Quantpedia as an Inspiration
We have a new video featuring three examples of how to built new strategies on top of ideas from Quantpedia’s database. We hope you will like it …
We have a new video featuring three examples of how to built new strategies on top of ideas from Quantpedia’s database. We hope you will like it …
We have prepared several new announcements, but first, let us recapitulate last month of Quantpedia’s research. Nine new Quantpedia Premium strategies have been added into our database, and eleven new related research papers have been included in existing Premium strategies during last month.
Additionally, we have produced 12 new backtests written in QuantConnect code. Our database currently contains over 350 strategies with out-of-sample backtests/codes.
Also, five new blog posts, that you may find interesting, have been published on our Quantpedia blog:
Once again, welcome to our summary of Quantpedia’s research. Ten new Quantpedia Premium strategies have been added into our database, and eleven new related research papers have been included in existing Premium strategies during last month.
Additionally, we have produced 15 new backtests written in QuantConnect code. Our database currently contains over 340 strategies with out-of-sample backtests/codes.
Also, four new blog posts, that you may find interesting, have been published on our Quantpedia blog:
The presidential campaign is becoming hotter as we are moving closer to this year’s election. But we still have enough time to dig deeper into data about the past elections and prepare for autumn. Therefore, we have prepared a short video recapitulation of our paper on the pre-election drift.
The best course of action for every quant researcher is to try to fundamentally understand anomalies and explore their functioning besides the original scope of the academic research papers. The goal of this article was to look for inspiration and further explore the Skewness affect – the tendency of assets with the lowest skewness to outperform assets with the highest skewness. It seems that this anomaly is present not only in commodities but also in currencies, fixed income and equities. Trading strategy that exploits the effect of skewness in the multi-asset setting would earn an annual return of 7.67% when leveraged to the 15% volatility.
Some companies have relatively more of their value in near-term cash flow (for ex. General Motors Corporation). Others (for ex. Tesla), are growth stocks, with a greater proportion of their market value based on long-term expected future cash flow. It seems that coronavirus pandemic has hit mainly the first group, the “low equity duration” companies. A new academic research paper written by Dechow, Erhard, Sloan, and Soliman explains how the equity duration factor can be used to assess how are companies exposed to short-term unexpected macroeconomic events (like COVID-19 pandemic), and how equity duration sensitivity can also explain relative underperformance of value vs growth stocks during the last bear market.
Authors: Dechow, Patricia and Erhard, Ryan and Sloan, Richard G. and Soliman, Mark T.
Title: Implied Equity Duration: A Measure of Pandemic Shutdown Risk