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We find stock portfolios with lower volatility & higher returns
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- We find portfolios of stocks that worked well together. Where the portfolio volatility was reduced because some stocks went up while others went down. These portfolios move with the market. Our model has been picking stocks with high BETA values and potential returns.
- This is a volatility minimization strategy that preserves your BETA exposure to market moves.
- The portfolio effects last up to 25 trading days.
Client Testimonials
Shamus Hurley (professional investor) December 2020
CEO | Board Member | Senior Advisor | Angel Investor | Startups, Private Investment & Family-Owned Corporations | Turnarounds & Transformations | Global Expansion | M&A
"I have had the good fortune (pun intended) of having Chicago Quantum conduct a series of runs on several of my portfolio stocks in service of learning how a CQNS better informs my long term trading thesis. Jeffrey has provided three CQNS models for me (where I provided guidance on rank prioritization on the stocks in the event of low trading or no data availability) and the results since Nov 30th (10 trading days out of 25 targeted in these CQNS models) on the top four stocks I used to test these scores (on actual trades) are: Stk1: 9.8%, Stk2: 10.2%, Stk3: 19.7%, Stk4: 54.1%. So while Chicago Quantum is not a financial advisor and does not provide any investing advice, they can help you learn (a lot) about any financial modeling or investing thesis you're using or considering. I'd recommend giving Jeffrey a call today and I will certainly be continuing to use CQNS modeling in concert with other models and approaches I use."
CEO | Board Member | Senior Advisor | Angel Investor | Startups, Private Investment & Family-Owned Corporations | Turnarounds & Transformations | Global Expansion | M&A
"I have had the good fortune (pun intended) of having Chicago Quantum conduct a series of runs on several of my portfolio stocks in service of learning how a CQNS better informs my long term trading thesis. Jeffrey has provided three CQNS models for me (where I provided guidance on rank prioritization on the stocks in the event of low trading or no data availability) and the results since Nov 30th (10 trading days out of 25 targeted in these CQNS models) on the top four stocks I used to test these scores (on actual trades) are: Stk1: 9.8%, Stk2: 10.2%, Stk3: 19.7%, Stk4: 54.1%. So while Chicago Quantum is not a financial advisor and does not provide any investing advice, they can help you learn (a lot) about any financial modeling or investing thesis you're using or considering. I'd recommend giving Jeffrey a call today and I will certainly be continuing to use CQNS modeling in concert with other models and approaches I use."
Ash Chopra, Lifefund Canada, October 2020
"My client and I engaged Chicago Quantum in September, 2020 to do a simple run (60 blue chip stocks with very little tech or growth oriented names) to help build out his "Quantum-enhanced Portfolio." Investing in just six of the selected stocks equally, the client's portfolio successfully achieved a return of 11.25%+ over 12 weeks; with less volatility and lower draw downs than major indices. The client is thrilled with the results."
"My client and I engaged Chicago Quantum in September, 2020 to do a simple run (60 blue chip stocks with very little tech or growth oriented names) to help build out his "Quantum-enhanced Portfolio." Investing in just six of the selected stocks equally, the client's portfolio successfully achieved a return of 11.25%+ over 12 weeks; with less volatility and lower draw downs than major indices. The client is thrilled with the results."
January 5, 2021 CQNS Run on 1,755 dividend paying stocks
Published publicly for free that morning. We will not trade this portfolio. Picked $WIT, $DHI, $SLGN & $KELYB)
Recent CQNS run on Dec 17, 2020 market close data
Recent CQNS results on Nov 30, 2020 Run: 4 stocks (2 pairs) selected
On Nov 30, 2020, before market open, the CQNS model selected a portfolio with $LPI, $PRTY, $SMLP and $FET. In a run on Dec 6, $SNDE was added by our analysis. As of December 9, 2020 (chart below), the CQNS portfolio did well on an absolute return basis and compared to benchmarks. On Dec 10, after another climb higher, we exited our positions with a 16% return after costs. We entered into positions on Nov 30, Dec 1 & Dec 7. Details here.
In our 3rd research article we pick $AX & $MCRB (Oct 9, 2020)
How did we do?
- In our 3rd research article we pick $AX and $MCRB (Oct 9 close)
- After 33 trading days (Oct 12 - Nov 25 3pm ET): $AX & $MCRB return an average +13.3% vs. $SPY +2.9 and $QQQ +0.7%
- One stock rises when the other falls...and both $QQQ and $SPY are straddled.
- This chart (from Oct 30) shows portfolios with offsetting moves while still delivering market performance or better.
- The 2nd chart (from Nov 25) shows $AX in the background, $MCRB in black, and $SPY & $QQQ in blue and yellow.
- $SPY is an ETF that tracks the S&P 500 index, and $QQQ is an ETF that tracks the NASDAQ 100 index.
Recently we picked only PDCE (October 20, 2020)
We selected PDC Energy, Inc. $PDCE as a buy for up to 25 trading days. We suggest it will have short-term volatility (up and down), but ultimately outperform the SPY & QQQ. It was a very successful call.
- One month later, $PDCE is up 22.76% vs. the S&P 500 $SPY up 5.02% and QQQ up 3.25%.
- After 26.5 trading days, $PDCE is +46.2% against SPY up 5.6% and QQQ up 4.2%.
- We also selected a 134 stock portfolio of 'all stars,' evenly weighted (not capitalization weighted) that should move as a group to minimize volatility while maintaining market exposure. This is a volatility reduction, return enhancement strategy.
"This week we select PDCE (PDC Energy, Inc.).
This stock alone has the best CQNS score. It is unusual for one stock to be selected."
This stock alone has the best CQNS score. It is unusual for one stock to be selected."
Results from October 20, 2020 through Nov 16, 2020 (14:54 CDT)
Results for PDCE vs. SPY and QQQ: Oct 20 - Nov 25 (intra-day)
We use quantum algorithms and quantum computers to pick stocks. Stocks to buy and stocks to trade.
We analyze the full search space. We also use non-quantum computers (e.g., servers and PCs).
We analyze the full search space. We also use non-quantum computers (e.g., servers and PCs).