Merge branch 'develop' into ml_based_pairs_selection

hudson-and-thames · Nov 26, 2020 · 8a98d2e · 8a98d2e
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diff --git a/.bumpversion.cfg b/.bumpversion.cfg
@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.0.1
+current_version = 0.1.0
 commit = True
 tag = True
 tag_name = {new_version}

diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -13,7 +13,7 @@ jobs:
       - run:
           name: Run Pylint Check
           command: |
-            pylint arbitragelab --rcfile=.pylintrc -f text
+            pylint arbitragelab tests --rcfile=.pylintrc -f text
       - run:
           name: Run Unit Tests
           command: |

diff --git a/README.md b/README.md
@@ -30,4 +30,4 @@ The best place to contact the team is via the ArbitrageLab Slack channel. Altern
 Looking forward to hearing from you!
 
 ## License
-This project is licensed under an all rights reserved licence.
+This project is licensed under an all rights reserved [licence](https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html).
diff --git a/arbitragelab/__init__.py b/arbitragelab/__init__.py
@@ -1,3 +1,7 @@
+# Copyright 2019, Hudson and Thames Quantitative Research
+# All rights reserved
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
+
 """
 ArbitrageLab helps portfolio managers and traders who want to leverage the power of Statistical Arbitrage by providing
 reproducible, interpretable, and easy to use tools.

diff --git a/arbitragelab/codependence/codependence_matrix.py b/arbitragelab/codependence/codependence_matrix.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 This implementation lets user generate dependence and distance matrix based on the various methods of Information

diff --git a/arbitragelab/codependence/correlation.py b/arbitragelab/codependence/correlation.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 Correlation based distances and various modifications (angular, absolute, squared) described in Cornell lecture notes:

diff --git a/arbitragelab/codependence/gnpr_distance.py b/arbitragelab/codependence/gnpr_distance.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 Implementation of distance using the Generic Non-Parametric Representation approach from "Some contributions to the

diff --git a/arbitragelab/codependence/information.py b/arbitragelab/codependence/information.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 Implementations of mutual information (I) and variation of information (VI) codependence measures from Cornell

diff --git a/arbitragelab/codependence/optimal_transport.py b/arbitragelab/codependence/optimal_transport.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 Implementations of Optimal Copula Transport dependence measure proposed by Marti et al.: https://arxiv.org/abs/1610.09659

diff --git a/arbitragelab/cointegration_approach/base.py b/arbitragelab/cointegration_approach/base.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 Base class for cointegration approach in statistical arbitrage.

diff --git a/arbitragelab/cointegration_approach/engle_granger.py b/arbitragelab/cointegration_approach/engle_granger.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 This module implements Engle-Granger cointegration approach.

diff --git a/arbitragelab/cointegration_approach/johansen.py b/arbitragelab/cointegration_approach/johansen.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 This module implements the Johansen cointegration approach.

diff --git a/arbitragelab/cointegration_approach/signals.py b/arbitragelab/cointegration_approach/signals.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 Module for signal generation for Cointegration Approach.

diff --git a/arbitragelab/distance_approach/basic_distance_approach.py b/arbitragelab/distance_approach/basic_distance_approach.py
@@ -1,6 +1,7 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
+
 """
 Implementation of the statistical arbitrage distance approach proposed by
 Gatev, E., Goetzmann, W. N., and Rouwenhorst, K. G. in

diff --git a/arbitragelab/network/validation.py b/arbitragelab/network/validation.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 This module validates your API key. Please note that making changes to this file or any of the files in this library is

diff --git a/arbitragelab/optimal_mean_reversion/ou_model.py b/arbitragelab/optimal_mean_reversion/ou_model.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 # pylint: disable=missing-module-docstring, invalid-name, too-many-instance-attributes
 import warnings

diff --git a/arbitragelab/other_approaches/kalman_filter.py b/arbitragelab/other_approaches/kalman_filter.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 This module implements Kalman filter logic in statistical arbitrage trading. Kalman trading

diff --git a/arbitragelab/other_approaches/pca_approach.py b/arbitragelab/other_approaches/pca_approach.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 This module implements the PCA approach described by by Marco Avellaneda and Jeong-Hyun Lee in

diff --git a/arbitragelab/util/generate_dataset.py b/arbitragelab/util/generate_dataset.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 This module generates  synthetic classification dataset of INFORMED, REDUNDANT, and NOISE explanatory

diff --git a/docs/source/changelog.rst b/docs/source/changelog.rst
@@ -12,7 +12,7 @@ Changelog
 ..
     For Help: https://releases.readthedocs.io/en/latest/index.html
 
