• Corpus ID: 238419520

A Method for Predicting VaR by Aggregating Generalized Distributions Driven by the Dynamic Conditional Score

@inproceedings{Song2021AMF,
  title={A Method for Predicting VaR by Aggregating Generalized Distributions Driven by the Dynamic Conditional Score},
  author={Shijia Song and Handong Li},
  year={2021}
}
  • Shijia Song, Handong Li
  • Published 6 October 2021
  • Economics
Constructing a more effective value at risk (VaR) prediction model has long been a goal in financial risk management. In this paper, we propose a novel parametric approach and provide a standard paradigm to demonstrate the modeling. We establish a dynamic conditional score (DCS) model based on high-frequency data and a generalized distribution (GD), namely, the GD-DCS model, to improve the forecasts of daily VaR. The model assumes that intraday returns at different moments are independent of… 

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