Multivariate Portmanteau (Ljung-Box) Test

Version 1.0.2 (15,3 ko) par Newport Quantitative
Test if there is auto- and cross correlation in a multivariate vector series
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Mise à jour 23 fév. 2019

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MLBQTEST(X,LAGS) performs multivariate Portmanteau test.

h = mlbqtest(X,LAGS) returns returns a logical value (h) for LAGS with the rejection decision from conducting a multivariate Portmanteau test for joint cross-correlation in a multivariate series X.

h = mlbqtest(X,LAGS,ALPHA) specifies the significance level (default=0.05).

[h,pValue] = mlbqtest(~) returns the rejection decision and p-value for the hypothesis test.

[h,pValue,stat,cValue] = mlbqtest(~) additionally returns the test statistic (stat) and critical value (cValue) for the hypothesis test.

Input argument X: a multivariate time-series (T x k) with k assets and T times.

Test null hypothesis H0: all correlation coefficients are zero, i.e.. rho_1=rho_2=...rho_m=0, where m the lag
Alternative hypothesis H1: there are some coefficients are not zero.

Citation pour cette source

Newport Quantitative (2024). Multivariate Portmanteau (Ljung-Box) Test (https://www.mathworks.com/matlabcentral/fileexchange/70365-multivariate-portmanteau-ljung-box-test), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2018b
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Version Publié le Notes de version
1.0.2

Enable customized degree of freedom
1.0.1

Upload needed function for multivariate cross correlation and demo
1.0.0