# MFE Toolbox

The Oxford MFE Toolbox is the follow on to the UCSD_GARCH toolbox. It has been widely used by students here at Oxford, and represents a substantial improvement in robustness over the original UCSD GARCH code, although in its current form it only contains univariate routines.

### Current Version¶

The latest version, including any work in progress, can be downloaded on the GitHub repository for the MFE Toolbox (Direct link to zip).

#### Last Updated¶

June 7, 2013

#### Update News¶

Many changes have occurred since the last release. The most notable are:

- A major rework of the subsampling in the Realized code
- Modern versions of BEKK (Scalar, Diagonal and Full) and RARCH, a recent model by Diaa Noureldin, Neil Sheppard and me.
- DCC, BEKK and HEAVY are all finally available in this toolbox, and so the retirement of the UCSD GARCH toolbox is almost ready.
- OGARCH and GOGARCH have been added.
- RCC, an alternative to DCC, is also available (by Diaa Noureldin, Neil Sheppard and Kevin Sheppard).

The next developments should include the TODO include:

- SARIMA
- Clean up of unused files and more coherent naming

### Code¶

### Documentation¶

Oxford MFE Toolbox Documentation

### High Level List of Functions¶

- Regression
- ARMA Simulation
- ARMA Estimation
- Heterogeneous Autoregression
- Information Criteria

- ARMA Forecasting
- Sample autocorrelation and partial autocorrelation
- Theoretical autocorrelation and partial autocorrelation
- Testing for serial correlation
- Ljung-BoxQ Statistic
- LM Serial Correlation Test

- Filtering
- Baxter-King Filtering
- Hodrick-Prescott Filtering

- Regression with Time Series Data
- Long-run Covariance Estimation
- Newey-West covariance estimation
- Den Hann-Levin covariance estimation

- Nonstationary Time Series
- Unit Root Testing
- Augmented Dickey-Fuller testing
- Augmented Dickey-Fuller testing with automated lag selection

- Vector Autoregressions
- Granger Causality Testing: grangercause
- Impulse Response function calculation

- Volatility Modeling
- ARCH/GARCH/AVARCH/TARCH/ZARCH Simulation
- EGARCH Simulation
- APARCH Simulation
- FIGARCH Simulation

- GARCH Model Estimation
- ARCH/GARCH/GJR-GARCH/TARCH/AVGARCH/ZARCH Estimation
- EGARCH Estimation
- APARCH Estimation
- AGARCH and NAGARCH estimation
- IGARCH estimation
- FIGARCH estimation
- HEAVY models

- Density Estimation
- Kernel Density Estimation

- Distributional Fit Testing
- Jarque-Bera Test
- Kolmogorov-Smirnov Test
- Berkowitz Test

- Bootstraps
- Block Bootstrap
- Stationary Bootstrap

- Multiple Hypothesis Tests
- Reality Check and Test for Superior Predictive Accuracy
- Model Confidence Set

- Multaivariate GARCH
- CCC MVGARCH
- Scalar Variance Targetting VECH
- MATRIX GARCH
- DCC and ADCC
- OGARCH
- GOGARCH
- RARCH

- Realized Measures
- Realized Variance
- Realized Covariance
- Realized Kernels
- Multivariate Realized Kernels
- Realized Quantile Variance
- Two-scale Realized Variance
- Multi-scale Realized Variance
- Realized Range
- QMLE Realized Variance
- Min Realized Variance, Median Realized Variance (MinRV, MedRV)
- Integrated Quarticity Estimation

#### Functions Missing from Previous UCSD GARCH Toolbox¶

The following list of function have not been updated and so if needed, you should continue to use the UCSD GARCH code.

- GARCH in mean
- IDCC MVGARCH
- Shapirowilks
- Shapirofrancia