Select efficient stock portfolio(s) from US stock market exchanges (Chicago Quantum Net Score)
SKU:
$750.00
$750.00
per item
You select up to four US stock exchanges for us to analyze all of their common stocks. You can choose from NYSE, NYSE American, NASDAQ Global and NASDAQ Global Select exchanges (about 3,500 common stocks before data validation). There are other options and comment boxes to complete (optionally) during checkout.
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 by selecting the most efficient 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.
The report will list the stocks that passed data validation and were analyzed, along with the most efficient portfolio(s) we found according to our Chicago Quantum Net Score. If our solvers do not converge on one 'best' portfolio, we will provide you the top 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 via Yahoo Finance.
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 expect those patterns to continue into the near future.
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. We call this 'zig and zag' in the portfolio. In the model runs that we have made (not for clients) and posted on Medium, we generally see an outperformance of the benchmarks (SPY and QQQ) over the first 25 - 35 trading days. In a few portfolios, 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 may be able to re-create this logic and build the data analytics capability to do a similar exercise (e.g., using the Sharpe Ratio or by reading our academic paper pre-prints). However, it will take significant time and expertise to learn and master. Mistakes are hard to discover and the data can be tricky to download and validate. With our service, and expertise, we can help you achieve these results quickly and cost effectively. We also provide excellent customer support and are patient (and passionate) in explaining the results and implications.
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. This is not investment advice. We are not investment advisors.
Thank you for your order and your business.
Once you place your order, please email us your information:
- Your name
- Your email address(es)
- Your phone (optional, in case we need to reach you)
- Any special requests
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 by selecting the most efficient 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.
The report will list the stocks that passed data validation and were analyzed, along with the most efficient portfolio(s) we found according to our Chicago Quantum Net Score. If our solvers do not converge on one 'best' portfolio, we will provide you the top 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 via Yahoo Finance.
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 expect those patterns to continue into the near future.
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. We call this 'zig and zag' in the portfolio. In the model runs that we have made (not for clients) and posted on Medium, we generally see an outperformance of the benchmarks (SPY and QQQ) over the first 25 - 35 trading days. In a few portfolios, 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 may be able to re-create this logic and build the data analytics capability to do a similar exercise (e.g., using the Sharpe Ratio or by reading our academic paper pre-prints). However, it will take significant time and expertise to learn and master. Mistakes are hard to discover and the data can be tricky to download and validate. With our service, and expertise, we can help you achieve these results quickly and cost effectively. We also provide excellent customer support and are patient (and passionate) in explaining the results and implications.
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. This is not investment advice. We are not investment advisors.
Thank you for your order and your business.