-
+* :release:`0.1.0 <2020-11-18>`
 * :feature:`2` Kalman Filter + Kalman strategy added.
 * :support:`2` Kalman Filter documentation.
 * :feature:`3` Landmark techniques: Engle Granger and Johansen tests for co-integration.

diff --git a/docs/source/codependence/codependence_marti.rst b/docs/source/codependence/codependence_marti.rst
@@ -231,4 +231,10 @@ The following research notebook can be used to better understand the codependenc
 
 * `Codependence by Marti`_
 
-.. _`Codependence by Marti`: https://github.com/Hudson-and-Thames-Clients/arbitrage_research/blob/master/Codependence%20Module/Codependence%20by%20Marti/codependence_by_marti.ipynb
+.. _`Codependence by Marti`: https://github.com/Hudson-and-Thames-Clients/arbitrage_research/blob/master/Codependence%20Module/Codependence%20by%20Marti/codependence_by_marti.ipynb
+
+References
+##########
+
+* `Marti, G., 2017. Some contributions to the clustering of financial time series and applications to credit default swaps (Doctoral dissertation, Université Paris-Saclay (ComUE)). <https://www.researchgate.net/publication/322714557_Some_contributions_to_the_clustering_of_financial_time_series_and_applications_to_credit_default_swaps>`__
+* `Marti Gautier, 2020. Measuring non-linear dependence with Optimal Transport. Available at personal blog. <https://gmarti.gitlab.io/qfin/2020/06/25/copula-optimal-transport-dependence.html>`__
diff --git a/docs/source/codependence/correlation_based_metrics.rst b/docs/source/codependence/correlation_based_metrics.rst
@@ -261,3 +261,12 @@ The following examples show how the described above correlation-based metrics ca
 
     # Calculate the Norm distance between two correlation matrices
     dist = norm_distance(corr_18, corr_19)
+
+References
+##########
+* `De Prado, M.L., 2016. Building diversified portfolios that outperform out of sample. The Journal of Portfolio Management, 42(4), pp.59-69. <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2708678>`__
+* `De Prado, M.L., 2020. Codependence (Presentation Slides). Available at SSRN 3512994. <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3512994>`__
+* `Johnson, D. and Sinanovic, S., 2001. Symmetrizing the kullback-leibler distance. IEEE Transactions on Information Theory. <https://scholarship.rice.edu/bitstream/handle/1911/19969/Joh2001Mar1Symmetrizi.PDF?sequence=1>`__
+* `Newton, M.A., 2010. Introducing the discussion paper by Szekely and Rizzo. arXiv preprint arXiv:1010.3575. <https://arxiv.org/pdf/1010.3575>`__
+* `Székely, G.J., Rizzo, M.L. and Bakirov, N.K., 2007. Measuring and testing dependence by correlation of distances. The annals of statistics, 35(6), pp.2769-2794. <https://projecteuclid.org/download/pdfview_1/euclid.aos/1201012979>`__
+* `Tumminello, M., Lillo, F. and Mantegna, R.N., 2007. Kullback-Leibler distance as a measure of the information filtered from multivariate data. Physical Review E, 76(3), p.031123. <https://arxiv.org/pdf/0706.0168>`__
diff --git a/docs/source/codependence/information_theory_metrics.rst b/docs/source/codependence/information_theory_metrics.rst
@@ -77,7 +77,7 @@ It can also be normalized using a known upper boundary:
 
 An alternative way of estimating the Mutual information is through using copulas.
 A link between Mutual information and copula entropy was presented in the paper by
-`Ma, Jian & Sun, Zengqi. (2008). Mutual information is copula entropy <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3512994>`_.
+`Ma, Jian & Sun, Zengqi. (2008). Mutual information is copula entropy <https://ieeexplore.ieee.org/iel5/5971803/6077925/06077935.pdf>`_.
 
