Showing 1 - 10 of 42
Persistent link: https://www.econbiz.de/10013256626
The asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in...
Persistent link: https://www.econbiz.de/10011303289
This paper proposes a parsimoniously time varying parameter vector autoregressive model (with exogenous variables, VARX) and studies the properties of the Lasso and adaptive Lasso as estimators of this model. The parameters of the model are assumed to follow parsimonious random walks, where...
Persistent link: https://www.econbiz.de/10010433901
generally, to observation-driven models, which include well-known models for conditional volatility. To overcome the problem of … Monte Carlo study and an empirical study concerning the measurement of conditional volatility from financial returns data. …
Persistent link: https://www.econbiz.de/10011794421
Persistent link: https://www.econbiz.de/10009708735
Persistent link: https://www.econbiz.de/10000961545
Persistent link: https://www.econbiz.de/10003913191
We revisit Wintenberger (2013) on the continuous invertibility of the EGARCH(1,1) model. We note that the definition of continuous invertibility adopted in Wintenberger (2013) may not always be sufficient to deliver strong consistency of the QMLE. We also take the opportunity to provide other...
Persistent link: https://www.econbiz.de/10011401308
the Efficient Method of Moments implemented to estimatestochastic volatility models this will surely be the case … method of momentstechnique for a broad range of univariate stochastic volatility models. As a side effect of the … volatility models. It describes the program. Some examples are given from other workof the author. Technicalities are given in …
Persistent link: https://www.econbiz.de/10010533201
Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled … oflow probability worst outcomes, RiskMetrics analysis underpredicts the VaR while historical simulationoverpredicts the VaR …. However, the estimates obtained from applying the semi-parametric method aremore accurate in the VaR prediction. In addition …
Persistent link: https://www.econbiz.de/10010533206