Change Logs

Changes since 4.0

  • Added FixedVariance volatility process which allows pre-specified variances to be used with a mean model. This has been added to allow so-called zig-zag estimation where a mean model is estimated with a fixed variance, and then a variance model is estimated on the residuals using a ZeroMean variance process.
  • Fixed a bug that prevented fix from being used with a new model (GH156)
  • Added first_obs and last_obs parameters to fix to mimic fit

Changes since 3.0

  • Added forecast code for mean forecasting
  • Added volatility hedgehog plot
  • Added fix to arch models which allows for user specified parameters instead of estimated parameters.
  • Added Hansen’s Skew T distribution to distribution (Stanislav Khrapov)
  • Updated IPython notebooks to latest IPython version
  • Bug and typo fixes to IPython notebooks
  • Changed MCS to give a pvalue of 1.0 to best model. Previously was NaN
  • Removed hold_back and last_obs from model initialization and to fit method to simplify estimating a model over alternative samples (e.g., rolling window estimation)
  • Redefined hold_back to only accept integers so that is simply defined the number of observations held back. This number is now held out of the sample irrespective of the value of first_obs.

Changes since 2.1

  • Added multiple comparison procedures
  • Typographical and other small changes

Changes since 2.0

  • Add unit root tests: * Augmented Dickey-Fuller * Dickey-Fuller GLS * Phillips-Perron * KPSS * Variance Ratio
  • Removed deprecated locations for ARCH modeling functions

Changes since 1.0

  • Refactored to move the univariate routines to arch.univariate and added deprecation warnings in the old locations
  • Enable numba jit compilation in the python recursions
  • Added a bootstrap framework, which will be used in future versions. The bootstrap framework is general purpose and can be used via high-level functions such as conf_int or cov, or as a low level iterator using bootstrap