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Applied quantitative method...
This book provides a manual on quantitative financial analysis. Focusing on advanced methods for modelling financial markets in the context of practical financial applications, it will cover data, software and techniques that will enable the reader to implement and interpret quantitative methodologies, specifically for trading and investment. Includes contributions from an international team of academics and quantitative asset managers from Morgan Stanley, Barclays Global Investors, ABN AMRO and Credit Suisse First Boston.Fills the gap for a book on applied quantitative investment
Monografía
monografia Rebiun29222788 https://catalogo.rebiun.org/rebiun/record/Rebiun29222788 m o d | cr -n--------- 030414s2003 enka ob 001 0 eng 1-280-27398-4 9786610273980 0-470-29950-9 0-470-87134-2 0-470-01326-5 CBUC 991010729463706709 MiAaPQ MiAaPQ MiAaPQ eng 332.6/01/5195 332.6015195 Applied quantitative methods for trading and investment electronic resource] edited by Christian L. Dunis, Jason Laws, and Patrick Naïm Chichester, West Sussex Hoboken, N.J. John Wiley c2003 Chichester, West Sussex Hoboken, N.J. Chichester, West Sussex Hoboken, N.J. John Wiley 1 online resource (427 p.) 1 online resource (427 p.) Text txt computer c online resource cr Wiley finance series Description based upon print version of record Includes bibliographical references and index Applied Quantitative Methods for Trading and Investment; Contents; About the Contributors; Preface; 1 Applications of Advanced Regression Analysis for Trading and Investment; Abstract; 1.1 Introduction; 1.2 Literature review; 1.3 The exchange rate and related financial data; 1.4 Benchmark models: theory and methodology; 1.5 Neural network models: theory and methodology; 1.6 Forecasting accuracy and trading simulation; 1.7 Concluding remarks; References; 2 Using Cointegration to Hedge and Trade International Equities; Abstract; 2.1 Introduction; 2.2 Time series modelling and cointegration 2.3 Implicit hedging of unknown common risk factors2.4 Relative value and statistical arbitrage; 2.5 Illustration of cointegration in a controlled simulation; 2.6 Application to international equities; 2.7 Discussion and conclusions; References; 3 Modelling the Term Structure of Interest Rates: An Application of Gaussian Affine Models to the German Yield Curve; Abstract; 3.1 Introduction; 3.2 Background issues on asset pricing; 3.3 Duffie-Kan affine models of the term structure; 3.4 A forward rate test of the expectations theory; 3.5 Identification 3.6 Econometric methodology and applications3.7 Estimation results; 3.8 Conclusions; References; 4 Forecasting and Trading Currency Volatility: An Application of Recurrent Neural Regression and Model Combination; Abstract; 4.1 Introduction; 4.2 The exchange rate and volatility data; 4.3 The GARCH (1,1) benchmark volatility forecasts; 4.4 The neural network volatility forecasts; 4.5 Model combinations and forecasting accuracy; 4.6 Foreign exchange volatility trading models; 4.7 Concluding remarks and further work; Acknowledgements; Appendix A; Appendix B; Appendix C; Appendix D; Appendix E Appendix FAppendix G; References; 5 Implementing Neural Networks, Classification Trees, and Rule Induction Classification Techniques: An Application to Credit Risk; Abstract; 5.1 Introduction; 5.2 Data description; 5.3 Neural networks for classification in Excel; 5.4 Classification tree in Excel; 5.5 See5 classifier; 5.6 Conclusions; References; 6 Switching Regime Volatility: An Empirical Evaluation; Abstract; 6.1 Introduction; 6.2 The model; 6.3 Maximum likelihood estimation; 6.4 An application to foreign exchange rates; 6.5 Conclusion; References Appendix A: Gauss code for maximum likelihood for variance switching models7 Quantitative Equity Investment Management with Time-Varying Factor Sensitivities; Abstract; 7.1 Introduction; 7.2 Factor sensitivities defined; 7.3 OLS to estimate factor sensitivities: a simple, popular but inaccurate method; 7.4 WLS to estimate factor sensitivities: a better but still sub-optimal method; 7.5 The stochastic parameter regression model and the Kalman filter: the best way to estimate factor sensitivities; 7.6 Conclusion; References 8 Stochastic Volatility Models: A Survey with Applications to Option Pricing and Value at Risk This book provides a manual on quantitative financial analysis. Focusing on advanced methods for modelling financial markets in the context of practical financial applications, it will cover data, software and techniques that will enable the reader to implement and interpret quantitative methodologies, specifically for trading and investment. Includes contributions from an international team of academics and quantitative asset managers from Morgan Stanley, Barclays Global Investors, ABN AMRO and Credit Suisse First Boston.Fills the gap for a book on applied quantitative investment English Finance- Mathematical models Investments- Mathematical models Speculation- Mathematical models Electronic books Dunis, Christian Laws, Jason Naïm, Patrick 0-470-84885-5 Wiley finance series