V.11:11 (457-460): Training Neural Networks by Lou Mendelsohn
Product Description
Training Neural Networks by Lou Mendelsohn
The application of neural networks to financial forecasting has quickly become a hot topic in today's globalized trading environment. With extensive technical, intermarket and fundamental data available for analysis, neural networks are well suited to pattern recognition and quantifying relationships between interrelated markets. However, neural networks are not easy to develop. Here, S&C contributor Lou Mendelsohn examines the best ways to train and test neural networks for maximum performance.
Successfully developing neural networks to implement synergistic market analysis for financial forecasting in today's global markets requires both knowledge of the financial markets and expertise in the design and application of artificial intelligence technologies. Now let us examine the process of training and testing neural networks for synergistic analysis in which technical, fundamental and intermarket data are used to find hidden patterns and relationships within the data.
To accomplish this, a set of data facts must be selected for presentation to the network. In addition, various training parameters must be optimized during the training process, and a protocol that automates the training and testing process to assure proper training of the network must be devised. If done properly, superior performance and more accurate forecasts can be achieved over rule-based technical analysis methods that rely on single market linear modeling of market dynamics.
The application of neural networks to financial forecasting has quickly become a hot topic in today's globalized trading environment. With extensive technical, intermarket and fundamental data available for analysis, neural networks are well suited to pattern recognition and quantifying relationships between interrelated markets. However, neural networks are not easy to develop. Here, S&C contributor Lou Mendelsohn examines the best ways to train and test neural networks for maximum performance.
Successfully developing neural networks to implement synergistic market analysis for financial forecasting in today's global markets requires both knowledge of the financial markets and expertise in the design and application of artificial intelligence technologies. Now let us examine the process of training and testing neural networks for synergistic analysis in which technical, fundamental and intermarket data are used to find hidden patterns and relationships within the data.
To accomplish this, a set of data facts must be selected for presentation to the network. In addition, various training parameters must be optimized during the training process, and a protocol that automates the training and testing process to assure proper training of the network must be devised. If done properly, superior performance and more accurate forecasts can be achieved over rule-based technical analysis methods that rely on single market linear modeling of market dynamics.
FOR THOSE ORDERING ARTICLES SEPARATELY:
*Note: $2.95-$5.95 Articles are in PDF format only. No hard copy of the article(s) will be delivered. During checkout, click the "Download Now" button to immediately receive your article(s) purchase. STOCKS & COMMODITIES magazine is delivered via mail. After paying for your subscription at store.traders.com users can view the S&C Digital Edition in the subscriber's section on Traders.com.
| Take Control of Your Trading. |
| Professional Traders' Starter Kit |
| All these items shown below only $299.99! |
| Click Here to Order |