Hello and good morning,
On Monday August 3, 2020 we published the results of our first 'published' portfolios. Our 'ideal' CQNS portfolio delivered 13% returns over the 3 week measurement period vs. 4% for the benchmark.
As a reminder, we are selecting from a set of 60 liquid, US equities. We created a Python script so we can test these 5 portfolios anytime.
The best, optimal 60 asset portfolio according to CQNS was two stocks, AMP (Ameriprise) and APA (Apache). Those two stocks returned 13% during the measurement period. This compares favorably to the benchmarks of all 60 stocks, and the S&P 500 during the period.
Our two generalized portfolios produced by the quantum annealing computer, which were selected to pick the highest CQNS, with a high CQR, and the highest CQR, with a high CQNS, did not perform as well as the benchmark of 60 stocks they were chosen from.
As a disclosure, we have not taken positions in any of the portfolios mentioned in this research.
Our goal is to complete our 60 asset engineering (*we have 8 items left), and publish another article (preprint) on arXiv in August 2020. After that, we will scale up again to evaluate more assets at a time.
Jeffrey Cohen, founder of Chicago Quantum and President, US Advanced Computing Infrastructure, Inc. August 4, 2020. For more information, please see the detailed articles (in the buttons below):
Over 100 registered, 71 joined, and 32 stayed for the full 2 hours. Very active discussion.
We choose two stock portfolios from our quantum annealing computer results. We run on July 10, 2020, 4pm CT data and develop our model for picking stock portfolios based on those results.
Read about it here:
Please download and read our paper on the arXiv. https://arxiv.org/abs/2007.01430
Portfolio Optimization of 40 Stocks Using the D-Wave Quantum AnnealerJeffrey Cohen, Alex Khan, Clark Alexander
Abstract: We investigate the use of quantum computers for building a portfolio out of a universe of U.S. listed, liquid equities that contains an optimal set of stocks. Starting from historical market data, we look at various problem formulations on the D-Wave Systems Inc. D-Wave 2000Q(TM) System (hereafter called DWave) to find the optimal risk vs return portfolio; an optimized portfolio based on the Markowitz formulation and the Sharpe ratio, a simplified Chicago Quantum Ratio (CQR), then a new Chicago Quantum Net Score (CQNS). We approach this first classically, then by our new method on DWave. Our results show that practitioners can use a DWave to select attractive portfolios out of 40 U.S. liquid equities.
Strategic 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.