KPSS

Install and import

bash

npm install fintech-algorithms

import { kpss } from "fintech-algorithms/statistical-time-series/diagnostics/kpss";

Signature

kpss(values, lags, criticalValue)

Worked example

executed Captured by running this function on the input its own test provides. Real output of real code — but not asserted against a published figure.

Input

values

[0.49366418, 1.54242291, -0.82556495, 0.47513288, 0.50704417, -0.3816439]

Showing 6 of 96 elements.

lags

criticalValue

0.463

Call

kpss(values, lags, criticalValue)

Returns

object with 13 fields: method, variant, nobs, lags, residual_mean, partial_sum_numerator, long_run_variance, covariance_terms, …

{
  "method": "kpss",
  "variant": "level-stationary-fixed-bartlett-bandwidth",
  "nobs": 96,
  "lags": 5,
  "residual_mean": -2.0816681711721685e-17,
  "partial_sum_numerator": 0.2446756917455388,
  "long_run_variance": 4.82902222159472,
  "covariance_terms": [
    {
      "lag": 1,
      "weight": 0.8333333333333334,
      "cross_product": 102.29629606088473
    },
    {
      "lag": 2,
      "weight": 0.6666666666666667,
      "cross_product": 67.86612357881646
    },
    {
      "lag": 3,
      "weight": 0.5,
      "cross_product": 43.864068660314665
    }
  ],
  "statistic": 0.05066775022309546,
  "critical_value": 0.463,
  "reject_null": false,
  "state": "fail-to-reject-level-stationarity",
  "reason": "statistic-not-above-boundary"
}

Other exports

This module also exports acf, pacf, adf, ljungBox, zivotAndrews, runDiagnostic. Every module additionally exports run as an alias of its primary function, and a meta object carrying its catalog id, domain, family, shape and article URL.

Diagrams

How it works

This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.

Read the article →

References

Testing the null hypothesis of stationarity against the alternative of a unit root
statsmodels.tsa.stattools.kpss
Evidence decisions