JOINT MODELING AND SIMULATION OF AUTOCORRELATED NON-NORMAL TIME SERIES: AN APPLICATION TO RISK AND RETURN ANALYSIS

This 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.


Issue Date:
1999
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/21564
Total Pages:
15
Series Statement:
Selected Paper




 Record created 2017-04-01, last modified 2017-08-24

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