As a result, I was delighted when he agreed to write this section of the concepts chapter. He's an internationally acclaimed technical analyst, investment software developer, and financial author. The integration of intermarket analysis with traditional single-market technical analysis is necessary for profitable trading in the 1990s and beyond. Today's limited single-market focus must yield to a broader analytic framework that addresses the nonlinear interdependence of today's financial markets. This approach allows traders to quantify complex intermarket relationships, assess the simultaneous impact of multiple related markets on a given market, and measure the leads and lags that exist within these relationships.
Neural networks are an excellent tool to implement synergistic analysis.
They can be used to synthesize disparate data and find hidden patterns and complex relationships between markets. In fact, they perform an outstanding job at processing extensive amounts of intermarket data. It is their ability to quantify subtle relationships and detect hidden patterns between numerous related markets that makes neural networks an important mathematical tool in the financial arena. Additionally, through the use of neural networks, financial forecasting becomes possible, so that traders can gain an anticipatory, not just a retrospective, vantage point on the financial markets. Through the use of neural networks applied to intermarket analysis, traders can actually forecast the financial markets, similar to the way meteorologists forecast the path that a hurricane is expected to take.