Jeffrey Cohen, US Advanced Computing Infrastructure, Inc.
September 7, 2023
Conclusion, if we run our model only against profitable, low debt leverage company common stocks, we can find only 3 ticks of edge or alpha as compared to 21 ticks when we look at the whole universe of US listed stocks. In short, we lose the edge from quantitative analysis if we stick to lower risk stocks.
We run a quantitative model called the Chicago Quantum Net Score. It looks for long stock portfolios with a better risk-return trade off than the large passive US stock indices. It runs for a long time, crunches significant amounts of data, does serious number crunching, and uses advanced solver heuristics. It sometimes runs on a quantum computer, just to see what happens.
We ran the model last night on September 6, 2023 in two versions. Thank you to our market data services provider, Intrinio, for providing us excellent, professional end of day data, along with historical financial information at high speed. There are some timing issues, as some of the historical data reflects prior periods (not sure the lag, but maybe up to a year).
One version allows for all common stocks of US listed companies. We just opened up the data validation and we end up with 3,017 stocks that traded every day for the past year with a minimum volume of 20,000 shares and a positive BETA.
The other version was more picky. Out of that group of 3,017 stocks we further require stocks to make a profit, have a positive common equity, and have debt that is a reasonable multiple of earnings. In short, these are the profitable, and lower risk stocks.
The 'all stock' version found long stock portfolios of between 2 and 11 stocks, and the best portfolios had between 20 and 21 ticks of edge, or alpha. Holding all 3,017 stocks, or holding the SPY, QQQ or IWM both have zero edges.
The 'profitable stock' version found long stock portfolios of between 2 and 8 stocks, and the best portfolios had three points of edge. That is not a material edge. Furthermore, one of the stocks picked, Velo3D, Inc. VLD, was profitable and no longer is. The model found stocks that have aggressive price movements, offsetting price changes, likely some closing stock price laddering or tape painting. Of note, Nvidia NVDA (computer hardware) is in a few of these portfolios, along with TTD (ad tech).
In conclusion, if we only invest in profitable, lower debt companies with positive common equity, we lose the edge from quantitative analysis. It is interesting that the model picked NVDA and TTD, and really likes small cap stocks.
If the model is allowed to evaluate all common stocks, it picks very risky stocks, but finds 7x to 8x the edge.
Part of being an investment advisor is to help people make the right decisions for investing and/or trading. Buying profitable, under-leveraged stocks is lower risk. It comes at a price, where the total stock set trades at 20.0x net income and 4.48x common equity. Debt:Equity ratio is 0.61, and Debt:Market Cap ratio is 0.14. It is interesting that when we ran the model a few weeks ago with a lower leverage ratio (a 'tighter' filter), the Price / Earnings ratio was 60% higher (32), and the Price / Equity ratio was 15% higher (5.2). Common stock safety comes with a steep price.
So, what should you do (without buying our services)?
You could choose randomly from among some or all profitable companies listed on US stock exchanges, and hold an equal amount of each stock. If you are looking for safety, be prepared to accept a slightly lower expected return (1.5% p.a.) that comes with higher valuations and know that you would have suffered through 30% less volatility than if you choose unprofitable companies.
You could also choose a combination of three US equity index ETFs, the SPY, QQQ and IWM.
In terms of investing in unprofitable companies, this is where you should spend time researching companies and looking for an edge, as these stocks carry more risk, and as a group have higher expected returns.
Our clients receive a list of stocks that have individually better (or worse) risk-return profiles, and portfolios of stocks that should provide an edge over the S&P 500, NASDAQ 100 or Russell 2000. Some of those stocks and profiles are meant to be held as long investments, and have a significant risk/return advantage based on historical price movements. Others are meant to be avoided or held as short positions, as they have much more risk for the return you would expect by holding them.
Our clients also receive other stock lists that show the Chicago Quantum Net Score for every stock analyzed, and certain outliers like stocks with high skewness and high kurtosis, along with low variance. We also identify stocks with price spikes, volume spikes, and negative BETA.
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