Penny stocks by their very nature carry a great deal of more volatility over greater priced stocks simply because it takes far less market activity to affect their prices. Many investors and day traders spend their whole lives employing different penny stock strategies trying to find the best and most prime cheap stocks which are set to go on a huge upswing so they can capitalize and get out before and in case it turns around quickly.
One of the most remarkable new penny stock strategies for easily doing just that has been taking the difficulty and time largely out of the analytical process.
Interestingly enough, analytical stock software has been in the hands of professional traders at major trading houses for years now. It’s purpose is simple: find well performing stocks based on behavioral overlaps so that the investors who use this technology can invest accordingly.
As an example of how this penny stock strategies technology works specifically, say you have a well performing stock of the past whose price remains steady and stagnant until it inexplicably bursts in value. By analyzing the factors which led to that stocks quick appreciation, analytical stock software is able to go in and find stocks which exhibit similar behavior in a contemporary market. Stock behavior is very specific and even the smallest overlaps between a stock of the past and the present can tell you everything which you should expect from that current one.
The obvious difficulty is identifying these tiny overlaps, hence the reliance on this penny stock strategies analytical software to do just that for you.
Getting back to your original point of this article, some of these stock programs as of late exclusively target and go after cheap stocks to look for well performing tendencies in today’s cheap investments. Given the greater propensity for volatility, it’s a different process finding high probability penny stocks versus greater priced stocks. This is why analytical stock pickers which attempt to target both cheap and greater priced stocks have historically always performed the worst and have been the least precise in their predictions.
