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:: Quasi Random-Walk Identification - Free Statistics Software (Calculator) ::

All rights reserved. The non-commercial (academic) use of this software is free of charge. The only thing that is asked in return is to cite this software when results are used in publications.

This free online software (calculator) computes the probability of (financial) Time Series being consitent with the Quasi Random-Walk based on the Bias-Reduced Logistic Regression Model [Firth, D. (1993) Bias reduction of maximum likelihood estimates. Biometrika 80, 27-38.]. The model uses the (large or small sample) Kurtosis p-value as the only exogenous variable.


If the probability is close to 1 then the (financial) time series under investigation is not consistent with the Efficient Market Hypothesis (c.q. Random-Walk) - hence it behaves like most 'real' financial stock market series (c.q. Quasi Random-Walk). Please, enter original financial time series (no transformation is required because this software computes log returns).

Enter (or paste) your data delimited by hard returns.

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Quasi Random-Walk Identification - Financial Time Series - Bias-Reduced Logistic Regression Model
Statistics of (1-B)lnY(t)Value
Kurtosis (small sample)1.959721
Kurtosis S.E. (small sample)0.417147
TEST 1 (small sample)4.697916
TEST 1 Prob. (small sample)0.000000
Quasi Random-Walk probability0.962935
Kurtosis (large sample)1.842043
Kurtosis S.E. (large sample)0.424795
TEST 1 (large sample)4.336306
TEST 1 Prob. (large sample)0.000000
Quasi Random-Walk probability0.962935





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Last computationDelete history
Server DateModuleCommand
Wed, 22 Feb 2017 10:40:00 +0000Quasi Random-Walk IdentificationPrint | Word | Excel | Blog this | Delete
Wed, 22 Feb 2017 10:40:00 +0000Start of session-
Top | Output | References | History | Feedback

To cite Wessa.net in publications use:
Wessa, P. (2017), Free Statistics Software, Office for Research Development and Education,
version 1.1.23-r7, URL http://www.wessa.net/

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Software Version : 1.1.23-r7
Algorithms & Software : Patrick Wessa, PhD
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