By Jeffrey Cohen, President, US Advanced Computing Infrastructure, Inc.

As a result, we are running our model tonight to bring in lots of small caps, and under $1.00 stocks to see if the model likes runners, or MOMO stocks, and even those that are small or micro-capitalization.

Our model is starting to pick risky, new economy stocks over the tried and true. It suggests smaller portfolio sizes with more concentrated risk in those very same risky stocks.

Why?

It's simple:
1. the market is going up
2. the market has lower risk right now (put another way, lower price volatility).

So, you get earnings with less risk. Sounds good to the Chicago Quantum Net Score.

Short post today.  Our model has a few stocks that it likes...over long periods of time.

They tend to have had high BETA values, and recently have low volatility. Therefore, they look like they can run wild when stocks rise, but also are very calm and safe bets.

Today, Digital Turbine $APPS issues earnings and showed their business shrunk (was a growth stock) and they went from profit to loss on a GAAP basis. 

Stock dropped 46% today.

When we run our model, we are using the 'math' behind stock movements, and not doing due diligence on stocks.  This loss would have been catastrophic had it not been hedged.

So, we suggest that at a minimum to eliminate positions in stocks that will have earnings releases. This way, these one-time events can be avoided, both on the positive and negative side.

Good luck to all.

May 16, 2023
Jeffrey Cohen, President US Advanced Computing Infrastructure, Inc.

We analyze between 3,500 and 4,000 stocks each day. We look at the price volatility over the past year and use it in our calculations. 

We have seen those volatility numbers decline over the past weeks.

What this means is that our model is 'promoting' economically sensitive stocks, and smaller portfolios. Why? Because the expected returns of stocks is outweighing the cost of risk.

This week we lowered the expected return of stocks (forward looking for the next 12 months). Normally, this makes our model more conservative. It did not this week.

​The model continues to 'crunch' the data on price variance for stocks, and it makes risky stocks more attractive.