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This repository includes the scripts to replicate results of my paper entitled "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices".

hkalager/dfdr

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dfdr

This code is prepared for the article titled "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices" published in the Journal of International Financial Markets, Institutions and Money.

You can access the article at https://doi.org/10.1016/j.intfin.2021.101353

Please cite the article as "Sermpinis, G., Hassanniakalager, A., Stasinakis, C. and Psaradellis, I., 2021. Technical Analysis Profitability and Persistence: A Discrete False Discovery Approach on MSCI Indices. Journal of International Financial Markets, Institutions and Money, p.101353"

Dataset:

The data for MSCI indices are collected from Bloomberg Terminal. All indices are denoted in US Dollar. You are not allowed to access/use the data files without a valid license for Bloomberg.

Third-part scripts: Part of the codes are from borrowed from "Bajgrowicz, P. and Scaillet, O., 2012. Technical trading revisited: False discoveries, persistence tests, and transaction costs. Journal of Financial Economics, 106(3), pp.473-491." https://doi.org/10.1016/j.jfineco.2012.06.001

Further information:

The Discrete Right Boundary function is based on "Liang, K., 2016. False discovery rate estimation for large‐scale homogeneous discrete p‐values. Biometrics, 72(2), pp.639-648." https://doi.org/10.1111/biom.12429

The codes here are provided as is. Subject to change at all time.

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This repository includes the scripts to replicate results of my paper entitled "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices".

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