Financial Risk Management with Bayesian Estimation of GARCH Models

By David Ardia. 2008

78 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4e4cf1e91852964ed44a4d74ba88460741aee6f4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Lennart F. Hoogerheide
2. H. V. Dijk
3. Maxime Rüede
4. Keven Bluteau
5. Richard Gerlach
6. Qi'an Chen
7. David Ardia

In Finance

1. Lennart F. Hoogerheide
2. H. V. Dijk
3. Maxime Rüede
4. Keven Bluteau
5. Richard Gerlach
6. Qi'an Chen
7. David Ardia

In Statistics and Probability

1. H. V. Dijk
2. Lennart F. Hoogerheide
3. Maxime Rüede
4. Keven Bluteau
5. Richard Gerlach
6. Qi'an Chen
7. David Ardia

Citations in the corpus

• The Two-sided Weibull Distribution and Forecasting Financial Tail Risk (2013, background): “For more details, see Chen et al. (2012) andGerlach and Chen (2008); or Ardia (2008) for alternative MCMC schemes for GARCHtype models.”
• Regime changes in Bitcoin GARCH volatility dynamics (2019, methodology): “Also, we note that for both the squared and absolute returns, the volatility persistence implied by the 6 Filtering the log–returns using an AR(p) model with p selected from AIC leads to similar results.”
• Bayesian Forecasting of Value at Risk and Expected Shortfall Using Adaptive Importance Sampling (2010, methodology): “Another alternative simulation method is to extend the approach of Nakatsuma (2000) for the case of Student-t innovations, see Ardia (2008).”