The volatility of financial markets: A time-series analysis of foreign exchange futures.
AdvisorTaylor, Lester D.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThis research introduces hedging and basis risk models based on intertemporal asset pricing between futures and spot currency exchange markets. Recently developed time-series models are employed and empirically tested for five currencies: the British pound, Canadian dollar, Deutschemark, Japanese yen and Swiss franc. The models of international intertemporal asset pricing, which have heretofore been largely based on the rational expectations hypothesis, are modified to allow for risk aversion. Recent research has demonstrated that the presence of risk premia can separate the expected future spot prices from certain speculative prices, such as futures and forward exchange rates, at the maturity date. My results show that there is strong indication of varying risk premia, as reflected in heteroskedastic error terms through time, in both hedging and basis risk models. The nature of heteroskedasticity is well captured by Autoregressive Conditional Heteroskedasticity (ARCH) and generalized ARCH (GARCH) models, which may explain the excess volatility of financial markets. Some markets indicate that the correct specification of models are ARMA with ARCH. I also extend the analysis from univariate to multivariate models, where the problem of heteroskedasticity is reflected in a system of equations. A multivariate ARCH model allows the conditional variance-covariance matrix to vary over time. The results support the hypotheses of varying risk premia for both hedging and basis risk models. The results of specification tests indicate that the models based on financial theory can be improved by introducing additional variables such as lagged endogenous and exogenous variables. This study shows how important it is to incorporate the varying variances and covariance matrices into financial models and it also shows that currently established financial models may need to be modified in order to capture the behavior for foreign exchange future markets.