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Jeffrey Cohen, President, US Advanced Computing Infrastructure, Inc. Jan 20, 2021 For more information: jeffrey@quantum-usaci.com or 847.780.4401 (office) For those who follow Chicago Quantum, you know that we have focus on building a classical and quantum platform with a first use case of picking efficient stock portfolios. That platform is based on custom, classical solvers to solve the 'stock pickers problem' and uses quantum annealing. The proprietary algorithm runs as a quadratic, unconstrained, binary, optimization (QUBO) problem that we load into a matrix and solve in both classical and quantum hardware. Yesterday we ran the IBM Q Quantum Experience tutorial for portfolio optimization on IBM-provided simulators, classical solvers, and the real quantum computer called 'melbourne' which has 15 qubits, of which 14 are listed in the documentation and 13 appear functional at time of the experiment. This is the first time we have run portfolio optimization on a quantum computer. A few caveats before we get started and share what we learned:
 The picture above is from the IBM description of 'melbourne' in Github in the link above. Below we can see the frequency, in gigahertz, for the individual qubits in the 'melbourne' machine. We notice that there are 15 qubits, but one appears down, and another operating at a very low frequency. The connectivity between these qubits is about 2:1, and direction matters. Not all qubits have 2 'friends' in two directions.  Picture above is from the IBM Quantum Experience dashboard. This would imply that we have 13 functioning qubits to run our 8-stock analysis. It would also mean that the connectivity between 3, 8, and 12 with other qubit would be down, so long swaps (e.g., 8-9, 9-10, 10-11, 11-12, 12-13) would likely not function.  The picture above shows the actual error rates calculated for the qubits, and we can see the darker color for qubits 8 and 12, as highlighted above. The average CNOT error rate is 3.3%, with a range of 1.2% to 7.7%. As seen below, we have an average CNOT error rate of 3.3%, and an average readout error rate of 6.5%. Also, the decoherence times are measured by T1 and T2 at 53 and 62 micro-seconds respectively. So, we had better move fast and keep our logic chains short on this system at this time.  Since a stock picking problem (the way we code it) requires fully connected vertices, or cliques, we need extra steps (swaps) to connect qubits that are not hardware connected. This makes our quantum logic map, or circuit, relatively long, at 406 steps (in some steps there are more than one operations). This is followed by 8 read-out steps (as seen in the 3 pictures below).    This particular run, which took 46.4 minutes to run, gave us an answer that favored smaller portfolios than the optimal size of four. The best portfolio is stocks 2,5,7 & 8, and that answer was chosen with 0.195% probability (out of 100%). We downloaded the .CSV file (found here) and manually searched for it. The highest probability, 4.004%, was for zero stocks, or keeping your money in riskfree assets. 
 Our intuition for this is that after running 406 logical gates, or swaps of data, most of the qubits have a significant probability of losing their entanglement (or ability to keep an accurate value in memory before readout). This would mean our answers would have a significant chance of a 'bit-flip' or even a return to a ground-state of zero (or no stock). If the gates were applied equally, we still have 406 / 14 = 29 operations per qubit. This is a significant workload when the typical gate has an error probability that is significant (from 1% to 10%) for each logic and read step. Our take-away is that this particular answer is likely too random to give us actionable intelligence. We need to refine our models, logic, and approach to restructure the problem for gate-based computing. If we think the best answer will somehow 'shine through' the randomizing errors, then we should run the problem many times. However, at today's queue length and queue time, running about (31 to 57), and an average of ~45 minutes of queue-time per shot, and (7.0 to 7.5) seconds of run time, we would run out of time even if the first answer was the best one.  One way to get around the queue time is to use the 5-qubit machines which have smaller queues. Here is a list of the machines we have access to in the IBM Q Quantum Experience. The QV stands for quantum value, and is an indicator of workload throughput. Higher is better. It looks like there is a newer processor type, called the Canary r3. Maybe we should have used 'ibmq_athens' or 'ibmq_santiago' before IBMQ_16_melbourne?  This is the second of two BLOG posts. As stated in the first post, we placed our source code for this run in our public Github. You may find this code here.  We will continue to provide you updates as we make progress with gate-based computing. If you would like to purchase a stock analysis using our quantum algorithm and our quantum and classical platform, please check out our offerings here. To email the author: jeffrey@quantum-usaci.com. To call the author: 847.780.4401. Thank you for reading. Comments and feedback welcome. One-time stock analysis of your list of up to 100 stocks (long or efficient portfolios)
