Optimal hedging with the cointegrated vector autoregressive model
Soren Johansen and
Bent Nielsen
No 14-23, Discussion Papers from University of Copenhagen. Department of Economics
Abstract:
We review recent asymptotic results on some robust methods for multiple regression. The regressors include stationary and non-stationary time series as well as polynomial terms. The methods include the Huber-skip M-estimator, 1-step Huber-skip M-estimators, in particular the Impulse Indicator Saturation, iterated 1-step Huber-skip M-estimators and the Forward Search. These methods classify observations as outliers or not. From the asymptotic results we establish a new asymptotic theory for the gauge of these methods, which is the expected frequency of falsely detected outliers. The asymptotic theory involves normal distribution results and Poisson distribution results. The theory is applied to a time series data set.
Keywords: Huber-skip M-estimators; 1-step Huber-skip M-estimators; iteration; Forward Search; Impulse Indicator Saturation; Robustified Least Squares; weighted and marked empirical processes; iterated martingale inequality; gauge. (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2014-09-08
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Citations: View citations in EconPapers (1)
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http://www.econ.ku.dk/english/research/publications/wp/dp_2014/1423.pdf (application/pdf)
Related works:
Working Paper: Optimal hedging with the cointegrated vector autoregressive model (2014) 
Working Paper: Optimal hedging with the cointegrated vector autoregressive model (2014) 
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Persistent link: https://EconPapers.repec.org/RePEc:kud:kuiedp:1423
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