add R-Index (Replicability Index) - Schimmack 2014

[jaymon0703]

The R-Index by Schimack (2014) intends to penalize QRPs (Questionable Research Practices) and is a "doping test for science." We should be able to use the output from txnsim() to come up with our own version of the R-Index and in so doing add to the list of diagnostic tools available in blotter/quantstrat for determining luck vs skill or overfitting.

http://www.r-index.org/uploads/3/5/6/7/3567479/introduction_to_the_r-index__14-12-01.pdf

where

and

Statistical Power (or Success Rate) in Schimmack is defined as the LR probability of finding a significant result. From a large enough 'n' in txnsim() we could rely on the pvalues output of our strategy within the sampled distribution.

For Effect Size (or Inflation) we could rely on the effsize R package. This will require more research.

Below are more references that could prove useful, from the blog replicationindex.wordpress.com

• https://replicationindex.wordpress.com/2016/01/31/a-revised-introduction-to-the-r-index/
• https://replicationindex.wordpress.com/2015/04/01/meta-analysis-of-observed-power-comparison-of-estimation-methods/
• https://replicationindex.wordpress.com/2015/03/24/an-introduction-to-observed-power-based-on-yuan-and-maxwell-2005/
• https://replicationindex.wordpress.com/2016/01/14/on-the-definition-of-statistical-power/
• https://stackoverflow.blog/2017/10/17/power-calculations-p-values-ab-testing-stack-overflow/
• http://rpsychologist.com/d3/NHST/
• http://meera.snre.umich.edu/power-analysis-statistical-significance-effect-size