$150.00
You enter up to 100 stock tickers + 10 backup tickers. We run our analysis, select the best portfolio(s) based on our CQNS algorithm, and email you a .PDF report. Once you place your order, please provide this information during checkout (or email us):
Please email these to research@quantum-usaci.com. Jeffrey will be running your analysis. What we do: We run our analysis, select the best portfolio(s) based on our CQNS algorithm, and return you a .PDF report via email (or another way if you prefer). We return it within 24 hours...possibly much faster. The report will list the stocks you provided, results of data validation, and the best portfolio(s) we find. If our solvers do not converge on one 'best' portfolio, we will provide you the top 3 portfolios they find. We provide you any insights from the run (e.g., was it easy to find a 'best' portfolio). We wait until the trading day is over, but can use today's intraday price data. At this time, we only analyze stocks listed on US stock exchanges (no OTC or foreign listings). What you should expect from the results: This algorithm gives you the portfolio with the desired characteristics (lower risk & higher return) in the past year. We view this as a buy and hold strategy for up to 25 days, but have seen the effects last as long as 35 days. We have also 'swing traded' these results to capture short-term volatility. We have seen offsetting stocks in these portfolios where some rise while the others fall, but overall the portfolio rises. In a few cases, one 'high flyer' carries the portfolio. Why does this happen? If the BETA values selected are higher than market average, then the stocks may move more than the market. If the risk is lower for those stocks, and the BETA is higher, then we may see investors attracted to those stocks in the short-term. The value proposition: You can most likely re-create this logic and build the data analytics capability to do a similar exercise (e.g., using the Sharpe Ratio). However, it would take significant time and effort. We run this analysis every week, and have been performing this service consistently for over a year. We purchased new servers and computers, and built a set of algorithms, code, logic and proprietary solvers to find your CQNS portfolio. We also use D-Wave Systems Inc. technology and code, including sometimes their quantum annealing computers. With our pre-packaged service and expertise, we help you better understand the stocks in your list and achieve an actionable list quickly. Explanations: Please see our webpage "Stock Market Links & FAQs" for details. Disclosure We think investors need to do their own due diligence on the companies and ensure they understand the risks associated with investing. Our model looks at the adjusted closing prices and the patterns between stocks held in that data. Note: The algorithm and methods used are subject to frequent change and development. Do not rely on this service for your investment decisions, and do your due diligence. This is not investment advice. We are not investment advisors. Thank you for your order and your business. One-time stock analysis of complete stock exchanges (long or efficient portfolios)
$500.00 - $1,000.00
Are you looking to find common stocks portfolios that will outperform the market (according to the Chicago Quantum Net Score)? Want to find stocks expected to outperform the US equity market? You select up to five US stock exchanges for us to analyze all of their common stocks. You can choose from NYSE, NYSE American, NASDAQ Global, Nasdaq Capital Markets, and NASDAQ Global Select exchanges. We analyze all common stocks from the exchanges you select, usually after the markets close today, and we report our findings to you. The cost is $750, and it takes us up to 10 hours to run the analysis and write the report. We run the analysis using our new Dell server, our new iMacPro, we leverage our proprietary code and solvers (the platform), and possibly use the D-Wave Systems Quantum Annealer. Most of our clients pay for their analysis with their first trade. If you pick all 5 exchanges, we analyze ~4,600 stocks before data validation and ~3,600 after. We select an interim portfolio of ~100 stocks (selected to create the least efficient portfolio we can find of ~100 stocks). Finally, we analyze those ~100 stocks to find the best, most efficient 'long' portfolios we can. Recently we picked multiple 4-stock portfolios, plus a 13 and a 17 stock portfolio which when held together in an equally weighted portfolio, are expected to outperform the benchmarks (SPY & QQQ). Sometimes we pick smaller portfolios, depending on how the market is doing (the model picks them...we just report them). The holding of stocks together is what creates the value, as these stocks offset each other's risk, while maintaining the expected returns. Once you place your order, please enter this information during checkout or email us:
