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not necessarily looking for predictive power. that's a 3 year project. just for market making skillset. The work that Dave Forster did was just for front month. That creates month 1. Then, similar logic has to create a month 1/month 2 spread to create a month 2 outright market. Same for month 2/ month 3 to create month 3. There might be 24-36 individual markets to create a forward curve. Sometimes month 1 has correlation to the month 1/ month 2 spread. Sometimes it does not. Must create a system that is mechanical but very easy for a human to add bias.
-----Original Message----- From: Thuraisingham, Ravi Sent: Monday, October 01, 2001 10:20 AM To: Arnold, John Subject: Neural Networks John, I just wanted to give you heads up that I did look into the subject system to learn from what your trading activities and then figure ways to automate some aspects of you daily activities. I will try to send you a few power point slides showing my initial thoughts on the system. It appears that neutral network (AI is a subset of this class of learning systems) type of model that takes input from all available sources (including actual market feedback, weather and other fundamentals) and uses curve building functions and other existing tools as transfer functions, along with your own thinking (your processing functions that your neurons are wired up to do), could help the neural network to learn and eventually provide the necessary predictive power. Ravi Thuraisingham, CFA Director, Storage Trading Enron Broadband Services p 713.853.3057 c 713.516.5440 pg 877.680.4806 ravi.thuraisingham@enron.com
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