In this article, we play with our relationship risk tool that tracks potentially fraudulent officers as they moved to other companies. Our conclusion is that our tool helps you find shortselling investments or reduce left tail risk.
In order to compare returns of companies exposed to different levels of fraud risk, we first had to address the issue of data. There was no dataset providing insight on officers past history with frauds.
To address the issue, we created those networks by compiling fraud events and linking events to individuals.
The below chart shows companies with different fraud risk rankings that we compile.
We provide the full list of companies with their rankings so that you can focus on the companies with highest links to fraudulent events.
Below is a standard single company search. The small blue dots are the Officers linked to our database of frauds and other malfeasance events. The companies featuring in the fraud database are represented by black dots.
By running a ticker search into our platform, you can identify the individuals linked to malpractice events. You can view it in the graph, or in the table with more details into the allegations and timelines.
Back testing performance
We create 2 model portfolios.
The high risk portfolio comprises companies with a relationship risk score of 10 and more.
The low risk portfolio comprises companies with a score of 0, meaning no links to our fraud database.
We then compared the distribution of returns on those portfolios over time. We chose a 12 month period. Below is the smoothed return distribution.
It seems that portfolios with companies linked to questionable or fraudulent companies have higher left tail risk.
Want to work with us on analytics? We are looking for collaborators and partners to address Investment research issues. Don' t hesitate to get in touch with us. See our contact page.