They will be useful for multi-period forecasting and for assessing the probability of recessions. Our theoretical work will contribute to the development of the methodology of multivariate nonlinear econometric modelling, and it will study the properties of user-oriented methods of evaluating forecasts. Our empirical results will interest government policy-makers and business managers, whose investment decisions depend on forecasts of growth and recessions. The method is Bayesian, with inference based on posterior distributions produced implicitly via the option prices. Returns data enter indirectly, via the prior distributions.
Inference is thus optimal, in the sense of being based on all data relevant to returns.
Returns models which feature time varying, possibly persistent conditional volatility, and conditional skewness and kurtosis, are accommodated, with alternative distributions for the pricing errors also modelled. The method is applied to US and Australian option prices. The innovative model developed here provides a theoretical solution to the important practical problem of testing the sensitivity of interest rate volatility to the level of interest rates. This is of fundamental importance in economics and finance and is the source of a number of celebrated 'rules', such as the Black-Scholes option pricing formula. The significance of the research is to enable the testing of such rules.