AI is quickly taking over the world of finance. AI algorithms are already making calculated split-second investment decisions that can outperform most human investors.
In 2002, Formula Stocks was one of the first strategies to start this trend with their AI algorithm analyzing big data to evaluate every company in the stock market with the goal of finding wonderful companies with high future growth potential selling for less than their intrinsic value.
After seven years in development, Formula Stocks launched in 2009 with their first publicly available algorithm claiming an +85% win ratio and annual growth rates double that of the usual index funds.
Over the last decade, Formula Stocks have continued development of this strategy finding high-quality companies with good growth prospects and a large margin of safety, setting the bar at a +92% win ratio. This is accomplished by studying the super investors of the world, such as Benjamin Graham, Philip Fisher, Warren Buffet, Jesse Livermore, etc., and implementing their teachings into a combined AI investment algorithm that can take advantage of these multiple investment strategies at the same time to find those high probability investment opportunities.
This is all simplified down to a simple number called the “AI Score” A number between -100 and +100 that is given to every stock trading on the major exchanges evaluating the value, growth, risk, reward, stewardship, and more. The AI Score can be used as a stock screener to quickly identify stocks that might be worth looking into, what to stay away from, what might have high growth potential but with a low margin of safety, etc.
Since Formula Stocks went public in 2009, the results have matched the research and backtesting with a +90% win ratio and outperformed the S&P500 between Jan 2009 and Jan 2022 following the long-term investment portfolio.
See https://formulastocks.com/ for more information on strategy and risk.
As quantitative investment strategies continue to advance rapidly, investors will have to adapt to keep up with these new algorithms that don’t make human errors or have to deal with human biases such as fear and greed.