While theory of autoregressive conditional heteroskedasticity (ARCH) models is well understood for strictly stationary processes, some recent interest has focused on the nonstationary case. In the classical model including a positive intercept parameter, the volatility process diverges to...

This article tests the linearity assumption underlying the popular heterogeneous autoregressive model for realized volatility (HAR-RV). We implement a consistent model specification test that is robust to both distributional and model misspecification. We find that, using a nonparametric HAR-RV...

In this note it is shown that the expectation of the usual MLE estimator of the mean-reversion parameter in linear diffusion models does not exist. However, the moment does exist conditionally on the estimator of the autoregressive parameter in the discretized model being positive.

This paper proposes a couple of new methods to compute the news impact curve for stochastic volatility (SV) models. The new methods incorporate the joint movement of return and volatility, which has been ignored by the extant literature. The first method employs the Bayesian Markov chain Monte...

The creation of a common cross-border stock trading platform is found, by use of a Flexible Dynamic Component Correlations (FDCC) model, to have increased long-run trends in conditional correlations between foreign and domestic stock market returns.

We investigate the impact of monetary conditions on stock market returns at different points on the return distributions. Our results reveal no association between stock returns and monetary environments at the lower quantiles. At the upper quantiles, however, we find that expansive monetary...

This paper presents evidence that the price of oil does not respond contemporaneously to shocks to the US gasoline market. We find no support for the hypothesis of feedback from the US gasoline market to the price of oil, justifying the identification of impulse response functions by applying a...

Novel data-driven analyses, appropriate for detecting economic instability in non-stationary time series, are developed using functional principal component analysis (fPCA) and Synchrosqueezing. fPCA is applied in a new way, aggregating multiple financial time series to identify periods of...

We show that structural changes in stochastic volatility models induce spurious persistence. Other than in GARCH-type models, implied persistence does not tend to unity with given size of the structural change and increasing sample size.

This paper provides a regression approach to estimate tail dependence measures. The estimates coincide with the non-parametric estimates following Extreme Value Theory. The approach can easily be extended to higher dimensional analysis. We provide an example on international stock markets.