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Persistent link: https://www.econbiz.de/10010515583
We introduce a long memory autoregressive conditional Poisson (LMACP) model to model highly persistent time series of counts. The model is applied to forecast quoted bid-ask spreads, a key parameter in stock trading operations. It is shown that the LMACP nicely captures salient features of...
Persistent link: https://www.econbiz.de/10009229669
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models. We show that HF-based predictions yield a significantly lower portfolio volatility than methods employing daily …
Persistent link: https://www.econbiz.de/10009714536
Persistent link: https://www.econbiz.de/10010344462
autoregressive processes revealing time-varying stochastic volatility. The factor volatilities capture risk inherent to the term … additional determinants of future excess returns. Finally, we illustrate that the yield and volatility factors are closely …
Persistent link: https://www.econbiz.de/10014219528
been widely adopted in the context of volatility forecasting. In this work, we aim to bridge the conceptual gap between … from the previous week, yesterday and the day before, yesterday's volatility makes by far the most contribution to today …'s realized volatility forecast. Moroever, within the previous month, the importance of single weeks diminishes almost linearly …
Persistent link: https://www.econbiz.de/10013199338
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We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed on high frequencies, such as cumulated trading volumes or the time between potentially...
Persistent link: https://www.econbiz.de/10008748137
We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed on high frequencies, such as cumulated trading volumes or the time between potentially...
Persistent link: https://www.econbiz.de/10008749839