We propose a new method to implement the Business Time Sampling (BTS) scheme for high-frequency financial data. We compute a time-transformation (TT) function using the intraday integrated volatility estimated by a jump-robust method. The BTS transactions are obtained using the inverse of the TT...

We propose a new method to implement the Business Time Sampling (BTS) scheme for high-frequency financial data. We compute a time-transformation (TT) function using the intraday integrated volatility estimated by a jump-robust method. The BTS transactions are obtained using the inverse of the TT...

We apply the ACD-ICV method proposed by Tse and Yang (2011) for the estimation of intraday volatility to estimate monthly volatility, and empirically compare this method against the re- alized volatility (RV) and generalized autoregressive conditional heteroskedasticity (GARCH) methods. Our...

This paper implements the Asymmetric Autoregressive Conditional Duration (AACD) model of Bauwens and Giot (2003) to analyze irregularly spaced transaction data of trade direction, namely buy versus sell orders. We examine the influence of lagged transaction duration, lagged volume and lagged...

In the last decade, intensive studies on modeling high frequency financial data at the transaction level have been conducted. In the analysis of high-frequency duration data, it is often the first step to remove the intraday periodicity. Currently the most popular adjustment procedure is the...

In finance, durations between successive transactions are usually modelled by the autoregressive conditional duration model based on a continuous distribution omitting frequent zero values. Zero durations can be caused by either split transactions or independent transactions. We propose a...

In finance, durations between successive transactions are usually modelled by the autoregressive conditional duration model based on a continuous distribution omitting frequent zero values. Zero durations can be caused by either split transactions or independent transactions. We propose a...

In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics and high-frequency duration models) and non-parametric (empirical quantile, extreme distributions models) Value-at-Risk (VaR) techniques to intraday data for three stocks traded on the NewY ork...