Please email these to research@quantum-usaci.com. Jeffrey will handle your order. We start work once we receive your email (or your provide this information through checkout), and our payment processor confirms payment (usually within minutes). We draft each report individually based on output from the multiple runs we perform, and our insights and experience from doing this. The programs themselves take between 4 and 10 hours to complete if you select the maximum number of exchanges (all 5). What we do: We run our analysis by selecting the most efficient (or best) portfolio(s) based on our Chicago Quantum Net Score (CQNS), based on the prior 1-year of adjusted close prices of all the common stocks that pass data validation. We then return you a .PDF report via email (or another way if you prefer) and return it within 24 hours, and possibly much faster. So far, we have 100% success in delivering our reports before markets open the next day. We are putting together a sample report. In the meantime: your report will include the five 'best' stock portfolios that we found, along with the interim portfolio of what we affectionately call 'allstars' (opposite of 'dogstars). This gives you ~100 stocks to research and take action on, after you do your due diligence of course. What usually happens? These stocks are a mix of high and low risk stocks that work well together. Their prices individually may move erratically, but that is compensated by a higher expected return. These stocks tend to risk over the next few days after we run our report, as these are the stocks that provide higher expected returns relative to risk. Please do your due diligence and understand the story behind these stocks. Why are the stock prices so stable? When we first started running this analysis for clients, the market in oil and gas stocks was flat because commodity prices were low. We selected a large number of stocks in that sector before they started to rise. With each run, we see both sector rotation, and stocks that have made their move start to be scored differently. Recently, MARA has been in our allstar portfolio. It is a crypto-currency based miner which ran up fiercely in the past, but lately has been very flat. The model says to hold this stock with others that move differently. We do provide some other screens on the stocks, depending on your level of interest. We can report out the highest paying dividend stocks in the market, or the stocks with the highest, lowest or negative BETA. We can let you know which stocks have HUGE volume spikes for one or a few days, then settled down again. We can also track stock splits and large one-day price moves. Each of these screens picks a few stocks that can be analyzed for action. We also provide a short analysis of the skewness, kurtosis and variance of the stocks that passed data validation. This is helpful for options traders. Typically, we wait to pull the data until the trading day is over, which ensures you have a clean set of price data. However, we can use today's intraday price data upon request. We only review US-listed stocks in this service. Foreign stocks will be a custom request, so please email us. What you should expect from the results: This algorithm gives you the portfolio with the highest amount of desired characteristics (lower risk relative to higher expected returns) in the past year. We expect those patterns to continue into the near future (average of 25 days). In our client runs, which have been going on for about a year, we generally see upward movement in the stocks selected, but the system is not perfect. Stocks can and do fall, even when picked by the Chicago Quantum Net Score. However, a trading model to use in upward markets is to 'swing trade' these results to capture short-term volatility and upward movements. The value proposition: We created pre-packaged solutions that allow us to continue investing (heavily) into a set of methods, tools, algorithms and our platform, so that we can better serve our clients in a repeatable manner. It is likely we are running this type of analysis often, so you get the benefit of our experience and growing expertise. The alternative is to pay on an hourly basis for a custom analysis, including the time for costing, testing and operations. This makes sense for clients that want to 'own' the analysis and have a very specific idea in mind of how they want to select stock portfolios. We welcome this business, and have a service on our website for weekly consulting work (for a fixed weekly fee). This algorithm is free from emotion, and provides a fact-base around the stock market and stocks that you may find valuable to trade to a plan. Finally, this is a proprietary algorithm (we published early versions of the algorithm to select efficient portfolios). We have also spent ~$10,000 on technology infrastructure and almost 18 months into the codebase. With our service, and expertise, we can help you achieve these results quickly and cost effectively. Explanations: Please see our webpage "Stock Market Links & FAQs" for details. Disclosure We think investors need to do their own due diligence on the companies and ensure they understand the risks associated with investing. Our model looks at the adjusted closing prices and the patterns between stocks held in that data. Note: The algorithm and methods used are subject to frequent change and development. Do not rely on this service for your investment decisions and do your own due diligence and research into companies. This is not investment advice. We are not investment advisors. Investments can and do lose money. Finally, if you prefer, please reach out to us at research@quantum-usaci and we can arrange a bulk order and typical business invoicing. This way nobody pays the 3% fee, and we can arrange runs on a fixed weekly schedule. Thank you for your order and your business. We expect you will learn a great deal in the process. Thank you for your order and your business. Consultation: Discussion of your stock analysis - deeper dive into CQNS & selections (30 minutes)
