Wavelet Improvement in Turning Point Detection using a Hidden Markov Model
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Other versions of this item:
- Li, Yushu & Reese, Simon, 2014. "Wavelet improvement in turning point detection using a Hidden Markov Model," Discussion Papers 2014/10, Norwegian School of Economics, Department of Business and Management Science.
References listed on IDEAS
- Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, January.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
- Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
- Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, EconWPA.
- Grané, Aurea & Veiga, Helena, 2009. "Wavelet-based detection of outliers in volatility models," DES - Working Papers. Statistics and Econometrics. WS ws090403, Universidad Carlos III de Madrid. Departamento de Estadística.
More about this item
KeywordsHMM; turning point; wavelet; outlier;
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2012-05-29 (All new papers)
- NEP-ECM-2012-05-29 (Econometrics)
- NEP-ETS-2012-05-29 (Econometric Time Series)
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