Showing 1 - 10 of 34
Summary We introduce an intuitive method of enhancing low-frequency volatility measures used to compute Value-at-Risk (VaR) by incorporating intradaily liquidity information from the limit order book. Using the quote slope of Hasbrouck and Seppi (2001), a compound liquidity measure comprising...
Persistent link: https://www.econbiz.de/10014609486
We introduce an intuitive method of enhancing low-frequency volatility measures used to compute Value-at-Risk (VaR) by incorporating intradaily liquidity information from the limit order book. Using the quote slope of Hasbrouck and Seppi (2001), a compound liquidity measure comprising the...
Persistent link: https://www.econbiz.de/10011278927
Persistent link: https://www.econbiz.de/10010428678
Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...
Persistent link: https://www.econbiz.de/10011730304
Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...
Persistent link: https://www.econbiz.de/10011674479
Large data sets in finance with millions of observations have becomewidely available. Such data sets enable the construction of reliablesemi-parametric estimates of the risk associated with extreme pricemovements. Our approach is based on semi-parametric statisticalextreme value analysis, and...
Persistent link: https://www.econbiz.de/10011299966
Persistent link: https://www.econbiz.de/10011339412
This paper applies a non- and a semiparametric copula-based approach to analyze the first-order autocorrelation of returns in high frequency financial time series. Using the EUREX D3047 tick data from the German stock index, it can be shown that the temporal dependence structure of price...
Persistent link: https://www.econbiz.de/10010265662
This paper analyses the long-memory properties of a high-frequency financial time series dataset. It focuses on temporal aggregation and other features of the data, and how they might affect the degree of dependence of the series. Fractional integration or I(d) models are estimated with a...
Persistent link: https://www.econbiz.de/10010293969
This paper analyses the long-memory properties of a high-frequency financial time series dataset. It focuses on temporal aggregation and other features of the data, and how they might affect the degree of dependence of the series. Fractional integration or I(d) models are estimated with a...
Persistent link: https://www.econbiz.de/10010293980