 `A blog post by Gautier Marti <https://gmarti.gitlab.io/qfin/2020/07/01/mutual-information-is-copula-entropy.html>`_
 includes descriptions of two alternative estimators of copula entropy:
@@ -283,3 +283,12 @@ The following example highlights how the various metrics behave under various va
    :alt: No Relationship
 
    Indepedent
+
+References
+##########
+
+* `De Prado, M.L., 2020. Codependence (Presentation Slides). Available at SSRN 3512994. <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3512994>`__
+* `Hacine-Gharbi, A., Ravier, P., Harba, R. and Mohamadi, T., 2012. Low bias histogram-based estimation of mutual information for feature selection. Pattern Recognition Letters, 33(10), pp.1302-1308. <https://www.researchgate.net/publication/257014935_Low_bias_histogram-based_estimation_of_mutual_information_for_feature_selection>`__
+* `Hacine-Gharbi, A. and Ravier, P., 2018. A binning formula of bi-histogram for joint entropy estimation using mean square error minimization. Pattern Recognition Letters, 101, pp.21-28. <https://www.researchgate.net/publication/320887281_A_binning_formula_of_bi-histogram_for_joint_entropy_estimation_using_mean_square_error_minimization>`__
+* `Ma, J. and Sun, Z., 2011. Mutual information is copula entropy. Tsinghua Science & Technology, 16(1), pp.51-54. <https://ieeexplore.ieee.org/iel5/5971803/6077925/06077935.pdf>`__
+* `Marti Gautier, 2020. Mutual Information Is Copula Entropy. Available at personal blog. <https://gmarti.gitlab.io/qfin/2020/07/01/mutual-information-is-copula-entropy.html>`__
diff --git a/docs/source/codependence/introduction.rst b/docs/source/codependence/introduction.rst
@@ -4,9 +4,9 @@
 Introduction
 ============
 
-This module includes implementations of codependence metrics. According to Lopez de Prado:
+This module includes implementations of codependence metrics.
 
-"Two random variables are codependent when knowing the value of one helps us determine the value of the other.
+According to Lopez de Prado: "Two random variables are codependent when knowing the value of one helps us determine the value of the other.
 This should not be confounded with the notion of causality."
 
 Pearson correlation coefficient is the most famous and widely used measure of codependence, however, it has some drawbacks.

diff --git a/docs/source/codependence/optimal_transport.rst b/docs/source/codependence/optimal_transport.rst
@@ -250,4 +250,10 @@ The following research notebook can be used to better understand the optimal cop
 
 * `Optimal Transport`_
 
-.. _`Optimal Transport`: https://github.com/Hudson-and-Thames-Clients/arbitrage_research/blob/master/Codependence%20Module/Optimal%20Transport/optimal_transport.ipynb
+.. _`Optimal Transport`: https://github.com/Hudson-and-Thames-Clients/arbitrage_research/blob/master/Codependence%20Module/Optimal%20Transport/optimal_transport.ipynb
+
+References
+##########
+
+* `Marti, G., Andler, S., Nielsen, F. and Donnat, P., 2017, February. Exploring and measuring non-linear correlations: Copulas, Lightspeed Transportation and Clustering. In NIPS 2016 Time Series Workshop (pp. 59-69). <https://arxiv.org/pdf/1610.09659.pdf>`__
+* `Marti Gautier, 2020. Measuring non-linear dependence with Optimal Transport. Available at personal blog. <https://gmarti.gitlab.io/qfin/2020/06/25/copula-optimal-transport-dependence.html>`__
diff --git a/docs/source/cointegration_approach/trading_strategies.rst b/docs/source/cointegration_approach/trading_strategies.rst
@@ -4,7 +4,12 @@
 Trading Strategies
 ==================
 
-The following are some strategies for trading the spread.These descriptions closely follow the book by Ernest P. Chan: `Algorithmic Trading: Winning Strategies and Their Rationale <https://www.wiley.com/en-us/Algorithmic+Trading%3A+Winning+Strategies+and+Their+Rationale-p-9781118460146>`__.
+The following are some strategies for trading the spread.
+
+.. note::
+   These descriptions closely follow the book by Ernest P. Chan:
+   `Algorithmic Trading: Winning Strategies and Their Rationale <https://www.wiley.com/en-us/Algorithmic+Trading%3A+Winning+Strategies+and+Their+Rationale-p-9781118460146>`__.
+
 
 Linear Trading Strategy
 #######################

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -22,7 +22,7 @@
 author = 'Hudson & Thames Quantitative Research'
 
 # The full version, including alpha/beta/rc tags
-release = '0.0.1'
+release = '0.1.0'
 
 
 # -- General configuration ---------------------------------------------------

diff --git a/docs/source/getting_started/installation.rst b/docs/source/getting_started/installation.rst
@@ -80,7 +80,7 @@ Accept all the requests to install.
 
    .. code-block::
 
-      pip install git+https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@github.com/hudson-and-thames/arbitragelab.git@master
+      pip install git+https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@github.com/hudson-and-thames/arbitragelab.git@0.1.0
 
 .. tip::
 
@@ -146,7 +146,7 @@ Accept all the requests to install.
 
