3 More Powerful Ways Proximilar Helps You Invest Better

In our previous post we looked at several ways Proximilar can help you make better investing and trading decisions. We focused on our fundamental forecasts, i.e., EPS & revenues. But our AI technology delivers much more than earnings estimates that outperform analysts and whisper numbers. And so today, in part two, we will take a closer look at our market forecasts.

Standard deviation of earnings price move (aka, post-release up-or-down move)

Earnings releases are usually the most volatile days of any quarter, packing 10-15 days’ worth of volatility — and often more — into just one morning. You may never know for sure in which direction the stock will move, but it will likely move by a lot. You should be ready for it.
Proximilar’s AI predicts the standard deviation of the post-announcement move for thousands of US stocks.
Our forecast works better than “implied moves” derived from option prices, because extraneous factors like option liquidity do not affect it. Nor does it depend on dealer positioning and market sentiment that drive option prices.
The actual price move (up or down) may be bigger or smaller than the estimated standard deviation, but our AI tells you the scale of the risk involved. Armed with our forecast, you can manage your positions better and avoid getting blindsided by unexpected price action.

Expected bid-ask spread

This is how brokerages make piles of money on your trades — despite charging you “zero commission”: the spread between the asking price and the bid. Your trade may look good on paper, but disappoint in practice if you do not take the bid-offer spread into account.
We built this model to make our own trading more rigorous. For thousands of US stocks it estimates the transaction costs of a “round-trip” trade.

We show this cost in two ways:
(1) as a “broker commission” you pay for a $10,000 position, and
(2) in cents per share.
Trading spreads always fluctuate, and your actual costs will vary depending on time of day, market environment, etc. But we find this estimate to be an excellent starting point.

Forward-looking beta (β)

Beta is how much we expected the stock to move on average when the market (e.g., S&P 500) moves 1%. The average beta of all stocks is about 1. For most stocks it’s a positive number.
Most data providers estimate beta by looking at the last few months, assuming that the future will resemble the past. We find that approach far too simplistic.
Our model does not get fooled by large recent moves that are unlikely to be repeated, and yet boost the “historical” beta. Our forecast’s focus is on the stock’s future performance relative to the overall market.

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