Holiday US Common Stock Picks using CQNS (Dec 18, 2020 pre-market)

We ran a quantum portfolio last Friday. Here are the US common stock portfolio results and R&D commentary.

This is not investment advice and is for informational purposes only. please do your own due diligence.

We run our Chicago Quantum Net Score (CQNS)(explanatory articles) for paying clients who either provide a set of tickers to optimize, or ask us to optimize a full stock exchange (NYSE, NASDAQ Q, NASDAQ G, NYSE American). We have two client testimonials (here). Our model picks portfolios of stocks with reduced risk and enhanced return characteristics, based on a prior year of stock price data.

We start usually with more than 3,000 stocks (which is a 2³⁰⁰⁰ search space), and narrow our search to either ~64 or ~134 stocks, which we then run on D-Wave Systems Quantum Annealing computers. At the end, we use heuristic search models to search for the best US common stock portfolios, then evaluate the best portfolio found by each solver type, including the quantum solver. This way, we get the benefit of many ‘good’ portfolios being analyzed together to find a few ‘great’ ones.

On December 17, 2020, we innovate and run our CQNS in four separate iterations to see if we could find a range of BETA exposures while still preserving the benefits of reduced portfolio volatility. In other words, could the CQNS find both higher-risk and lower risk portfolios with reduced volatility? Yes, it can and it does.

Our model contains a primary equation, which is risk minus return. We want these to be roughly equal, so we raise our expected return calculation to a power, which we call the CQNS Power. Our portfolios selected will be equal weight investments.

In our first run, we set the CQNS_power to favor high-BETA solutions. It choses two portfolios: (SNDE) and (FET, SNDE).

In our second run, we favor a more balanced solution. We select (AMRK, SNDE), and (PDCE, SNDE, TNDM)

In our third run, we favor a less risky solution. We select (AMRK, FORM, HUBS, and TNDM). We also have other solutions with very similar CQNS scores, in order of preference here: (AMRK, MKSI, TNDM), AMRK, AMS, CRUS, HUBS, TNDM), and (AMRK, AMS, CRUS, FORM and TNDM).

In our final run, we allow the ‘all-in’ portfolio to set the stage for the search, and here we see two portfolios: (PDCE, SNDE), and (FET, SNDE).

Daily performance of selected stocks (December 22, 2020)

These stocks are not performing well today, so we sit tight and see if the selected portfolios improve.


The author of this article is long TNDM, AMRK, SNDE and PDCE and entered those positions on December 18, 2020. This is not investment advice and we are not investment advisors, nor brokers. This is research into quantum computing and the use of quantum algorithms on both classical and quantum computing systems. Please do your own due diligence and research before investing.

For more information, please contact Jeffrey Cohen, President, US Advanced Computing Infrastructure, Inc.

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Jeffrey Cohen, President of US Advanced Computing Infrastructure, Inc., & founder of Chicago Quantum (SM). We use quantum algorithms & our quantum platform

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