arch_test perform a Lagrange Multiplier (LM) test of thenull hypothesis of no conditional heteroscedascity against the alternative of CH(P) arch_test(Y,X,P) PVAL = arch_test(Y,X,P) [PVAL, LM]= arch_test(Y,X,P) P: Degrees of freedom PVAL: PVAL is the p-value (1 minus the CDF of this distribution at LM) of the test perform a Lagrange Multiplier (LM) test of thenull hypothesis of no conditional heteroscedascity against the alternative of CH(P). I.e., the model is y(t) = b(1) * x(t,1) + ... + b(k) * x(t,k) + e(t), given Y up to t-1 and X up to t, e(t) is N(0, h(t)) with h(t) = v + a(1) * e(t-1)^2 + ... + a(p) *e(t-p)^2, and the null is a(1) == ... == a(p) == 0. If the second argument is a scalar integer, k,perform the sametest in a linear autoregression model of orderk, i.e., with [1, y(t-1), ..., y(t-K)] as the t-th row of X. Under the null, LM approximatel has a chisquare distribution with P degrees of freedom and PVAL is the p-value (1 minus the CDF of this distribution at LM) of the test. If no output argument is given, the p-value is displayed.