As we run our CQNS service more often, we do more targeted R&D (industrial engineering) on our algorithm & Chicago Quantum Net Score model.
We analyze two questions:
Q: Should we continue to use the SPY (S&P 500 ETF) as our benchmark for calculating BETA for use in calculating expected returns? How about QQQ (NASDAQ ETF)?
A: It does not seem to significantly impact the results. We ran BETAs against the QQQ last night and came up with similar portfolios (for a 64 stock portfolio) as when we used SPY. We may make this a parameter for clients, but it likely won't change much.
Q: Should we manually change CQNS_power from how we automatically calculate it today?
A: Not sure it matters much. The CQNS_Power is a way to balance risk and return in our runs, and it naturally changes with BETA values, market returns and market volatility. When we have changed this manually (in the past week), it has not made a significant difference.
How is the Simulated Bifurcation Machine working? Better each time we advance our tuning expertise. Two days ago we were able to use our bifurcator (custom coded) to find a very good portfolio of 64 stocks out of 4,000+ stocks. It yielded a CQNS score that was in the ballpark (not best, but good) with our best solvers on this run.
One interesting anecdote. When we are running 4,000+ stocks, things take much longer to run. Our tuning takes on more importance. For example, one of our genetic algorithm runs (this is one small part of our client analysis process) took 2,262 seconds to run and provide a deep and 'best' CQNS score, before we moved to phase 2 code and run on the quantum computer. There must be a way to do this more quickly (in this case, we could have eliminated 4 generations with hindsight). When we move to phase 2, and look at 64 stocks, we can run almost every solver to full explanatory power and not run out of time.
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.