ZIPGARCH-MIDAS、DDC-MIDAS模型MATLAB代码 1.12MB

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资源文件列表:

MIDASv2.4.zip 大约有39个文件
  1. MIDASv2.4/appADLMIDAS1.m 4.22KB
  2. MIDASv2.4/appADLMIDAS2.m 3.3KB
  3. MIDASv2.4/appADLMIDAS3.m 2.62KB
  4. MIDASv2.4/appADLMIDAS4.m 1.32KB
  5. MIDASv2.4/appDCCMIDAS1.m 3.7KB
  6. MIDASv2.4/appGARCHMIDAS1.m 3.4KB
  7. MIDASv2.4/appMidasQuantile1.m 1.13KB
  8. MIDASv2.4/DataQuantile.xlsx 84.94KB
  9. MIDASv2.4/DccMidas.m 36.03KB
  10. MIDASv2.4/DEXJPUS.xls 380.5KB
  11. MIDASv2.4/DGS10.xls 379.5KB
  12. MIDASv2.4/ForecastCombine.m 2.92KB
  13. MIDASv2.4/GarchMidas.m 33.29KB
  14. MIDASv2.4/INDPRO.xls 25KB
  15. MIDASv2.4/mfrvobj_adl.m 595B
  16. MIDASv2.4/MIDAS_ADL.m 30.48KB
  17. MIDASv2.4/MIDAS_Usersguide_V2.4.pdf 633.26KB
  18. MIDASv2.4/MidasQuantile.m 18.5KB
  19. MIDASv2.4/MixFreqData.m 14.61KB
  20. MIDASv2.4/mydata.xlsx 48.23KB
  21. MIDASv2.4/NASDAQCOM.xls 381.5KB
  22. MIDASv2.4/private/aicbic.m 232B
  23. MIDASv2.4/private/almon_adl_new.m 2.03KB
  24. MIDASv2.4/private/almon_weights.m 177B
  25. MIDASv2.4/private/bnls_adl_new.m 4.03KB
  26. MIDASv2.4/private/bnlsNN_adl_new.m 4.1KB
  27. MIDASv2.4/private/enls1_adl_new.m 3.65KB
  28. MIDASv2.4/private/HAC_kernel.m 501B
  29. MIDASv2.4/private/hessian.m 3.98KB
  30. MIDASv2.4/private/jacob.m 485B
  31. MIDASv2.4/private/midas_sf_adl_new.m 1.89KB
  32. MIDASv2.4/private/midas_X.m 4.22KB
  33. MIDASv2.4/private/ols.m 1.76KB
  34. MIDASv2.4/private/ssr_mfrvobj_adl.m 173B
  35. MIDASv2.4/private/var2struct.m 235B
  36. MIDASv2.4/Readme.txt 1.12KB
  37. MIDASv2.4/ssr_r25_adl_new.m 928B
  38. MIDASv2.4/ssr_r25_NN_adl_new.m 1.35KB
  39. license.txt 1.47KB

资源介绍:

2,4版 可以估计DCC-MIDAS adl-MIDAS DCC-GARCH
The mixed frequency regression studies the explanatory power of high frequency variables on the low frequency outcome. The weights associated with high frequency regressors are usually assumed some functional form. This toolbox is a repack of the Mi(xed) Da(ta) S(ampling) regressions (MIDAS) programs written by Eric Ghysels. It supports ADL-MIDAS type regressions. It also includes two functions for GARCH-MIDAS and DCC-MIDAS estimation Syntax: [...] = MIDAS_ADL(DataY,DataYdate,DataX,DataXdate) [...] = MIDAS_ADL(DataY,DataYdate,DataX,DataXdate,name,value,...) [...] = GarchMidas(y, name,value,...) [...] = DccMidas(Data, name,value,...) Version History v2.4 Add Legendre polynomial in MIDAS_ADL v2.1 Add MIDAS quantile regression v2.0 Add GARCH-MIDAS and DCC-MIDAS v1.1 Allow MIDAS leads and lags specification 'horizon' be negative. Add true out-of-sample forecast; results are restored in the last output argument 'Extended Forecast' struct. Report the approximated dates associated with the forecasted values in the output struct, in character instead of serial dates. v1.0 First release of the repacked MIDAS regression
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