$100.00
You and I will have a discussion of the stocks that were picked in your run, a deeper dive into the Chicago Quantum Net Score algorithm, methodology, and results. We will also help you understand the valuations of the firms selected and special (if any) considerations with how the stocks traded over the past year. You may arrange this for after their stock market analysis to better understand the results and discuss implications and actions. Time permitting, I will build you a spreadsheet valuation of your chosen stock based on public filings (including debt). This will help you get a feel for 'the multiples' your stock, or stocks, are valued at by the market. Discussion to be scheduled and conducted as soon as practical, and can be within 1 hour if necessary. A typical, repeat client spend 3-4 hours a week on the phone with me, Jeffrey Cohen, President, Chicago Quantum, over a period of time to build rapport and common understanding of key stocks under analysis, and action. After payment, please text Jeffrey Cohen at +1.312.515.7333 or email him at jeffrey@quantum-usaci.com to schedule your consultation. One-time stock analysis of your list of up to 100 stocks (short or inefficient portfolios)
$150.00
Do you want to find the 'worst' or most inefficient stocks in your list? You enter up to 100 stock tickers and up to 10 backup tickers. We run our analysis, select the worst portfolio(s) based on our CQNS algorithm, and email you a .PDF report. You may have other options and comment boxes to complete during checkout, and you may request report delivery in other ways. Once you place your order, please email us your information:
Please email these to jeffrey@quantum-usaci.com and research@quantum-usaci.com Your payment confirmation comes from the payment processor. What we do: We run our analysis, select the worst portfolio(s) based on our CQNS algorithm, and return you a .PDF report via email (or another way if you prefer). We return it within 24 hours...possibly much faster. The report will list the stocks you provided, results of data validation, and the worst portfolio(s) we find. If our solvers do not converge on one 'worst' portfolio, we will provide you the bottom 3 portfolios they find. We provide you any insights from the run (e.g., was it easy to find a 'worst' portfolio). We wait until the trading day is over, but can use today's intraday price data if you ask. If you provide non-US listed stocks, we will include if the data is available via Yahoo Finance. What you should expect from the results: This algorithm gives you the portfolio with the least amount of desired characteristics (lower risk & higher return) in the past year. In fact, it gives the highest risk and lowest expected return combination. We view this as a short or put option strategy for up to 25 days. This is a new capability, and it seems to work for the first week of the call. We are not sure how long the effects will last, since stocks tend to take the stairs when they rise, but take the elevator when they fall. In our first client case, the three stocks picked reacted significantly in the first 3 days. This could be a 'swing traded' to capture short-term volatility. The model, as designed now, tends to pick one or two stocks. There is no benefit to diversification, this analysis picks the 'dogstars' and the worst performers we can find using a revision of the Chicago Quantum Net Score. The larger portfolios do not score as badly, as diversification helps with high risk, low expected return positions. If the BETA values selected are higher than market average, then the stocks may move more quickly than the market. If the risk is higher for those stocks, and the BETA is higher, then we may see investors selling those stocks in the short-term. The value proposition: You can ask us to provide you a service that is based on extensive model building, market research, computational intensity and creativity, and now, trading experience. It is independent of feelings and emotions and is based on market data and a unique quantum algorithm. This is a proprietary algorithm adjustment (we published the algorithm to select allstar, efficient portfolios). However, you can experiment to re-create this logic and build the data analytics capability to do a similar exercise (e.g., using the Sharpe Ratio). However, it would take significant time to learn and master. Mistakes are hard to discover and the data can be tricky to download and validate. Also, this is computationally difficult. With our service, and expertise, we can help you achieve these results quickly and cost effectively. Explanations: Please see our webpage "Stock Market Links & FAQs" for details on the financial markets and the computational solvers we use. Disclosure We think investors need to do their own due diligence on the companies and ensure they understand the risks associated with investing. Our model looks at the adjusted closing prices and the patterns between stocks held in that data. Note: The algorithm and methods used are subject to frequent change and development. Do not rely on this service for your investment decisions, and do your due diligence. This is not investment advice. We are not investment advisors. Thank you for your order and your business. One-time stock analysis of complete stock exchanges (long or efficient portfolios)
