Today's Interconnected Financial Markets Demand New Trading Strategies

By: Lou Mendelsohn

With the world's financial markets becoming increasingly interconnected, serious futures and index option traders must now pay closer attention to related markets and their effects on the market being traded. Traders who continue to focus internally on only one market at a time (single-market analysis), oblivious to the underlying intermarket forces or market synergy that drives today's financial markets, are now at a severe competitive disadvantage and putting themselves at needless risk.

It's no longer good enough to "keep an eye" on what related markets are doing. A subjective assessment of intermarket relationships through visual examination of price charts or listening to daily news reports is simply not sufficient. Now, new, quantitative methods of analysis, capable of finding hidden patterns and relationships in related market data, are necessary to identify and profit from lucrative trading opportunities.

Complex patterns and otherwise hidden relationships between related financial markets are found through the use of neural networks, allowing the astute trader to discern and act upon trading information reflecting the intermarket dynamics inherent in today's global financial markets.

THE POWER OF FORECASTING MOVING AVERAGES
This methodology has been incorporated into an intermarket analysis software program that I developed known as VantagePoint, which utilizes neural networks to make forecasts of prices and anticipate the trend direction for various financial markets. VantagePoint's predictions include the next day's high and low, the 5-day moving average of closes two days in the future, and the 10-day moving average of closes four days in the future.

By comparing these forecasted moving averages with today's calculated moving averages, daily oscillators are created which form the basis of a predictive moving average crossover system. This unique approach retains all of the smoothing benefits of traditional moving average systems, eliminates the lag inherent in such systems, and thereby obviates the need to optimize the types and sizes of the moving averages.

Additionally, VantagePoint's neural networks are trained using the open, high, low, close, volume, and open interest data for the past ten years from the target market and nine related markets that nonlinearly affect the target market being traded, so that the moving average forecasts are not based solely upon past price data on the target market only.