Trading on non-public information has been very profitable in the past (and probably still is). Prominent insiders use their knowledge and share it with influential, wealthy institutional investors who earn money in an illegal way. And especially, options provide attractive leverage and relatively viable ways to “hide” sources of this illegal advantage. But after several big scandals, the resurgence of some forms of insider trading was stopped in 2009 after a trial with hedge fund superstar Raj Rajaratnam. The question is: What is the situation now?

Hello all,

What have we accomplished in the last month?

– A new Automatic Trading Edge Analysis report
– 9 new Quantpedia Premium strategies have been added to our database
– 10 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 9 new backtests written in QuantConnect code
– And finally, 2+4 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

Have you ever wondered if your trading asset trends or mean-reverts? Everyone involved in trading or investments daily solves the task of – What trading strategy should I apply to my assets to generate profits? As always, we at Quantpedia will try to help you a bit with this never-ending task with our new tool/report, which will be unveiled next week for all Quantpedia Pro subscribers. The following article serves as an introduction to the methodology we will use to find new trading edges for you automatically.

Passive index funds are believed to offer low fees, nearly limitless liquidity, very low trading costs and (most of the time) they beat most active managers. Although not all of the above are accurate, there are still many arguments in favour of passive indexing. However, what is often left forgotten are avoidable travails linked to index funds. In general, after an index rebalances, traditional cap-weighted index funds buy high and sell low. Their tendency to add recent highfliers and drop unloved value stocks is what causes investors to lose. Arnott et al. (2022) target the stock selection problem around index rebalancing and propose several ideas on how to adjust index strategies in order to earn above-market returns. They present simple ways to construct an index, thanks to which it is possible to reduce both negative effects of buy-high/sell-low dynamic and the turnover costs of cap-weighted indices.