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The neural index is used to confirm these oscillators. It is based on a predicted three-day moving average of today's, tomorrow's, and the following day's closes. When the neural index is 1.00, VantagePoint expects the market to go up over the next two days. When the neural index is 0.00, VantagePoint expects the market to go down over the next two days. It presently makes these predictions with up to 78 percent accuracy. |
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A trader can also look at daily reports from related markets for additional confirmation. For instance, the Eurodollar, 5-year T-note, and 10-year T-note daily reports offer additional insight for bond traders into what VantagePoint expects to happen in the interest rate complex. Similar relationships exist between various energy markets, stock indexes, and currency markets that VantagePoint covers. The bottom line is that predictive intermarket information, based upon the pattern recognition capabilities of neural networks, offers traders a broader insight or "vantage point" (hence the name of the software) on the markets which can be realized by focusing solely upon the internal dynamics of each market alone. |
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Neal: So how can we translate this concept into profits? |
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Louis: Through financial forecasting incorporating intermarket analysis, traders can gain an anticipatory, not just a retrospective, vantage point on the markets. With single-market system testing, it's easy to discern where the markets have been and to discover simulated trading strategies which may have worked on past data. But the real payoff is in being able to anticipate future market direction consistently so that you can act decisively and confidently when real money is on the line. |
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With randomness and unpredictable events inherent in the financial markets, no one, regardless of financial, intellectual, and computational resources, will ever be able to make 100% accurate predictions. A maximum achievable level, in my estimation, is at best 80 to 85%. From a decision-making standpoint under conditions of uncertainty, even considerably less |
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