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...

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...

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...

This letter estimates the asymmetric influence of the production tax credit on wind energy production. I find that states with deregulated electricity markets were more responsive to the tax incentive than their regulated counterparts. Excluding any external benefits from wind production, this...

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...

There is a growing literature on the realized volatility (RV) forecasting of asset returns using high-frequency data. We explore the possibility of forecasting RV with factor analysis; once considering the significant jumps. A real high-frequency financial data application suggests that the...

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.

This paper presents a method helpful in analyzing the sources of return in an event study. A generalized decomposition result derived from the differential between two random linear functions attributes the effect of events or regulations on the value of firms to differences in economy-wide and...

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.