Murray A. Ruggiero, Jr - Intermarket Analysis Using Todays Hot New Indicators (Total size: 187.6 MB Contains: 4 files)

Advanced technologies are methods used by engineers, scientists, and physicists to solve real-world problems that affect our lives in many unseen ways. Advanced technologies are not just rocket science methods;they include applying statistical analysis to prove or disprove a given hypothesis. For example, statistical methods are used to evaluate the effectiveness of a drug for treating a given illness. Genetic algorithms have been used by engineers for many different applications: the development of the layout of micro processors circuits, for example, or the optimization of landing strut weights in aircraft. In general, complex problems that require testing millions or even billions of combinations to find the optimal answer can be solved using genetic algorithms.

Another method, maximum entropy spectral analysis or the maximum entropy method (MEM), has been used in the search for new oil reserves and was adapted by John Ehlers for use in developing trading strategies. Chaos, a mathematical concept, has been used by scientists to understand how to improve weather forecasts. Artificial intelligence was once used only in laboratories to try to learn how to capture human expertise. Now, this technology is used in everything from cars to toasters. These technologies-really just different ways of looking at the world-have found their way to Wall Street and are now used by some of the most powerful institutions in the world.


John Deere Inc. manages 20 percent of its pension fund money using neural networks, and Brad Lewis, while at Fidelity Investments, used neural networks to select stocks.You do not need to be a biophysicist or statistician to understand these technologies and incorporate them into your technical trading system.Cybernetic Trading Strategies will explain how some of these advanced technologies can give your trading system an edge. I will show you which technologies have the most market applicability, explain how they work, and then help you design a technical trading system using these technologies. Lastly, but perhaps most importantly, we will test these systems.

Although the markets have no single panacea, incorporating elements of statistical analysis, spectra analysis, neural networks, genetic algorithms, fuzzy logic, and other high-tech concepts into a traditional technical trading system can greatly improve the performance of standard trading systems. For example, I will show you how spectra analysis can be used to detect, earlier than shown by classical indicators such as ADX-the average direction movement indicator that measures the strength of a trend-when a market is trending. I will also show you how to evaluate the predictive value of a given classical method, by using the same type of statistical analysis used to evaluate the effectiveness of drugs on a given illness.I have degrees in both physics and computer science and have been researching neural networks for over eight years.

I invented a method for embedding neural networks into a spreadsheet. It seemed a natural extension to then try and apply what I have learned to predicting the markets. However, my early models were not very successful. After many failed attempts, I realized that regardless of how well I knew the advanced technologies, if I didn’t have a clear understanding of the markets I was attempting to trade, the applications would prove fruitless. I then spent the greater part of three years studying specific markets and talking to successful traders. Ultimately, I realized that my systems needed a sound premise as their foundation.

My goals are: to provide you with the basics that will lead to greater market expertise (and thus a reasonable premise on which to base your trades) and to show you how to develop reliable trading models using so called advanced technologies.

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Murray A. Ruggiero, Jr - Intermarket Analysis Using Todays Hot New Indicators (Total size: 187.6 MB Contains: 4 files)

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