EOL is a principal based trading platform, meaning Enron is the buyer (seller) when there is seller (buyer) who wants to transact on EOL. EOL provides market liquidity by making the bid-ask spread. However making the spread is not the only revenue source for running EOL. There is certain information asymmetry beneficial to Enron as the market maker: ⢠Enron owns EOL trading database that contains detailed information about each transactions; trades can be aggregated according to different categories, for example, by commodity, by contract maturity, by counter party, by trading time interval, just to name a few. The informational advantage will allow us to explore market inefficiency and arbitrage across different products. ⢠The time series recorded in EOL data base contains valuable information about supply-demand balance, market directions and volatilities, market correlations and cross-market correlations, trading habits and patterns. The EOL Data Mining project is aimed at taking the advantage of the information asymmetry and market inefficiency so as to predict the market conditions. The benefit of predictability is obvious, especially in the following aspects: ⢠Predictability means profit. The ability to predict (even in a statistical sense) will give us an edge in trading and risk management. ⢠Predictability will enable us to control and reduce the risk of market making. Data Ming is a new field that combines the business insights with computer learning capabilities. The business insights are translated into certain quantitative state space models [1] (most likely non-linear time series models). Then the best model is selected deductively to fit the reality the most. A different approach is gaining popularity, that is the inductive methodology [2]. The inductive method takes advantage cheap computation power and artificial intelligence, builds the prediction model by learning the patterns contained in the time series. In the EOL Data Mining project, we will exploit both type approaches to build our ultimate Enron Perdition Models. [1] Weigend, A. S. & Gershenfeld, N. A. (eds) Time Series Prediction: Forecasting the Future and Understanding
its from the enron Eol information .. google enron EOL. that stand for enron online which was an exchange for traders.. pretty illegal though to be able to run all of those stas on your customers and then play with or against them.. like having transparent cards at a poker game except for your own. Anyone and i mean anyone could have made big money with that type of information