Showing 1 - 7 of 7
We study the effects of trade duration properties on dependence in counts (number of transactions) and thus on dependence in volatility of returns. A return model is established to link counts and volatility. We present theorems as well as a conjecture relating properties of durations to long...
Persistent link: https://www.econbiz.de/10005556295
We study the modeling of large data sets of high frequency returns using a long memory stochastic volatility (LMSV) model. Issues pertaining to estimation and forecasting of large datasets using the LMSV model are studied in detail. Furthermore, a new method of de-seasonalizing the volatility in...
Persistent link: https://www.econbiz.de/10005556335
Standard predictive regressions produce biased coefficient estimates in small samples when the regressors are Gaussian first-order autoregressive with errors that are correlated with the error series of the dependent variable; see Stambaugh (1999) for the single-regressor model. This paper...
Persistent link: https://www.econbiz.de/10005556357
We consider processes with second order long range dependence resulting from heavy tailed durations. We refer to this phenomenon as duration- driven long range dependence (DDLRD), as opposed to the more widely studied linear long range dependence based on fractional differencing of an $iid$...
Persistent link: https://www.econbiz.de/10005407934
We consider a common components model for multivariate fractional cointegration, in which the s=1 components have different memory parameters. The cointegrating rank is allowed to exceed 1. The true cointegrating vectors can be decomposed into orthogonal fractional cointegrating subspaces such...
Persistent link: https://www.econbiz.de/10005407953
We consider semiparametric estimation of the memory parameter in a model which includes as special cases both the long-memory stochastic volatility (LMSV) and fractionally integrated exponential GARCH (FIEGARCH) models. Under our general model the logarithms of the squared returns can be...
Persistent link: https://www.econbiz.de/10005408005
We establish sufficient conditions on durations that are stationary with finite variance and memory parameter $d \in [0,1/2)$ to ensure that the corresponding counting process $N(t)$ satisfies $\textmd{Var} \, N(t) \sim C t^{2d+1}$ ($C0$) as $t \rightarrow \infty$, with the same memory parameter...
Persistent link: https://www.econbiz.de/10005119205