This paper provides an up-to-date survey of the main theoretical developments in ACD modeling and... more This paper provides an up-to-date survey of the main theoretical developments in ACD modeling and empirical studies using financial data. First, we discuss the properties of the standard ACD specification and its extensions, existing diagnostic tests, and joint models for the arrival times of events and some market characteristics. Then, we present the empirical applications of ACD models to different
Abstract This paper provides an up-to-date survey of the main theoretical developments in autoreg... more Abstract This paper provides an up-to-date survey of the main theoretical developments in autoregressive conditional duration (ACD) modeling and empirical studies using financial data. First, we discuss the properties of the standard ACD specification and its extensions, existing diagnostic tests, and joint models for the arrival times of events and some market characteristics. Then, we present the empirical applications of ACD models to different types of events, and identify possible directions for future research.
Tous droits réservés pour tous les pays. Toute traduction et toute reproduction sous quelque form... more Tous droits réservés pour tous les pays. Toute traduction et toute reproduction sous quelque forme que ce soit est interdite. Les textes publiés dans la série «Les Cahiers du CREF» de HEC Montréal n'engagent que la responsabilité de leurs auteurs. La publication de cette série de rapports de recherche bénéficie d'une subvention du programme de l'Initiative de la nouvelle économie (INE) du Conseil de recherches en sciences humaines du Canada (CRSH).
Engle and Russell's autoregressive conditional duration (ACD) models have been proven successful ... more Engle and Russell's autoregressive conditional duration (ACD) models have been proven successful in modelling financial data that arrive at irregular intervals. In practice, evaluating these models represents a crucial step. The spectral density is widely used in engineering and applied mathematics. Here, we advocate its use when testing for the so-called ACD effects, and for evaluating the adequacy of ACD models. Two classes of test statistics for duration clustering and one class of test statistics for the adequacy of ACD models are proposed. We adapt Hong's [Consistent testing for serial correlation of unknown form. Econometrica 1996;64:837-64; One-sided testing for conditional heteroskedasticity in time series models. Journal of Time SeriesAnalysis 1997;18:253-77] approach in the context of evaluating ACD models. In particular, we justify rigorously the asymptotic distributions, which are all standard normal, of the test statistics in the ACD framework. When testing for ACD effects, the second class of test statistics exploits the one-sided nature of the alternative hypothesis and we discuss in which circumstances these test statistics should be more powerful. Using a particular kernel function, the classes based on integrated measures provide generalized versions of the classical Box-Pierce/Ljung-Box test statistics, which are popular procedures among practitioners. However, we obtain more powerful test procedures in many situations, using nonuniform kernels. Important aspects of the paper are a simulation study illustrating the merits of the proposed procedures in the ACD context, and applications with financial data. ᭧ 131 trade process or the quote process such that the retained durations are characterized by a total traded volume of at least c. See Bauwens and Giot [3] for details.
The objective of this paper is to investigate the use of tick-by-tick data for market risk measur... more The objective of this paper is to investigate the use of tick-by-tick data for market risk measurement. We propose an Intraday Value at Risk (IVaR) at different horizons based on irregularly time-spaced high-frequency data by using an intraday Monte Carlo simulation. An UHF-GARCH model extending the framework of Engle is used to specify the joint density of the marked-point process of durations and high-frequency returns. We apply our methodology to transaction data for the Royal Bank and the Placer Dome stocks traded on the Toronto Stock Exchange. Results show that our approach constitutes reliable means of measuring intraday risk for traders who are very active on the market. The UHF-GARCH model performs well out-ofsample for almost all the time horizons and the confidence levels considered even when normality is assumed for the distribution of the error term, provided that intraday seasonality has been accounted for prior to the estimation.
The objective of this paper is to investigate the use of tick-by-tick data for market risk measur... more The objective of this paper is to investigate the use of tick-by-tick data for market risk measurement. We propose an Intraday Value at Risk (IVaR) at different horizons based on irregularly time-spaced high-frequency data by using an intraday Monte Carlo simulation. An UHF-GARCH model extending the framework of Engle is used to specify the joint density of the marked-point process of durations and high-frequency returns. We apply our methodology to transaction data for the Royal Bank and the Placer Dome stocks traded on the Toronto Stock Exchange. Results show that our approach constitutes reliable means of measuring intraday risk for traders who are very active on the market. The UHF-GARCH model performs well out-ofsample for almost all the time horizons and the confidence levels considered even when normality is assumed for the distribution of the error term, provided that intraday seasonality has been accounted for prior to the estimation.
