StockSpotter as a Trading Tool

John Ehlers and Ric Way are far too professional to pump me for a recommendation of their StockSpotter service, which is always something I look for in a market service with integrity.  I was first impressed with John's longtime work on market cycles and then discovered that he and Ric had assembled the StockSpotter site.  

Above is an algorithmic, cycle-based forecast for Boeing stock ($BA) that Ric had shared recently on StockTwits (@StockSpotter).  In addition to the forecasts, StockSpotter tracks where individual stocks and ETFs stand in their dominant cycles and identify both trade setups (stocks poised to give buy or sell signals within a few days) and actual trade signals.  

Particularly impressive is the fact that John and Ric track the accuracy of their signals in real time and report the P/L of each of their recommendations.  Because they track the broad universe of U.S. shares, they can make far more recommendations than an individual trader is likely to implement.  A Monte Carlo simulation feature shows how their forecasts performed if one were to take one or several random recommendations from their lists.  The Sharpe Ratio of 1.3 for the strategy is quite good; a separate Monte Carlo drawdown analysis helps identify the risks of the strategy.

There are many ways to use the information.  You could create a long/short strategy of the names that give buy and sell signals or you could trade a basket of shares with signals against a sector or index ETF that does not give a signal.  You could also use the cycle-based research as a second opinion for your own trade ideas.  I've found, for example, that when the StockSpotter forecasts and my own model signals point in a particular direction at the same time, that's a high probability entry signal.

As I've emphasized many times, trading is a team sport.  Finding the people who do good work and making them part of your team is a great success strategy.

Further Reading:  Visualizing Market Sentiment