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| fixed length control field |
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
240319b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783030410704 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
332.0285554 |
| Item number |
DIX |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Dixon, Matthew F. |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Machine learning in finance : from theory to practice |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2020 |
| Place of publication, distribution, etc |
Cham : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxv, 548 p. ; |
| Other physical details |
ill., |
| Dimensions |
24 cm. |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
79.99 |
| Price type code |
€ |
| Unit of pricing |
93.50 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Insurance |
|
|---|
| Topical term or geographic name as entry element |
Statistics |
|
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| Topical term or geographic name as entry element |
Applications of mathematics |
|
|---|
| Topical term or geographic name as entry element |
Interpretability |
|
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| Topical term or geographic name as entry element |
Gaussian processes |
|
|---|
| Topical term or geographic name as entry element |
Probabilistic sequence |
|
|---|
| Topical term or geographic name as entry element |
Inverse reinforcement |
|
|---|
| Topical term or geographic name as entry element |
Machine learning and finance |
|
|---|
| Topical term or geographic name as entry element |
Bayesian regression |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Halperin, Igor |
|
|---|
| Personal name |
Bilokon, Paul A. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |