MARC details
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02569nam a22002297a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20221114131844.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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221114b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781107150751 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
332.0285513 |
| Item number |
BEN |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Bennett, Mark J. |
| 245 ## - TITLE STATEMENT |
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| Title |
Financial analytics with R: |
| Remainder of title |
building laptop laboratory for data science |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc. |
Cambridge University Press |
| Place of publication, distribution, etc. |
Cambridge |
| Date of publication, distribution, etc. |
2016 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xvi, 377 p. |
| 365 ## - TRADE PRICE |
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| Price type code |
GBP |
| Price amount |
51.99 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Table of Contents<br/>Preface<br/>Acknowledgements<br/>1. Analytical thinking<br/>2. The R language for statistical computing<br/>3. Financial statistics<br/>4. Financial securities<br/>5. Dataset analytics and risk measurement<br/>6. Time series analysis<br/>7. The Sharpe ratio<br/>8. Markowitz mean-variance optimization<br/>9. Cluster analysis<br/>10. Gauging the market sentiment<br/>11. Simulating trading strategies<br/>12. Data mining using fundamentals<br/>13. Prediction using fundamentals<br/>14. Binomial model for options<br/>15. Black–Scholes model and option implied volatility<br/>Appendix. Probability distributions and statistical analysis<br/>Index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Are you innately curious about dynamically inter-operating financial markets? Since the crisis of 2008, there is a need for professionals with more understanding about statistics and data analysis, who can discuss the various risk metrics, particularly those involving extreme events. By providing a resource for training students and professionals in basic and sophisticated analytics, this book meets that need. It offers both the intuition and basic vocabulary as a step towards the financial, statistical, and algorithmic knowledge required to resolve the industry problems, and it depicts a systematic way of developing analytical programs for finance in the statistical language R. Build a hands-on laboratory and run many simulations. Explore the analytical fringes of investments and risk management. Bennett and Hugen help profit-seeking investors and data science students sharpen their skills in many areas, including time-series, forecasting, portfolio selection, covariance clustering, prediction, and derivative securities.<br/><br/>Contains an ideal blend of innovative research and practical applications<br/>Tackles relevant investor problems<br/>Provides a multi-disciplined approach, solving problems from both fundamental and non-traditional methods. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Finance--Mathematical models--Data processing |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
R (Computer program language) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Finance--Databases |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Hugen, Dirk L. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |