High frequency-based quantile forecast and combination: an application to oil market
From MaRDI portal
Publication:2086173
DOI10.1007/978-3-030-77094-5_19zbMath1495.62090OpenAlexW3202010848MaRDI QIDQ2086173
Publication date: 25 October 2022
Full work available at URL: https://doi.org/10.1007/978-3-030-77094-5_19
Uses Software
Cites Work
- MIDAS Regressions: Further Results and New Directions
- A multiple indicators model for volatility using intra-daily data
- Predicting volatility: getting the most out of return data sampled at different frequencies
- Dynamic quantile models
- Improving the value at risk forecasts: theory and evidence from the financial crisis
- Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes
- Do high-frequency measures of volatility improve forecasts of return distributions?
- Generalized autoregressive conditional heteroscedasticity
- Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
- Regression Quantiles
- Market Microstructure Invariance: Empirical Hypotheses
- Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
- Using CAViaR Models with Implied Volatility for Value‐at‐Risk Estimation
- Value-at-Risk Prediction: A Comparison of Alternative Strategies
- Strictly Proper Scoring Rules, Prediction, and Estimation
- Modeling and Forecasting Realized Volatility
- Extreme Value Theory as a Risk Management Tool
This page was built for publication: High frequency-based quantile forecast and combination: an application to oil market