This paper provides an up-to-date survey of the main theoretical developments in ACD modeling and... more This paper provides an up-to-date survey of the main theoretical developments in ACD modeling and empirical studies using financial data. First, we discuss the properties of the standard ACD specification and its extensions, existing diagnostic tests, and joint models for the arrival times of events and some market characteristics. Then, we present the empirical applications of ACD models to different
Abstract This paper provides an up-to-date survey of the main theoretical developments in autoreg... more Abstract This paper provides an up-to-date survey of the main theoretical developments in autoregressive conditional duration (ACD) modeling and empirical studies using financial data. First, we discuss the properties of the standard ACD specification and its extensions, existing diagnostic tests, and joint models for the arrival times of events and some market characteristics. Then, we present the empirical applications of ACD models to different types of events, and identify possible directions for future research.
Tous droits réservés pour tous les pays. Toute traduction et toute reproduction sous quelque form... more Tous droits réservés pour tous les pays. Toute traduction et toute reproduction sous quelque forme que ce soit est interdite. Les textes publiés dans la série «Les Cahiers du CREF» de HEC Montréal n'engagent que la responsabilité de leurs auteurs. La publication de cette série de rapports de recherche bénéficie d'une subvention du programme de l'Initiative de la nouvelle économie (INE) du Conseil de recherches en sciences humaines du Canada (CRSH).
Engle and Russell's autoregressive conditional duration (ACD) models have been proven successful ... more Engle and Russell's autoregressive conditional duration (ACD) models have been proven successful in modelling financial data that arrive at irregular intervals. In practice, evaluating these models represents a crucial step. The spectral density is widely used in engineering and applied mathematics. Here, we advocate its use when testing for the so-called ACD effects, and for evaluating the adequacy of ACD models. Two classes of test statistics for duration clustering and one class of test statistics for the adequacy of ACD models are proposed. We adapt Hong's [Consistent testing for serial correlation of unknown form. Econometrica 1996;64:837-64; One-sided testing for conditional heteroskedasticity in time series models. Journal of Time SeriesAnalysis 1997;18:253-77] approach in the context of evaluating ACD models. In particular, we justify rigorously the asymptotic distributions, which are all standard normal, of the test statistics in the ACD framework. When testing for ACD effects, the second class of test statistics exploits the one-sided nature of the alternative hypothesis and we discuss in which circumstances these test statistics should be more powerful. Using a particular kernel function, the classes based on integrated measures provide generalized versions of the classical Box-Pierce/Ljung-Box test statistics, which are popular procedures among practitioners. However, we obtain more powerful test procedures in many situations, using nonuniform kernels. Important aspects of the paper are a simulation study illustrating the merits of the proposed procedures in the ACD context, and applications with financial data. ᭧ 131 trade process or the quote process such that the retained durations are characterized by a total traded volume of at least c. See Bauwens and Giot [3] for details.
The objective of this paper is to investigate the use of tick-by-tick data for market risk measur... more The objective of this paper is to investigate the use of tick-by-tick data for market risk measurement. We propose an Intraday Value at Risk (IVaR) at different horizons based on irregularly time-spaced high-frequency data by using an intraday Monte Carlo simulation. An UHF-GARCH model extending the framework of Engle is used to specify the joint density of the marked-point process of durations and high-frequency returns. We apply our methodology to transaction data for the Royal Bank and the Placer Dome stocks traded on the Toronto Stock Exchange. Results show that our approach constitutes reliable means of measuring intraday risk for traders who are very active on the market. The UHF-GARCH model performs well out-ofsample for almost all the time horizons and the confidence levels considered even when normality is assumed for the distribution of the error term, provided that intraday seasonality has been accounted for prior to the estimation.
The objective of this paper is to investigate the use of tick-by-tick data for market risk measur... more The objective of this paper is to investigate the use of tick-by-tick data for market risk measurement. We propose an Intraday Value at Risk (IVaR) at different horizons based on irregularly time-spaced high-frequency data by using an intraday Monte Carlo simulation. An UHF-GARCH model extending the framework of Engle is used to specify the joint density of the marked-point process of durations and high-frequency returns. We apply our methodology to transaction data for the Royal Bank and the Placer Dome stocks traded on the Toronto Stock Exchange. Results show that our approach constitutes reliable means of measuring intraday risk for traders who are very active on the market. The UHF-GARCH model performs well out-ofsample for almost all the time horizons and the confidence levels considered even when normality is assumed for the distribution of the error term, provided that intraday seasonality has been accounted for prior to the estimation.
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Papers by Maria Pacurar