A class of semiparametric fractional autoregressive GARCH models (SEMIFAR-GARCH), which includes deterministic trends, difference stationarity and stationarity with short- and long-range dependence, and heteroskedastic model errors, is very powerful for modelling financial time series. This...

A new multivariate random walk model with slowly changing parameters is introduced and investigated in detail. Nonparametric estimation of local covariance matrix is proposed. The asymptotic distributions, including asymptotic biases, variances and covariances of the proposed estimators are...

We present new autoregressive logit models for forecasting the probability of a time series of financial asset returns exceeding a threshold. The models can be estimated by maximizing a Bernoulli likelihood. Alternatively, to account for the extent to which an observation does or does not exceed...