illustrated by the air testing of sample bombsights -
M. Frisén (2009)
Optimal Sequential Surveillance for Finance, Public Health, and Other AreasSequential Analysis, 28
-
P. Śliwa, W. Schmid (2005)
Surveillance of the covariance matrix of multivariate nonlinear time seriesStatistics, 39
-
Vasyl Golosnoy, S. Ragulin, W. Schmid (2011)
CUSUM control charts for monitoring optimal portfolio weightsComput. Stat. Data Anal., 55
-
T. Philips, E. Yashchin, David Stein (2003)
Using Statistical Process Control to Monitor Active Managers, 30
-
Elena Andreou, Eric Cirano, Eric Ghysels, Valentina Corradi, Piotr Kokoszka, Theo Nijman, Werner Ploberger, Baswerker
Série Scientifique Scientific Series Monitoring for Disruptions in Financial Markets Monitoring for Disruptions in Financial Markets * -
Olha Bodnar, W. Schmid (2011)
CUSUM charts for monitoring the mean of a multivariate Gaussian processFuel and Energy Abstracts
-
Vasyl Golosnoy, Iryna Okhrin, W. Schmid (2010)
New characteristics for portfolio surveillanceStatistics, 44
-
R. Engle (2000)
Dynamic Conditional Correlation : A Simple Class of Multivariate GARCH ModelsERN: Time-Series Models (Multiple) (Topic)
-
(2008)
Financial Surveillance -
RW Hoerl, RD Snee (2009)
Post‐financial meltdown: what do the services industries need from us now?, 25
-
Z. Stoumbos, M. Reynolds, T. Ryan, W. Woodall (2000)
The State of Statistical Process Control as We Proceed into the 21st CenturyJournal of the American Statistical Association, 95
-
W. Woodall (2000)
Controversies and Contradictions in Statistical Process ControlJournal of Quality Technology, 32
-
J. Coleman, J. Nickerson (2005)
A multivariate exponentially weighted moving average control chart for photovoltaic processesConference Record of the Thirty-first IEEE Photovoltaic Specialists Conference, 2005.
-
T. Bollerslev (1990)
Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH ModelThe Review of Economics and Statistics, 72
-
H Hotelling (1947)
Techniques of Statistical Analysis -
S. Bersimis, S. Psarakis, J. Panaretos (2007)
Multivariate statistical process control charts: an overviewQuality and Reliability Engineering International, 23
-
C. Hafner, O. Reznikova (2012)
On the estimation of dynamic conditional correlation modelsComput. Stat. Data Anal., 56
-
CA Lowry, WH Woodall, CW Champ, SE Rigdon (1992)
A multivariate exponentially weighted moving average control chart, 34
-
J. Pignatiello, G. Runger (1990)
Comparison of multivariate CUSUM chartsQuality Engineering, 36
-
R. Merton (1980)
On Estimating the Expected Return on the Market: An Exploratory InvestigationCapital Markets: Asset Pricing & Valuation
-
(1996)
Technical Document -
A. Zeileis, Ajay Shah, I. Patnaik (2010)
Testing, monitoring, and dating structural changes in exchange rate regimesComput. Stat. Data Anal., 54
-
R. Engle (2002)
Dynamic Conditional CorrelationJournal of Business & Economic Statistics, 20
-
J. Ord, A. Koehler, R. Snyder, Rob Hyndman (2009)
Monitoring processes with changing variancesInternational Journal of Forecasting, 25
-
R. Crosier (1988)
Multivariate generalizations of cumulative sum quality-control schemesTechnometrics, 30
-
M. Frisén, E. Andersson, L. Schiöler (2010)
Evaluation of multivariate surveillanceJournal of Applied Statistics, 37
-
Charles Champ, Allison Jones-Farmer (2007)
Properties of Multivariate Control Charts with Estimated ParametersSequential Analysis, 26
-
L. Bauwens, S. Laurent, J. Rombouts (2003)
Multivariate GARCH Models: A SurveyEconometrics eJournal
-
RS Tsay (2005)
Analysis of Financial Time Series -
E. Rossi, F. Spazzini (2010)
Model and distribution uncertainty in multivariate GARCH estimation: A Monte Carlo analysisComput. Stat. Data Anal., 54
-
Vasyl Golosnoy, Iryna Okhrin, W. Schmid (2011)
Statistical Surveillance of Volatility Forecasting ModelsEconometrics: Econometric & Statistical Methods - General eJournal
-
Olha Bodnar, W. Schmid (2009)
Discussion on “Optimal Sequential Surveillance for Finance, Public Health, and Other Areas” by Marianne FrisénSequential Analysis, 28
-
R. Tsay (2005)
Analysis of Financial Time Series: Tsay/Analysis of Financial Time Series
- Publisher
- Wiley
- Copyright
- Copyright © 2014 John Wiley & Sons, Ltd.
- ISSN
- 1524-1904
- eISSN
- 1526-4025
- DOI
- 10.1002/asmb.1980
- Publisher site
- See Article on Publisher Site
Abstract
Timely detection of changes in the mean vector of multivariate financial time series is of great practical importance. In this paper, the covariance dynamics of the multivariate stochastic processes is assessed by either the RiskMetrics approach, the constant conditional correlation, or the dynamic conditional correlation models. For online monitoring of mean changes, we introduce several control schemes based on exponential smoothing and cumulative sums, which explicitly account for heteroscedasticity. The detecting ability of the introduced charts is compared for different processes in a Monte Carlo simulation study. The empirical study illustrates monitoring of changes in the mean vector of daily returns of exchange rates. Copyright © 2013 John Wiley & Sons, Ltd.
Journal
Applied Stochastic Models in Business and Industry – Wiley
Published: Jan 1, 2014
Keywords: ; ; ;