Signature Methods in Finance
This Open Access volume offers an accessible entry point into the fast-growing field of signature methods in finance. It is written for early-career researchers and quantitatively minded practitioners—quant analysts and applied researchers—seeking a clear, practical introduction. It highlights recen...
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| Ձևաչափ: | Online |
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| Լեզու: | անգլերեն |
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Springer Nature
2025
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| Խորագրեր: | |
| Առցանց հասանելիություն: | ONIX_20251128T131701_9783031972393_53 |
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| _version_ | 1869529678922907648 |
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| collection | Directory of Open Access Books |
| description | This Open Access volume offers an accessible entry point into the fast-growing field of signature methods in finance. It is written for early-career researchers and quantitatively minded practitioners—quant analysts and applied researchers—seeking a clear, practical introduction. It highlights recent developments and includes coding examples to help readers apply signature methods in practice. The advantages of modeling financial markets from a path-wise perspective, rather than as a traditional series of returns, are increasingly gaining recognition. Signature methods provide a parsimonious description of paths of stochastic processes and, through the signature kernel, open a rich and compelling framework at the interface between machine learning and mathematical finance. “I have been extraordinarily fortunate to work alongside brilliant collaborators throughout this journey, and this book beautifully reflects the richness of that shared contribution—for which I am deeply grateful.”—Prof Terry Lyons, University of Oxford, Imperial College, and PI of DataSig “This fascinating collection, dedicated to Terry Lyons, offers invaluable insights into signature methods and their many uses.” Jim Gatheral, Presidential Professor, Baruch College, Quant of the Year 2021 "A timely and important contribution to the fast-growing field of signature methods, showcasing the theory and applications of these powerful ideas.” — Prof Ben Hambly, University of Oxford “An impressive book on signatures with articles by the most distinguished researchers in the field. A reference from day one." – Dr Hans Buehler, co-CEO XTX Markets, Quant of the Year 2022 "This book provides a masterful exposition and development of signature methods in finance. It is concise, precise, and actionable. It will be an excellent source for anyone interested in modern financial engineering techniques." – Prof Alexander Lipton, Global Head of R&D, ADIA, and Founding Member ADIA Lab, Quant of the Year 2000 and Buy-side Quant of the Year 2021. |
| format | Online |
| id | doab-20.500.12854ir-169620 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1696202025-11-29T07:07:54Z Signature Methods in Finance Bayer, Christian dos Reis, Goncalo Horvath, Blanka Oberhauser, Harald Open Access Path Signature Methods Machine Learning Mathematical Finance Modelling Capturing Information of Paths of Random Processes Examples in Trading, Model Calibration and Statistical Finance thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics thema EDItEUR::K Economics, Finance, Business and Management This Open Access volume offers an accessible entry point into the fast-growing field of signature methods in finance. It is written for early-career researchers and quantitatively minded practitioners—quant analysts and applied researchers—seeking a clear, practical introduction. It highlights recent developments and includes coding examples to help readers apply signature methods in practice. The advantages of modeling financial markets from a path-wise perspective, rather than as a traditional series of returns, are increasingly gaining recognition. Signature methods provide a parsimonious description of paths of stochastic processes and, through the signature kernel, open a rich and compelling framework at the interface between machine learning and mathematical finance. “I have been extraordinarily fortunate to work alongside brilliant collaborators throughout this journey, and this book beautifully reflects the richness of that shared contribution—for which I am deeply grateful.”—Prof Terry Lyons, University of Oxford, Imperial College, and PI of DataSig “This fascinating collection, dedicated to Terry Lyons, offers invaluable insights into signature methods and their many uses.” Jim Gatheral, Presidential Professor, Baruch College, Quant of the Year 2021 "A timely and important contribution to the fast-growing field of signature methods, showcasing the theory and applications of these powerful ideas.” — Prof Ben Hambly, University of Oxford “An impressive book on signatures with articles by the most distinguished researchers in the field. A reference from day one." – Dr Hans Buehler, co-CEO XTX Markets, Quant of the Year 2022 "This book provides a masterful exposition and development of signature methods in finance. It is concise, precise, and actionable. It will be an excellent source for anyone interested in modern financial engineering techniques." – Prof Alexander Lipton, Global Head of R&D, ADIA, and Founding Member ADIA Lab, Quant of the Year 2000 and Buy-side Quant of the Year 2021. 2025-11-29T07:07:53Z 2025-11-29T07:07:53Z 2025-11-28T12:22:43Z 2026 book ONIX_20251128T131701_9783031972393_53 https://library.oapen.org/handle/20.500.12657/108717 9783031972393 9783031972386 https://directory.doabooks.org/handle/20.500.12854/169620 eng Springer Finance; Springer Finance Lecture Notes; Mathematics and Statistics; Mathematics and Statistics (R0) open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/108717/1/9783031972393.pdf Springer Nature Springer 10.1007/978-3-031-97239-3 10.1007/978-3-031-97239-3 9fa3421d-f917-4153-b9ab-fc337c396b5a ffe944ae-f50d-47e4-84c8-6d589176c7f4 53a8fe1d-b995-4e29-80d1-795cca6b72b5 9783031972393 9783031972386 Springer 424 Cham [...] [...] open access |
| spellingShingle | Open Access Path Signature Methods Machine Learning Mathematical Finance Modelling Capturing Information of Paths of Random Processes Examples in Trading, Model Calibration and Statistical Finance thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics thema EDItEUR::K Economics, Finance, Business and Management Signature Methods in Finance |
| title | Signature Methods in Finance |
| title_full | Signature Methods in Finance |
| title_fullStr | Signature Methods in Finance |
| title_full_unstemmed | Signature Methods in Finance |
| title_short | Signature Methods in Finance |
| title_sort | signature methods in finance |
| topic | Open Access Path Signature Methods Machine Learning Mathematical Finance Modelling Capturing Information of Paths of Random Processes Examples in Trading, Model Calibration and Statistical Finance thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics thema EDItEUR::K Economics, Finance, Business and Management |
| topic_facet | Open Access Path Signature Methods Machine Learning Mathematical Finance Modelling Capturing Information of Paths of Random Processes Examples in Trading, Model Calibration and Statistical Finance thema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics thema EDItEUR::K Economics, Finance, Business and Management |
| url | ONIX_20251128T131701_9783031972393_53 |