Final Update: The top 10 CQNS-scoring stocks held together (equally weighted), outperforms the S&P 500 ETF ($SPY) by an alpha return of 9.7% after 9 trading days (12.8% vs. 3.1%),11.6% after 17 trading days, and 13% after 24 trading days (16.9% vs. 3.9%.).

Six of the ten stocks outperformed the $SPY during the 9-day period, while eight of ten outperformed the $SPY during the 17 day and 24 day periods. …


Updated (1): We usually pick stocks for clients that are good to invest in. They have less risk and more return potential over the coming 25 trading days. We call these ‘allstars’ and they are the most efficient stocks, and can be formed into the more efficient portfolios.

This week we are posting the most inefficient stocks, or the stocks with the most risk (or daily price volatility) relative to the expected return. Think of these as stocks ‘on a pogo stick’ that go up and down (can be exhausting to watch) but generally have little direction.

These stocks were…


Author: Jeffrey Cohen, President, Chicago Quantum, Update May 19, 2021

I attended the University of Chicago in the late 1980s in the economics department. We were taught inflation by a Nobel Prize winner in economics, Robert Lucas Jr., who spoke about Rational Expectations (often). He was a great professor who taught us a simple definition of inflation.

Inflation is a monetary issue, not a supply and demand issue.

Inflation is the growth rate of GNP — growth rate of money supply, or d(GNP)/d(M). Seemed easy, and in hindsight I used to check the WSJ and it would tie out historically…


Hello to our readers. Another efficient stock portfolio to publish three days after we ran it (for research & not for a client). We made an important math change, we lowered our annual risk-free rate from 1.0% to 0.6% to reflect what an individual investor could earn. We continue to have trouble with our data validation process (when it works, it works great…but lately it stopped being consistent). We are working this issue, and have removed our full exchange analysis offerings until corrected.

So, what was the run? 3,514 stocks that data validated down to 1,631 stocks that paid a…


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 11, 2021, after market close, we ran our model against NYSE, NASDAQ (Global Select & Global) and NYSEAmerican. We validate dividends, which means we exclude all stocks that have not paid a dividend during the measurement…


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. …


Updated Jan 31, 2021 with market results.

On January 4, 2021, after a down day in the US equity markets, I decided to do a ‘big run’ of our quantum algorithm against all US common stocks in four major exchanges. This included 3,569 stocks across NASDAQ (Q&G), NYSE and NYSEAmerican.

I was going to trade on this ‘in-house’ run but in a YouTube AMA this morning I disclosed the picks instead with a commitment to not take a position in any stocks listed for at least 24 hours. The Chicago Quantum Net Score (CQNS), which maximizes expected return (based on…


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…


Jeffrey Cohen, President US Advanced Computing Infrastructure, Inc. Chicago Quantum (SM)
Dec 7, 2020 1pm CT

A few updates to share on our run over this past weekend.

1. We include more shares in our analysis: (from ~3,250 to 4,529 US common shares on Dec 6, 2020). We analyze 4,529 stocks, perform data validation to remove missing or incomplete adjusted close prices, and extreme BETA(1-year vs. SPY ETF) values. We pass and analyze 4,163 US common stocks (up from 3,171 in our most recent publication). We made improvements and adjustments. We now include both NASDAQ Q and NASDAQ G stocks…


Jeffrey Cohen (jeffrey@quantum-usaci.com), Dec 2, 2020

Quick update Dec 4, 2020: Performance Update

Update Dec 10, 2020 (our trading results)

Good morning quantum computing and US equities readers. We have another ‘public’ stock pick (actually 2 pairs of stocks to hold), and a few updates on our quantum algorithm models for you. Not Earth-shattering, but possibly interesting for those who follow quantum computing in financial services.

This past weekend, with the markets closed, we downloaded all current US common stock tickers from the NYSE, NASDAQ Q, and NYSE American (tape b) which make up around 3,400 stocks. …

Chicago Quantum

Jeffrey Cohen, President, US Advanced Computing Infrastructure, Inc., & founder of Chicago Quantum (SM). We R&D and solve problems like portfolio optimization.

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