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Applied quantitative methods for trading and investment [[electronic resource] /] / edited by Christian L. Dunis, Jason Laws, and Patrick Naïm
| Applied quantitative methods for trading and investment [[electronic resource] /] / edited by Christian L. Dunis, Jason Laws, and Patrick Naïm |
| Pubbl/distr/stampa | Chichester, West Sussex ; ; Hoboken, N.J., : John Wiley, c2003 |
| Descrizione fisica | 1 online resource (427 p.) |
| Disciplina |
332.6/01/5195
332.6015195 |
| Altri autori (Persone) |
DunisChristian
LawsJason NaïmPatrick |
| Collana | Wiley finance series |
| Soggetto topico |
Finance - Mathematical models
Investments - Mathematical models Speculation - Mathematical models |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-27398-4
9786610273980 0-470-29950-9 0-470-87134-2 0-470-01326-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 |
| Record Nr. | UNINA-9910143228603321 |
| Chichester, West Sussex ; ; Hoboken, N.J., : John Wiley, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applied quantitative methods for trading and investment [[electronic resource] /] / edited by Christian L. Dunis, Jason Laws, and Patrick Naïm
| Applied quantitative methods for trading and investment [[electronic resource] /] / edited by Christian L. Dunis, Jason Laws, and Patrick Naïm |
| Pubbl/distr/stampa | Chichester, West Sussex ; ; Hoboken, N.J., : John Wiley, c2003 |
| Descrizione fisica | 1 online resource (427 p.) |
| Disciplina |
332.6/01/5195
332.6015195 |
| Altri autori (Persone) |
DunisChristian
LawsJason NaïmPatrick |
| Collana | Wiley finance series |
| Soggetto topico |
Finance - Mathematical models
Investments - Mathematical models Speculation - Mathematical models |
| ISBN |
1-280-27398-4
9786610273980 0-470-29950-9 0-470-87134-2 0-470-01326-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 |
| Record Nr. | UNINA-9910830386503321 |
| Chichester, West Sussex ; ; Hoboken, N.J., : John Wiley, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applied quantitative methods for trading and investment / / edited by Christian L. Dunis, Jason Laws, and Patrick Naim
| Applied quantitative methods for trading and investment / / edited by Christian L. Dunis, Jason Laws, and Patrick Naim |
| Pubbl/distr/stampa | Chichester, West Sussex ; ; Hoboken, N.J., : John Wiley, c2003 |
| Descrizione fisica | 1 online resource (427 p.) |
| Disciplina | 332.6/01/5195 |
| Altri autori (Persone) |
DunisChristian
LawsJason NaïmPatrick |
| Collana | Wiley finance series |
| Soggetto topico |
Finance - Mathematical models
Investments - Mathematical models Speculation - Mathematical models |
| ISBN |
9786610273980
9781280273988 1280273984 9780470299500 0470299509 9780470871348 0470871342 9780470013267 0470013265 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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 |
| Record Nr. | UNINA-9911019677603321 |
| Chichester, West Sussex ; ; Hoboken, N.J., : John Wiley, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence in Financial Markets : Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics / / edited by Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos
| Artificial Intelligence in Financial Markets : Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics / / edited by Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | London : , : Palgrave Macmillan UK : , : Imprint : Palgrave Macmillan, , 2016 |
| Descrizione fisica | 1 online resource (XV, 344 p. 49 illus., 17 illus. in color.) |
| Disciplina | 658.15 |
| Collana | New Developments in Quantitative Trading and Investment |
| Soggetto topico |
Business enterprises - Finance
Financial services industry Financial risk management Social sciences - Mathematics Artificial intelligence Corporate Finance Financial Services Risk Management Mathematics in Business, Economics and Finance Artificial Intelligence |
| ISBN |
9781137488800
1137488808 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. A Review of Applications of Artificial Intelligence in Financial Domain -- SECTION I: Financial Forecasting and Trading -- 2. Trading the FTSE100 Index – ‘Adaptive' Modelling and Optimisation Techniques -- 3. Modelling, Forecasting and Trading the Crack – A Sliding Window Approach to Training Neural Networks -- 4. GEPTrader: A new Standalone Tool for Constructing Trading Strategies with Gene Expression Programming -- SECTION II: ECONOMICS -- 5. Business Intelligence for Decision Making in Economics -- 6. An automated literature analysis on data mining applications to credit risk assessment -- SECTION III: CREDIT RISK ANALYSIS -- 7. Intelligent credit risk decision support: architecture and implementations -- 8. Artificial Intelligence for Islamic Sukuk Rating Predictions -- SECTION IV: PORTFOLIO MANAGEMENT, ANALYSIS AND OPTIMISATION -- 9. Portfolio selection as a multiperiod choice problem under uncertainty: an interation-based approach -- 10. Handling model risk in portfolio selection using a Multi-Objective Genetic Algorithm -- 11. Linear regression versus fuzzy linear regression — does it make a difference in the evaluation of the performance of mutual fund managers? |
| Record Nr. | UNINA-9910153100303321 |
| London : , : Palgrave Macmillan UK : , : Imprint : Palgrave Macmillan, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||