Chicago Quantum Net Score picks and results: Jan 21, 2021 market close
Jeffrey Cohen, President, US Advanced Computing Infrastructure, Inc.
Hello Chicago Quantum (SM) followers. About a year ago we developed a quantum algorithm, loosely based on the sharpe ratio, that picks attractive stock portfolios based on 1-year of historical pricing data. We run the algorithm on quantum computers from D-Wave Systems and/or on our own classical hardware.
We have two client testimonials here.
On Jan 21, 2021, after market close, we ran our model against NYSE, NASDAQ (Global Select & Global) and NYSEAmerican. We start with 3,486 stocks, and exit validation with 3,182 stocks. We ran three risk tolerances (this is not publicly available, but you can ask upon checkout).
These are the best picks (best CQNS score we found). We also share similar portfolios with slightly worse CQNS scores, as these are typically larger, or involve one new stock.
Medium risk: $AMRK & $SNDE (2nd best: $AMRK, $SNDE and $PDCE). This portfolio was up ~24.5% (assuming an equally weighted portfolio) vs a market index $SPY that was down 3.7%.
High risk: SNDE (2nd best: $FET & $SNDE). Using the same chart above, this portfolio (of one stock) was up 47% in the period, against $SPY that was down 3.7%.
Low risk: $AMRK, $CAG, $GIS, $HRL, $MMM & $WAT. At least with this portfolio you get your food groups. This portfolio did return +2.2% for the period and outperformed the $SPY, that was down -3.7% during the period. What is interesting in this set is the zig and zag you see at key points (1/25, 1/27 and on 1/29).
In summary, our model significantly outperformed the market during this turbulent time. Only time will tell how these results hold up. These results were after 6 trading days. We expect our model effects, which are based on 252 or 253 trading days data, to last from 25 to 35 trading days.
- High Risk: +47% vs. -3.7% baseline
- Medium Risk: + 24.5% vs. -3.7% baseline
- Low Risk: +2.2% vs. -3.7% baseline
Notes and Disclosures:
Over the past 3 months I have invested personal capital into some of our previous picks to better understand how the model works, how investors might trade these picks, and to live a ‘day in the life’ of our customers.
When we run the model for a paying client, we avoid conflict of interest by keeping those picks private, and only sharing them with the client. We will not run a model for our ‘house account’ on that day.
These picks were from days with no paid client runs. You can learn more about our firm and services here on our homepage.
By way of disclosure, I am long $SMLP in my personal brokerage account, and all other positions are held either in active hedge funds or passive, indexed mutual funds where I do not influence trading decisions.
We are not investment advisors, and this is not investment advice. Please do your own research and due diligence before investing. Investing in stocks can and does involve risks, and you can lose your entire investment.