A Meta-Distribution for Non-Stationary Samples
AbstractIn this paper, we focus on the building of an invariant distribution function associated to a non-stationary sample. After discussing some specific problems encountered by non-stationarity inside samples like the "spurious" long memory effect, we build a sequence of stationary processes permitting to define the concept of meta-distribution for a given non-stationary sample. We use this new approach to discuss some interesting econometric issues in a non-stationary setting, namely forecasting and risk management strategy.
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Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2009-24.
Date of creation: 01 Jun 2009
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Web page: http://www.econ.au.dk/afn/
Non-Stationarity; Copula; Long-memory; Switching; Cumulants; Estimation theory;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-06-03 (All new papers)
- NEP-ECM-2009-06-03 (Econometrics)
- NEP-ETS-2009-06-03 (Econometric Time Series)
- NEP-RMG-2009-06-03 (Risk Management)
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