    .. code-block::
 
-      pip install git+https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@github.com/hudson-and-thames/arbitragelab.git@master
+      pip install git+https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@github.com/hudson-and-thames/arbitragelab.git@0.1.0
 
 .. tip::
 
@@ -208,7 +208,7 @@ Windows
 
    .. code-block::
 
-      pip install git+https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@github.com/hudson-and-thames/arbitragelab.git@master
+      pip install git+https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@github.com/hudson-and-thames/arbitragelab.git@0.1.0
 
 .. tip::
 

diff --git a/docs/source/optimal_mean_reversion/ou_model.rst b/docs/source/optimal_mean_reversion/ou_model.rst
@@ -609,3 +609,8 @@ The following research notebook can be used to better understand the concepts of
 * `Trading Under the Ornstein-Uhlenbeck Model`_
 
 .. _`Trading Under the Ornstein-Uhlenbeck Model`: https://github.com/Hudson-and-Thames-Clients/arbitrage_research/blob/master/Optimal%20Mean%20Reversion/ou_model.ipynb
+
+References
+##########
+
+1. `Leung, T.S.T. and Li, X., 2015. Optimal mean reversion trading: Mathematical analysis and practical applications (Vol. 1). World Scientific. <https://www.amazon.co.uk/Optimal-Mean-Reversion-Trading-Mathematical/dp/9814725919/>`__
diff --git a/requirements.txt b/requirements.txt
@@ -14,6 +14,8 @@ lxml==4.5.2
 requests_html==0.10.0
 
 #Develop
+bump2version==1.0.1
+bumpversion==0.6.0
 codecov==2.0.15
 coverage==4.5.2
 pylint==2.5.3

diff --git a/setup.cfg b/setup.cfg
@@ -1,6 +1,6 @@
 [metadata]
 name = arbitragelab
-version = 0.0.1
+version = 0.1.0
 author = Hudson and Thames Quantitative Research
 author_email = research@hudsonthames.org
 licence = All Rights Reserved

diff --git a/setup.py b/setup.py
@@ -14,3 +14,5 @@
 
 # Bump version
 # bumpversion major/minor/patch --allow-dirty
+# git push origin [0.1.0]
+
diff --git a/tests/test_basic_distance_approach.py b/tests/test_basic_distance_approach.py
@@ -1,6 +1,7 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
+
 """
 Tests the basic distance approach from the Distance Approach module of ArbitrageLab.
 """

diff --git a/tests/test_codependence.py b/tests/test_codependence.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 Test functions from codependence module.
@@ -11,9 +11,9 @@
 import pandas as pd
 
 from arbitragelab.codependence.correlation import (squared_angular_distance, angular_distance, absolute_angular_distance,
-                                               distance_correlation, kullback_leibler_distance, norm_distance)
+                                                   distance_correlation, kullback_leibler_distance, norm_distance)
 from arbitragelab.codependence.information import (get_mutual_info, variation_of_information_score,
-                                               get_optimal_number_of_bins)
+                                                   get_optimal_number_of_bins)
 from arbitragelab.codependence.codependence_matrix import (get_dependence_matrix, get_distance_matrix)
 from arbitragelab.codependence.gnpr_distance import (spearmans_rho, gpr_distance, gnpr_distance)
 from arbitragelab.codependence.optimal_transport import optimal_transport_dependence

diff --git a/tests/test_kalman_filter.py b/tests/test_kalman_filter.py
@@ -1,6 +1,7 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
+
 """
 Tests the Kalman Filter Strategy from the Other Approaches module.
 """

diff --git a/tests/test_mean_reversion.py b/tests/test_mean_reversion.py
@@ -1,6 +1,7 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
+
 """
 Tests function of Statistical Arbitrage Cointegration module:
 cointegration_approach/base.py, engle_granger.py, johansen.py, signals.py

diff --git a/tests/test_ou_model.py b/tests/test_ou_model.py
@@ -1,6 +1,6 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
 
 """
 Test functions from the OU-model of the Optimal Mean Reversion module.

diff --git a/tests/test_pca_approach.py b/tests/test_pca_approach.py
@@ -1,6 +1,7 @@
 # Copyright 2019, Hudson and Thames Quantitative Research
 # All rights reserved
-# Read more: https://github.com/hudson-and-thames/mlfinlab/blob/master/LICENSE.txt
+# Read more: https://hudson-and-thames-arbitragelab.readthedocs-hosted.com/en/latest/additional_information/license.html
+
 """
 Tests the PCA Strategy from the Other Approaches module.
 """