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Modeling nonlinear dynamics of daily futures price changes
Author(s) -
Gao Andre H.,
Wang George H. K.
Publication year - 1999
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/(sici)1096-9934(199905)19:3<325::aid-fut5>3.0.co;2-6
Subject(s) - futures contract , autoregressive model , econometrics , autoregressive conditional heteroskedasticity , nonlinear system , nonlinear autoregressive exogenous model , series (stratigraphy) , volatility (finance) , economics , mathematics , financial economics , paleontology , physics , quantum mechanics , biology
The purpose of this article is to characterize linear and nonlinear serial dependence in daily futures price changes. The daily prices of four futures are included in this study: (i) S&P 500; (ii) Japanese yen; (iii) Deutsche mark; and (iv) Eurodollar. Our major empirical findings are: (i) Based on the results of nonlinearity tests (that is, the BDS, the Q 2 , and the TAR‐F tests), we found all futures price changes contain nonlinearity in the series; (ii) a GARCH model can explain the source of nonlinearity for three out of four series; (iii) a threshold autoregressive model and autoregressive volatility model can adequately represent nonlinear dynamics of S&P 500 series; and (iv) deterministic chaos is not evident in the scaled residuals from the nonlinear time series models. Hence we favor a statistical time series approach to represent the data‐generating mechanism of futures price changes. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 325–351, 1999