Add to ORKGThe objective of this paper is to propose a market risk measure defined 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 finite sample properties through numerical Monte Carlo simulations. Finally, we propose an application to two NYSE stocks
This dissertation covers three topics in modeling and forecasting interval-valued time series.In Cha...
This paper proposes new approximate long-memory VaR models that incorporate intra-day price ranges. ...
Financial market activity via trade durations and price dynamics are investigated by means of ultra ...
The objective of this paper is to propose a market risk measure defined in price event time and a su...
The objective of this paper is to propose a market risk measure de\u85ned in price event time and a ...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
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...
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...
This paper proposes a new duration-based backtesting procedure for value-at-risk (VaR) forecasts. Th...
The thesis consists of three studies. The first two contribute to financial market risk modelling an...
Financial risk model evaluation or backtesting is a key part of the internal model’s approach to mar...
In this paper, we develop modeling tools to forecast Value-at-Risk and volatility with investment ho...
This study investigates the practical importance of several VaR modeling and forecasting issues in t...
This dissertation covers three topics in modeling and forecasting interval-valued time series.In Cha...
This paper proposes new approximate long-memory VaR models that incorporate intra-day price ranges. ...
Financial market activity via trade durations and price dynamics are investigated by means of ultra ...
The objective of this paper is to propose a market risk measure defined in price event time and a su...
The objective of this paper is to propose a market risk measure de\u85ned in price event time and a ...
In this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics...
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...
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...
This paper proposes a new duration-based backtesting procedure for value-at-risk (VaR) forecasts. Th...
The thesis consists of three studies. The first two contribute to financial market risk modelling an...
Financial risk model evaluation or backtesting is a key part of the internal model’s approach to mar...
In this paper, we develop modeling tools to forecast Value-at-Risk and volatility with investment ho...
This study investigates the practical importance of several VaR modeling and forecasting issues in t...
This dissertation covers three topics in modeling and forecasting interval-valued time series.In Cha...
This paper proposes new approximate long-memory VaR models that incorporate intra-day price ranges. ...
Financial market activity via trade durations and price dynamics are investigated by means of ultra ...