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SESL Meeting / Presentation April 2003

This presentation by Takenori Kamo highlights recent revisions to the paper "Global Stock Index Forecasting Using Multiple Generalized Regression Neural Networks with a Gating Network." The revisions were made based on reviewer feedback, including the addition of out-of-sample results, extending data analysis from 3 months to 3 years, and incorporating new learning models such as Backpropagation and Recurrent Networks. The updates aim to improve forecasting accuracy and legitimacy, supported by MATLAB simulations and an expanded dataset covering July 1997 to February 2003.

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SESL Meeting / Presentation April 2003

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  1. SESL Meeting / Presentation April 2003 Takenori Kamo

  2. Currently, working on . . . . • Revising the paper, “Global Stock Index Forecasting Using Multiple Generalized Regression Neural Networks with a Gating Network” for the Journal, “ Applied Intelligence”, Kluwer Academic Publishers. • The revision is based on the suggestions and corrections by the reviewers and referees.

  3. Suggestions and Correction • No reference of Radial Basis Function (RBF), but it mentioned in Section 3. • Do Not Believe the results based on only 3 months of data. Need to see out-of-sample results for at least 1 year. • Need more than one learning model (GRNN)

  4. To fulfill these suggestions • Data/results Expanded from 3 months to 3 years. • New learning models are added • Backpropagation • Recurrent Networks • Re-simulate and get new results

  5. Have completed . . . • Data (indexes) of July 1997 Feb 2003 are collected/updated • Backpropergation and GRNN are simulated and data are corrected. (3 models for each learning models).

  6. Working on . . . . • Recurrent Neural Network • MATLAB programs and simulations • Website: Financial Forecasting with Neural Networks

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