Add to ORKGThe objective of this paper is to propose a market risk measure de\u85ned in price event time and a suitable backtesting procedure for irregularly spaced data. Firstly, we combine Autoregressive Conditional Duration models for price movements and a non parametric quantile estimation to derive a semi-parametric Irregularly Spaced Intraday Value at Risk (ISIVaR) model. This ISIVaR measure gives two information: the expected duration for the next price event and the related VaR. Secondly, we use a GMM approach to develop a backtest and investigate its \u85nite sample properties through numerical Monte Carlo simulations. Finally, we propose an application to two NYSE stocks
Financial market activity via trade durations and price dynamics are investigated by means of ultra ...
Financial risk model evaluation or backtesting is a key part of the internal model’s approach to mar...
This paper proposes new approximate long-memory VaR models that incorporate intra-day price ranges. ...
The objective of this paper is to propose a market risk measure de\u85ned in price event time and a ...
The objective of this paper is to propose a market risk measure defined in price event time and a su...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
The thesis investigates topics on how to improve the estimation and forecasting for market risk mea...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
This paper proposes a new duration-based backtesting procedure for value-at-risk (VaR) forecasts. Th...
This paper proposes a new duration-based backtesting procedure for value-at-risk (VaR) forecasts. Th...
We propose a new model for transaction data that accounts jointly for the time duration between tran...
We investigate price duration based variance estimators that have long been ignored in the literatur...
The thesis consists of three studies. The first two contribute to financial market risk modelling an...
This dissertation covers three topics in modeling and forecasting interval-valued time series.In Cha...
This study investigates the practical importance of several VaR modeling and forecasting issues in t...
Financial market activity via trade durations and price dynamics are investigated by means of ultra ...
Financial risk model evaluation or backtesting is a key part of the internal model’s approach to mar...
This paper proposes new approximate long-memory VaR models that incorporate intra-day price ranges. ...
The objective of this paper is to propose a market risk measure de\u85ned in price event time and a ...
The objective of this paper is to propose a market risk measure defined in price event time and a su...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
The thesis investigates topics on how to improve the estimation and forecasting for market risk mea...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
This paper proposes a new duration-based backtesting procedure for value-at-risk (VaR) forecasts. Th...
This paper proposes a new duration-based backtesting procedure for value-at-risk (VaR) forecasts. Th...
We propose a new model for transaction data that accounts jointly for the time duration between tran...
We investigate price duration based variance estimators that have long been ignored in the literatur...
The thesis consists of three studies. The first two contribute to financial market risk modelling an...
This dissertation covers three topics in modeling and forecasting interval-valued time series.In Cha...
This study investigates the practical importance of several VaR modeling and forecasting issues in t...
Financial market activity via trade durations and price dynamics are investigated by means of ultra ...
Financial risk model evaluation or backtesting is a key part of the internal model’s approach to mar...
This paper proposes new approximate long-memory VaR models that incorporate intra-day price ranges. ...