Quantpedia’s Research in 2023
Dear readers & clients,
As we celebrate the dawn of another year, it’s a great occasion to reflect on Quantpedia’s journey in the previous 12 months. While 2023 certainly had its own share of challenges, luckily, the movements in financial markets were not as seismic as during the events that unfolded in 2022. As always, I am really proud of my whole team for their work as we continue fulfilling our primary mission to process academic research related to quant & algo trading to a more user-friendly form.
So, what are the main highlights?
– We have again enlarged our database, currently to over 950 trading strategies, produced over 100 out-of-sample backtests (and now we have over 730 of them, with over 450 of them periodically updated)
– Other public ventures included the continuation of our Youtube series Quantpedia Explains Trading Strategies (with over 50 new videos), an update of our lists of tools for quant traders (mainly for historical data, but also for algo trading discounts for our readers), again a lot of public blogs and countless of our own research articles
– In spring 2023, we launched a new Quantpedia Prime offering that serves as the “light” version of Quantpedia Premium and Pro tiers. It is tailored mainly to individual systematic investors, advisors, and quants at the beginning of their learning path. Users got access to a subset of Quantpedia Premium trading strategies (~100) that are easier to execute and understand (mainly tactical asset allocation, simple market timing, and seasonality strategies), plus access to essential modeling tools (Portfolio Manager) and a few Quantpedia Pro reports.
– We have also continued to build our Quantpedia Pro offering. Over the year, we performed a technical upgrade of the Portfolio Manager, and users can now create/store/manage multiple model portfolios and benchmarks. We also expanded its capabilities to over 40 reports, with new additions like Strategy Grading, Alpha Analysis, Component Analysis, Technical Analysis, and Rebalancing Analysis.
– We are actively keeping a close watch on the developments in artificial intelligence and how it can be applied in the trading field. We published multiple short reviews of the current state of the technology in the last year. We concluded with the launch of our own Quantpedia chatbot, which has been trained on our database of Quantpedia strategies. It’s not the last endeavor, and we have some more surprises ready for the upcoming year.
– Plus, there is one more surprise that we prepared for all of you for the year 2024. I am not telling you what it is at the moment as the full announcement will be made in about two weeks. But I will let you guess 🙂
Happy New Year 2024 and profitable trading …
Yours,
Radovan Vojtko & Team of Quantpedia.com
PS: If you are looking for a few more articles to read, as usual, here is the list of previous month’s blog posts, that you may find interesting:
Cyber Risk and the Cross-Section of Stock Returns
Authors: Daniel Celeny and Loïc Maréchal
Title: Cyber risk and the cross-section of stock returns
What’s the FED Perspective on Inflation Surprises and Equity Returns
Authors: Antonio Gil de Rubio Cruz, Emilio Osambela, Berardino Palazzo, Francisco Palomino, and Gustavo Suarez
Title: Inflation Surprises and Equity Returns
Top Ten Blog Posts on Quantpedia in 2023
Author: Radovan Vojtko
Title: Top Ten Blog Posts on Quantpedia in 2023
Why Do US Stocks Outperform EM and EAFE Regions?
Author: Cyril Dujava
Title: Why Do US Stocks Outperform EM and EAFE Regions?
Are you looking for more strategies to read about? Visit our Blog or Screener.
Do you want to learn more about Quantpedia Pro service? Check its description, watch videos, review reporting capabilities and visit our pricing offer.
Do you want to know more about us? Check how Quantpedia works and our mission.
Are you looking for historical data or backtesting platforms? Check our list of Algo Trading Discounts.
Or follow us on:
Facebook Group, Facebook Page, Twitter, Linkedin, Medium or Youtube
Share onLinkedInTwitterFacebookRefer to a friend