Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Бэктестинг Value-at-Risk (VaR)× | Модель HAR-RV реализованной волатильности× | |
|---|---|---|
| Область | Финансы | Финансы |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1998 | 2009 |
| Автор метода≠ | Kupiec (1995); Christoffersen (1998); Engle & Manganelli (DQ test) | Fulvio Corsi |
| Тип≠ | Statistical hypothesis tests on VaR violation sequences | Linear time-series regression for volatility |
| Основополагающий источник≠ | Kupiec, P. H. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models. The Journal of Derivatives, 3(2), 73-84. DOI ↗ | Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗ |
| Другие названия≠ | VaR backtest, Kupiec test, Christoffersen test, Dynamic Quantile test | HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility) |
| Связанные≠ | 3 | 5 |
| Сводка≠ | VaR backtesting is a family of statistical tests that validate a risk model by comparing its Value-at-Risk forecasts against realised losses. It builds on Kupiec's (1995) unconditional coverage test, Christoffersen's (1998) conditional coverage test, and the Engle-Manganelli Dynamic Quantile (DQ) test. | The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility. |
| ScholarGateНабор данных ↗ |
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