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Recently several large volatility matrix estimation procedures have been developed for factor-based Ito processes whose integrated volatility matrix consists of low-rank and sparse matrices. Their performance depends on the accuracy of input volatility matrix estimators. When estimating...
Persistent link: https://www.econbiz.de/10012941597
Several novel large volatility matrix estimation methods have been developed based on the high-frequency financial data. They often employ the approximate factor model that leads to a low-rank plus sparse structure for the integrated volatility matrix and facilitates estimation of large...
Persistent link: https://www.econbiz.de/10012941598
The online Supplement presents the proof the auxiliary Lemmas 1-6, the entire set of tables with results from the Monte Carlo and the empirical studies, and further discussion on selected topics.Full paper is available at: 'https://ssrn.com/abstract=2707176' https://ssrn.com/abstract=2707176
Persistent link: https://www.econbiz.de/10012968328
We propose a new long-memory model with a time-varying fractional integration parameter, evolving non-linearly according to a Logistic Smooth Transition Autoregressive (LSTAR) specification. To estimate the time-varying fractional integration parameter, we implement a method based on the wavelet...
Persistent link: https://www.econbiz.de/10012968414
We develop a dynamic model to simultaneously characterize the liquidity demand and supply in limit order book. The joint dynamics is modelled in a unified Vector Functional AutoRegressive (VFAR) framework. We derive a closed-form maximum likelihood estimator under sieves and establish asymptotic...
Persistent link: https://www.econbiz.de/10012968564
We address the issue of modelling and forecasting macroeconomic variables using rich datasets by adopting the class of Vector Autoregressive Moving Average (VARMA) models. We overcome the estimation issue that arises with this class of models by implementing an iterative ordinary least squares...
Persistent link: https://www.econbiz.de/10012970411
In this paper, we provide non-parametric statistical tools to test stationarity of microstructure noise in general hidden Ito semimartingales, and discuss how to measure liquidity risk using high frequency financial data. In particular, we investigate the impact of non-stationary microstructure...
Persistent link: https://www.econbiz.de/10012970519
This paper introduces a method based on the use of various linear and nonlinear state space models that uses non-synchronous data to extract global stochastic financial trends (GST). These models are specifically constructed to take advantage of the intraday arrival of closing information coming...
Persistent link: https://www.econbiz.de/10012971773
This paper investigates the empirical properties of oil price and Stock market return volatilities using a range of univariate and multivariate GARCH models and monthly data from the U.S. The study relates the period August 1987 to October 2016, a total of 351 observations given. The aim of this...
Persistent link: https://www.econbiz.de/10012977192
We develop a generalized impulse response function for the fractionally integrated vector autoregressive (FIVAR) model using the Pesaran and Shin (1998) approach. Our method is different from the methodology shown in Chung (2001) since it does not require us to orthogonalize the error vector...
Persistent link: https://www.econbiz.de/10013008490