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the variance matrix. Monte Carlo evidence for parameter estimation based on different small sample sizes is provided. We …
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autoregressive conditional heteroskedasticity model and the dynamic conditional correlation model where distributional assumptions …
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We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...
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This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the … microstructure noise has an adverse effect on both spot variance estimation and jump detection. In our approach we can analyze high …
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We investigate the intraday dependence pattern between tick data of stock price changes using a new time-varying model for discrete copulas. We let parameters of both the marginal models and the copula vary over time using an observation driven autoregressive updating scheme based on the score...
Persistent link: https://www.econbiz.de/10013025960