发帖
雷达卡
1. Introduction; Revision on covariance, correlation and law of iterated expectations
2. White noise and other innovation series; Putting the tools to use; Autoregressive (AR) processes, Moving average (MA) processes, ARMA processes
3. Auto-covariance functions; Predictability and R2; Leaning outcomes; Sample examination questions
4. Predictability of asset return volatility; Autoregressive heteroscedasticity (ARCH) processes
5. Stationarity, moments, and restriction on parameters; Maximum likelihood estimation of GARCH models
6. Testing for volatility clustering; Leaning outcomes; Sample examination questions
7. Extensions of the univariate ARCH model
8. Choosing a volatility model
9. Multivariate volatility models
10. Introduction; Evaluating forecasts
11. Comparing forecasts; Forecast encompassing and combining
12. Introduction; Historical simulation; Weighted historical simulation
13. Models based on normal distribution; Models based on flexible distributions; Semi-parametric models
14. The conditional autoregressive Value at Risk (VaR) model; Leaning outcomes; Sample examination questions
15. Evaluating VaR forecasts
16. Comparing and combining VaR forecasts. Leaning outcomes; Sample examination questions
17. Modeling seasonality/diurnality
18. Modeling seasonality/diurnality (continued); Modeling durations
19. Modeling durations (continued)
Quantitative Finance.rar
(1.32 MB, 需要: 3 个论坛币)
本附件包括：- 8._QF_Chapter_10___11_(Lessons_20___21)_2013.pdf
- 1._QF_Chap_1___2_(Lessons_01_-_03)_2013.pdf
- 2._QF_Chapter_04_(Lessons_04_-_06)_2013.pdf
- 3._QF_Chapter_05_(Lessons_07_-_09)_2013.pdf
- 4._QF_Chapter_06_(Lessons_10_-_11)_2013.pdf
- 5._QF_Chapter_07_(Lessons_12_-_14)_2013.pdf
- 6._QF_Chapter_08_(Lessons_15_-_16)_2013.pdf
- 7._QF_Chapter_09_(Lessons_17_-_19)_2013.pdf
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