$500.00 - $1,000.00
Are you looking to find the worst stocks and portfolios (according to the Chicago Quantum Net Score)? Want to find stocks expected to underperform the US equity market? You select up to five US stock exchanges for us to analyze all of their common stocks. You can choose from NYSE, NYSE American, NASDAQ Global, Nasdaq Capital Markets, and NASDAQ Global Select exchanges. This service analyzes all common stocks from the exchanges you select, usually after the markets close today, and we report our findings to you. The cost is $750, and it takes us up to 10 hours to run the analysis and write the report! You get the benefit of our new Dell server, possibly the D-Wave Systems Quantum Annealer, and our proprietary code and solver platform, and D-Wave Systems classical solvers. It is a bargain price as we grow our business. If you pick all 5 exchanges, we analyze ~4,600 stocks before data validation and ~3,600 after. We select an interim portfolio of ~100 stocks (selected to create the least efficient portfolio we can find of ~100 stocks). Finally, we analyze those ~100 stocks to find the worst portfolios. Usually, there are 1 to 3 stocks selected, and a list of individual stocks to avoid, or bet against. Why, because diversification makes bad stocks better...so these are very small portfolios. Once you place your order, please enter this information during checkout or email us:
Please email these to research@quantum-usaci.com. Jeffrey will handle your order. We start work once we receive your email (or your provide this information through checkout), and our payment processor confirms payment (usually within minutes). We draft each report individually based on output from the multiple runs we perform, and our insights and experience from doing this. The programs themselves take between 4 and 10 hours to complete if you select the maximum number of exchanges (all 5). Fewer exchanges go faster, but it is up to you. What we do: We run our analysis by selecting the most inefficient (or worst) portfolio(s) based on our Chicago Quantum Net Score (CQNS), based on the prior 1-year of adjusted close prices of all the common stocks that pass data validation. We then return you a .PDF report via email (or another way if you prefer) and return it within 24 hours...possibly much faster. So far, we have 100% success in delivering our reports before markets open the next day. We are putting together a sample report. In the meantime: your report will include the five 'worst' stock portfolios that we found, along with the interim portfolio of what we affectionately call 'dogstars' (opposite of 'allstars). This gives you ~100 stocks to research and take action on, after you do your due diligence of course. What usually happens? These stocks are very risky. Their prices move erratically compared to their expected returns. So, we find that these stocks fall, and can fall fast when markets are weak. These stocks, however, can run up when markets are strong. So, do your due diligence and understand the story behind these stocks. When we first started running this analysis for clients, we selected a stock that was 3 months away from a bankruptcy filing. They did file for BK. Other stocks are MEME stocks that have been run up and down. Finally, others are in the healthcare space and have seem dramatic rises and falls based on news, or anomalous trading activity. Finally, some make no sense at all why they are trading at current levels (seem too high), and are just fun to watch or ride down. list the stocks that passed data validation and were analyzed, along with the most inefficient (or worst) portfolio(s) we found according to our Chicago Quantum Net Score. If our solvers do not converge on one 'worst' portfolio, we will provide you the bottom 3 portfolios found. We provide you any additional insights from the run. We also provide a short analysis of the skewness, kurtosis and variance of the stocks that passed data validation. We wait to pull the data until the trading day is over, which ensures you have a clean set of price data. However, we can use today's intraday price data upon request. If you provide non-US listed stocks, we will include if the data is available. What you should expect from the results: This algorithm gives you the portfolio with the lowest amount of desired characteristics (higher risk & lower expected return) in the past year. We expect those patterns to continue into the near future (average of 25 days). In