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Nonlinear Dynamics of Daily Cash Prices
Author(s) -
Yang SeungRyong,
Brorsen B. Wade
Publication year - 1992
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1242584
Subject(s) - autoregressive conditional heteroskedasticity , heteroscedasticity , econometrics , autoregressive model , mathematics , economics , jump , nonlinear system , distribution (mathematics) , volatility (finance) , statistics , physics , mathematical analysis , quantum mechanics
Daily cash price changes are not normally distributed. Their empirical distributions have fat tails and most are skewed. In addition, they are not independent. Among the diffusion‐jump, extended generalized autoregressive conditional heteroskedasticity (GARCH), and deterministic chaos processes, a GARCH process with residuals following a student distribution is the most likely. Our GARCH model reduces leptokurtosis, removes nonlinear dependence, and provides a considerable improvement over the i.i.d. normal model. The GARCH process is not well calibrated because it cannot explain all the observed nonnormality, but it does yield asymptotically valid hypothesis tests.