關於本電子書
This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong.
* Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website
* Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website
為這本電子書評分
歡迎提供意見。
閱讀資訊
智慧型手機與平板電腦
筆記型電腦和電腦
你可以使用電腦的網路瀏覽器聆聽你在 Google Play 購買的有聲書。
電子書閱讀器與其他裝置
如要在 Kobo 電子閱讀器這類電子書裝置上閱覽書籍，必須將檔案下載並傳輸到該裝置上。請按照說明中心的詳細操作說明，將檔案傳輸到支援的電子閱讀器上。
