Joint Modeling And Simulation Of Autocorrelated Non-Normal Time Series: An Application To Risk And Return Analysis
AbstractThis study presents a technique that can jointly model and simulate the expected values, variances, and covariances of sets of correlated time-series dependent variables that are autocorrelated and non-normal (right or left skewed and/or kurtotic). It illustrates the method by applying it to risk analysis of diversified tropical agroforestry systems.
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Bibliographic InfoPaper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 1999 Annual meeting, August 8-11, Nashville, TN with number 21564.
Date of creation: 1999
Date of revision:
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Resource /Energy Economics and Policy; Risk and Uncertainty;
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- McDonald, James B., 1989. "Partially adaptive estimation of ARMA time series models," International Journal of Forecasting, Elsevier, vol. 5(2), pages 217-230.
- Meyer, Jack, 1977. "Choice among distributions," Journal of Economic Theory, Elsevier, vol. 14(2), pages 326-336, April.
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