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American-type options : stochastic approximation methods. Volume 1 / / Dmitrii S. Silvestrov
American-type options : stochastic approximation methods. Volume 1 / / Dmitrii S. Silvestrov
Autore Silvestrov Dmitrii S
Pubbl/distr/stampa Berlin : , : De Gruyter, , [2014]
Descrizione fisica 1 online resource (520 p.)
Disciplina 332.6/01/5195
Collana De Gruyter studies in mathematics
Soggetto topico Options (Finance) - Mathematical models
Stochastic approximation
Markov processes
Business mathematics
Soggetto genere / forma Electronic books.
ISBN 3-11-032982-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front matter -- Preface -- Contents -- 1. Multivariate modulated Markov log-price processes (LPP) -- 2. American-type options -- 3. Backward recurrence reward algorithms -- 4. Upper bounds for option rewards -- 5. Convergence of option rewards - I -- 6. Convergence of option rewards - II -- 7. Space-skeleton reward approximations -- 8. Convergence of rewards for Markov Gaussian LPP -- 9. Tree-type approximations for Markov Gaussian LPP -- 10. Convergence of tree-type reward approximations -- Bibliographical Remarks -- Bibliography -- Index -- Back matter
Record Nr. UNINA-9910463858603321
Silvestrov Dmitrii S  
Berlin : , : De Gruyter, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
American-type options : stochastic approximation methods. Volume 1 / / Dmitrii S. Silvestrov
American-type options : stochastic approximation methods. Volume 1 / / Dmitrii S. Silvestrov
Autore Silvestrov Dmitrii S
Pubbl/distr/stampa Berlin : , : De Gruyter, , [2014]
Descrizione fisica 1 online resource (520 p.)
Disciplina 332.6/01/5195
Collana De Gruyter studies in mathematics
Soggetto topico Options (Finance) - Mathematical models
Stochastic approximation
Markov processes
Business mathematics
Soggetto non controllato American Option
Approximation Algorithm
Convergence of Rewards
Markov Chain
Optimal Stopping
ISBN 3-11-032982-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front matter -- Preface -- Contents -- 1. Multivariate modulated Markov log-price processes (LPP) -- 2. American-type options -- 3. Backward recurrence reward algorithms -- 4. Upper bounds for option rewards -- 5. Convergence of option rewards - I -- 6. Convergence of option rewards - II -- 7. Space-skeleton reward approximations -- 8. Convergence of rewards for Markov Gaussian LPP -- 9. Tree-type approximations for Markov Gaussian LPP -- 10. Convergence of tree-type reward approximations -- Bibliographical Remarks -- Bibliography -- Index -- Back matter
Record Nr. UNINA-9910787756203321
Silvestrov Dmitrii S  
Berlin : , : De Gruyter, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
American-type options : stochastic approximation methods. Volume 1 / / Dmitrii S. Silvestrov
American-type options : stochastic approximation methods. Volume 1 / / Dmitrii S. Silvestrov
Autore Silvestrov Dmitrii S
Pubbl/distr/stampa Berlin : , : De Gruyter, , [2014]
Descrizione fisica 1 online resource (520 p.)
Disciplina 332.6/01/5195
Collana De Gruyter studies in mathematics
Soggetto topico Options (Finance) - Mathematical models
Stochastic approximation
Markov processes
Business mathematics
Soggetto non controllato American Option
Approximation Algorithm
Convergence of Rewards
Markov Chain
Optimal Stopping
ISBN 3-11-032982-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Front matter -- Preface -- Contents -- 1. Multivariate modulated Markov log-price processes (LPP) -- 2. American-type options -- 3. Backward recurrence reward algorithms -- 4. Upper bounds for option rewards -- 5. Convergence of option rewards - I -- 6. Convergence of option rewards - II -- 7. Space-skeleton reward approximations -- 8. Convergence of rewards for Markov Gaussian LPP -- 9. Tree-type approximations for Markov Gaussian LPP -- 10. Convergence of tree-type reward approximations -- Bibliographical Remarks -- Bibliography -- Index -- Back matter
Record Nr. UNINA-9910814311003321
Silvestrov Dmitrii S  
Berlin : , : De Gruyter, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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-9910840784103321
Chichester, West Sussex ; ; Hoboken, N.J., : John Wiley, c2003
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui