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Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system / / Edina Berlinger [and seventeen others]
| Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system / / Edina Berlinger [and seventeen others] |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham, England : , : Packt Publishing, , 2015 |
| Descrizione fisica | 1 online resource (362 p.) |
| Disciplina | 332 |
| Collana | Community Experience Distilled |
| Soggetto topico | Finance |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-78355-208-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Time Series Analysis; Multivariate time series analysis; Cointegration; Vector autoregressive models; VAR implementation example; Cointegrated VAR and VECM; Volatility modeling; GARCH modeling with the rugarch package; The standard GARCH model; Exponential GARCH model (EGARCH); Threshold GARCH model (TGARCH); Simulation and forecasting; Summary; References and reading list; Chapter 2: Factor Models; Arbitrage pricing theory; Implementation of APT
Fama-French three-factor modelModeling in R; Data selection; Estimation of APT with principal component analysis; Estimation of the Fama-French model; Summary; References; Chapter 3: Forecasting Volume; Motivation; The intensity of trading; The volume forecasting model; Implementation in R; The data; Loading the data; The seasonal component; AR(1) estimation and forecasting; SETAR estimation and forecasting; Interpreting the results; Summary; References; Chapter 4: Big Data - Advanced Analytics; Getting data from open sources; Introduction to big data analysis in R K-means clustering on big dataLoading big matrices; Big data K-means clustering analysis; Big data linear regression analysis; Loading big data; Fitting a linear regression model on large datasets; Summary; References; Chapter 5: FX Derivatives; Terminology and notations; Currency options; Exchange options; Two-dimensional Wiener processes; The Margrabe formula; Application in R; Quanto options; Pricing formula for call quanto; Pricing a call quanto in R; Summary; References; Chapter 6: Interest Rate Derivatives and Models; The Black model; Pricing a cap with Black's model; The Vasicek model The Cox-Ingersoll-Ross modelParameter estimation of interest rate models; Using the SMFI5 package; Summary; References; Chapter 7: Exotic Options; A general pricing approach; The role of dynamic hedging; How R could help a lot; A glance beyond vanillas; Greeks - the link back to the vanilla world; Pricing the Double-no-touch option; Another way to price the Double-no-touch option; The life of a Double-no-touch option - a simulation; Exotic options embedded in structured products; Summary; References; Chapter 8: Optimal Hedging; Hedging of derivatives; Market risk of derivatives Static delta hedgeDynamic delta hedge; Comparing the performance of delta hedging; Hedging in the presence of transaction costs; Optimization of the hedge; Optimal hedging in the case of absolute transaction costs; Optimal hedging in the case of relative transaction costs; Further extensions; Summary; References; Chapter 9: Fundamental Analysis; The Basics of fundamental analysis; Collecting data; Revealing connections; Including multiple variables; Separating investment targets; Setting classification rules; Backtesting; Industry-specific investment; Summary; References Chapter 10: Technical Analysis, Neural Networks, and Logoptimal Portfolios |
| Record Nr. | UNINA-9910463729903321 |
| Birmingham, England : , : Packt Publishing, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system / / Edina Berlinger [and seventeen others]
| Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system / / Edina Berlinger [and seventeen others] |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham, England : , : Packt Publishing, , 2015 |
| Descrizione fisica | 1 online resource (362 p.) |
| Disciplina | 332 |
| Collana | Community Experience Distilled |
| Soggetto topico |
Finance
R (Computer program language) |
| ISBN | 1-78355-208-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Time Series Analysis; Multivariate time series analysis; Cointegration; Vector autoregressive models; VAR implementation example; Cointegrated VAR and VECM; Volatility modeling; GARCH modeling with the rugarch package; The standard GARCH model; Exponential GARCH model (EGARCH); Threshold GARCH model (TGARCH); Simulation and forecasting; Summary; References and reading list; Chapter 2: Factor Models; Arbitrage pricing theory; Implementation of APT
Fama-French three-factor modelModeling in R; Data selection; Estimation of APT with principal component analysis; Estimation of the Fama-French model; Summary; References; Chapter 3: Forecasting Volume; Motivation; The intensity of trading; The volume forecasting model; Implementation in R; The data; Loading the data; The seasonal component; AR(1) estimation and forecasting; SETAR estimation and forecasting; Interpreting the results; Summary; References; Chapter 4: Big Data - Advanced Analytics; Getting data from open sources; Introduction to big data analysis in R K-means clustering on big dataLoading big matrices; Big data K-means clustering analysis; Big data linear regression analysis; Loading big data; Fitting a linear regression model on large datasets; Summary; References; Chapter 5: FX Derivatives; Terminology and notations; Currency options; Exchange options; Two-dimensional Wiener processes; The Margrabe formula; Application in R; Quanto options; Pricing formula for call quanto; Pricing a call quanto in R; Summary; References; Chapter 6: Interest Rate Derivatives and Models; The Black model; Pricing a cap with Black's model; The Vasicek model The Cox-Ingersoll-Ross modelParameter estimation of interest rate models; Using the SMFI5 package; Summary; References; Chapter 7: Exotic Options; A general pricing approach; The role of dynamic hedging; How R could help a lot; A glance beyond vanillas; Greeks - the link back to the vanilla world; Pricing the Double-no-touch option; Another way to price the Double-no-touch option; The life of a Double-no-touch option - a simulation; Exotic options embedded in structured products; Summary; References; Chapter 8: Optimal Hedging; Hedging of derivatives; Market risk of derivatives Static delta hedgeDynamic delta hedge; Comparing the performance of delta hedging; Hedging in the presence of transaction costs; Optimization of the hedge; Optimal hedging in the case of absolute transaction costs; Optimal hedging in the case of relative transaction costs; Further extensions; Summary; References; Chapter 9: Fundamental Analysis; The Basics of fundamental analysis; Collecting data; Revealing connections; Including multiple variables; Separating investment targets; Setting classification rules; Backtesting; Industry-specific investment; Summary; References Chapter 10: Technical Analysis, Neural Networks, and Logoptimal Portfolios |
| Record Nr. | UNINA-9910788168603321 |
| Birmingham, England : , : Packt Publishing, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system / / Edina Berlinger [and seventeen others]
| Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system / / Edina Berlinger [and seventeen others] |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham, England : , : Packt Publishing, , 2015 |
| Descrizione fisica | 1 online resource (362 p.) |
| Disciplina | 332 |
| Collana | Community Experience Distilled |
| Soggetto topico |
Finance
R (Computer program language) |
| ISBN | 1-78355-208-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Time Series Analysis; Multivariate time series analysis; Cointegration; Vector autoregressive models; VAR implementation example; Cointegrated VAR and VECM; Volatility modeling; GARCH modeling with the rugarch package; The standard GARCH model; Exponential GARCH model (EGARCH); Threshold GARCH model (TGARCH); Simulation and forecasting; Summary; References and reading list; Chapter 2: Factor Models; Arbitrage pricing theory; Implementation of APT
Fama-French three-factor modelModeling in R; Data selection; Estimation of APT with principal component analysis; Estimation of the Fama-French model; Summary; References; Chapter 3: Forecasting Volume; Motivation; The intensity of trading; The volume forecasting model; Implementation in R; The data; Loading the data; The seasonal component; AR(1) estimation and forecasting; SETAR estimation and forecasting; Interpreting the results; Summary; References; Chapter 4: Big Data - Advanced Analytics; Getting data from open sources; Introduction to big data analysis in R K-means clustering on big dataLoading big matrices; Big data K-means clustering analysis; Big data linear regression analysis; Loading big data; Fitting a linear regression model on large datasets; Summary; References; Chapter 5: FX Derivatives; Terminology and notations; Currency options; Exchange options; Two-dimensional Wiener processes; The Margrabe formula; Application in R; Quanto options; Pricing formula for call quanto; Pricing a call quanto in R; Summary; References; Chapter 6: Interest Rate Derivatives and Models; The Black model; Pricing a cap with Black's model; The Vasicek model The Cox-Ingersoll-Ross modelParameter estimation of interest rate models; Using the SMFI5 package; Summary; References; Chapter 7: Exotic Options; A general pricing approach; The role of dynamic hedging; How R could help a lot; A glance beyond vanillas; Greeks - the link back to the vanilla world; Pricing the Double-no-touch option; Another way to price the Double-no-touch option; The life of a Double-no-touch option - a simulation; Exotic options embedded in structured products; Summary; References; Chapter 8: Optimal Hedging; Hedging of derivatives; Market risk of derivatives Static delta hedgeDynamic delta hedge; Comparing the performance of delta hedging; Hedging in the presence of transaction costs; Optimization of the hedge; Optimal hedging in the case of absolute transaction costs; Optimal hedging in the case of relative transaction costs; Further extensions; Summary; References; Chapter 9: Fundamental Analysis; The Basics of fundamental analysis; Collecting data; Revealing connections; Including multiple variables; Separating investment targets; Setting classification rules; Backtesting; Industry-specific investment; Summary; References Chapter 10: Technical Analysis, Neural Networks, and Logoptimal Portfolios |
| Record Nr. | UNINA-9910812827403321 |
| Birmingham, England : , : Packt Publishing, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||