our first client run, the declines have been significant (in a declining market) in the first few days. You can likely 'swing trade' these results to capture short-term volatility. We see a smaller number of stocks picked (one or two) in a portfolio, because diversification helps these 'dogstar' stocks. We will provide the interim portfolio of 100 stocks, and the final portfolios selected by the top solvers / methods. It is likely you may find a few 'dogstar' stocks from this analysis to take action on. Why does this happen? If we can find stocks with low BETA values and high variance, then these stocks do not move up with the market as much as others...and the higher variance means you likely will carry more risk for that expected return. The value proposition: We created pre-packaged solutions that allow us to continue investing (heavily) into a set of methods, tools, algorithms and our platform, so that we can better serve our clients in a repeatable manner. It is likely we are running this type of analysis often, so you get the benefit of our experience and growing expertise. The alternative is to pay on an hourly basis for a custom analysis, including the time for costing, testing and operations. This makes sense for clients that want to 'own' the analysis and have a very specific idea in mind of how they want to select stock portfolios. We welcome this business, and have a service on our website for weekly consulting work (for a fixed weekly fee). This algorithm is free from emotion, and provides a fact-base around the stock market and stocks that you may find valuable to trade to a plan. Finally, this is a proprietary algorithm (we published early versions of the algorithm to select efficient portfolios). We have also spent ~$10,000 on technology infrastructure and almost 18 months into the codebase. With our service, and expertise, we can help you achieve these results quickly and cost effectively. Explanations: Please see our webpage "Stock Market Links & FAQs" for details. Disclosure We think investors need to do their own due diligence on the companies and ensure they understand the risks associated with investing. Our model looks at the adjusted closing prices and the patterns between stocks held in that data. Note: The algorithm and methods used are subject to frequent change and development. Do not rely on this service for your investment decisions and do your own due diligence and research into companies. This is not investment advice. We are not investment advisors. Investments can and do lose money. Finally, if you prefer, please reach out to us at research@quantum-usaci and we can arrange a bulk order and typical business invoicing. This way nobody pays the 3% fee, and we can arrange runs on a fixed weekly schedule. Thank you for your order and your business. We expect you will learn a great deal in the process. One week of custom portfolio algorithm development & coding (quantum & classical)
$7,500.00
One of our senior team members (President or Associate) will code your algorithm ideas into quantum and classical algorithms for one week. One week is defined as a continuous 5 day period (e.g., Monday - Friday, or Saturday - Wednesday), with a 60 hour maximum (yes, 60 hours...because coding requires focus & time). The code and documentation we develop is yours to keep, to use and to sell. We apply our skills, experience, and knowledge of the D-Wave Systems quantum annealing computers as well as with coding and running classical solvers. We apply our domain expertise. We work with your team as requested. We can provide virtual training and mentorship while we code. We have experience in working with classical solvers such as: Monte Carlo Genetic Algorithm Simulated Annealer Simulated Bifurcator Particle Swarm Optimization TABU MultiStart We have experience working with the D-Wave Systems quantum annealing computers (Advantage 1.1 and 2000Q). One member of our current team has experience with gate-based computers (IBM Q). We will leverage your expertise in coding these if/when we work together with your development or trading teams. We are happy to work with you in your facility (safely due to Covid 19), work on video, or work remotely against your specifications. We work in Python in Jupyter Notebooks, and code our proprietary solvers into the notebooks, along with code to run the D-Wave Systems quantum annealing computers. You may want to software engineer that code afterwards so harden and speed up the models. You receive and own the code and documentation that we built upon payment for the time you have purchased. If you pay in advance (as you can with this website), you can request the code and documentation at any time. We act in a confidential manner for you. Our expertise has been sharpened with our focus on one optimization problem: US common stock portfolio optimization. We believe this expertise can be used to help solve other optimization problems.
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Jeff CohenStrategic IT Management Consultant with a strong interest in Quantum Computing. Consulting for 29 years and this looks as interesting as cloud computing was in 2010. Archives
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