Python for Algorithmic Trading: from idea to cloud development
Financial trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows stud...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Sebastopol, CA
O'Reilly
[2021]
|
| Schriftenreihe: | Python/Finance
|
| Zusammenfassung: | Financial trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM platforms |
| Beschreibung: | xvii, 358 Seiten Diagramme |
| ISBN: | 9781492053354 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV047212750 | ||
| 003 | DE-604 | ||
| 005 | 20210430 | ||
| 007 | t | ||
| 008 | 210325s2021 |||| |||| 00||| eng d | ||
| 020 | |a 9781492053354 |9 978-1-492-05335-4 | ||
| 035 | |a (OCoLC)1245332221 | ||
| 035 | |a (DE-599)BVBBV047212750 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-523 | ||
| 084 | |a ST 250 |0 (DE-625)143626: |2 rvk | ||
| 100 | 1 | |a Hilpisch, Yves |e Verfasser |0 (DE-588)122757831 |4 aut | |
| 245 | 1 | 0 | |a Python for Algorithmic Trading |b from idea to cloud development |c Yves Hilpisch |
| 264 | 1 | |a Sebastopol, CA |b O'Reilly |c [2021] | |
| 300 | |a xvii, 358 Seiten |b Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Python/Finance | |
| 520 | 3 | |a Financial trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM platforms | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-032617529 | ||
Datensatz im Suchindex
| _version_ | 1804182328237359104 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Hilpisch, Yves |
| author_GND | (DE-588)122757831 |
| author_facet | Hilpisch, Yves |
| author_role | aut |
| author_sort | Hilpisch, Yves |
| author_variant | y h yh |
| building | Verbundindex |
| bvnumber | BV047212750 |
| classification_rvk | ST 250 |
| ctrlnum | (OCoLC)1245332221 (DE-599)BVBBV047212750 |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02171nam a2200289 c 4500</leader><controlfield tag="001">BV047212750</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20210430 </controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">210325s2021 |||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781492053354</subfield><subfield code="9">978-1-492-05335-4</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1245332221</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047212750</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-523</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 250</subfield><subfield code="0">(DE-625)143626:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hilpisch, Yves</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)122757831</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Python for Algorithmic Trading</subfield><subfield code="b">from idea to cloud development</subfield><subfield code="c">Yves Hilpisch</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Sebastopol, CA</subfield><subfield code="b">O'Reilly</subfield><subfield code="c">[2021]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">xvii, 358 Seiten</subfield><subfield code="b">Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Python/Finance</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Financial trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM platforms</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-032617529</subfield></datafield></record></collection> |
| id | DE-604.BV047212750 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:54:54Z |
| indexdate | 2024-07-10T09:05:48Z |
| institution | BVB |
| isbn | 9781492053354 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032617529 |
| oclc_num | 1245332221 |
| open_access_boolean | |
| owner | DE-523 |
| owner_facet | DE-523 |
| physical | xvii, 358 Seiten Diagramme |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | O'Reilly |
| record_format | marc |
| series2 | Python/Finance |
| spelling | Hilpisch, Yves Verfasser (DE-588)122757831 aut Python for Algorithmic Trading from idea to cloud development Yves Hilpisch Sebastopol, CA O'Reilly [2021] xvii, 358 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Python/Finance Financial trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM platforms |
| spellingShingle | Hilpisch, Yves Python for Algorithmic Trading from idea to cloud development |
| title | Python for Algorithmic Trading from idea to cloud development |
| title_auth | Python for Algorithmic Trading from idea to cloud development |
| title_exact_search | Python for Algorithmic Trading from idea to cloud development |
| title_exact_search_txtP | Python for Algorithmic Trading from idea to cloud development |
| title_full | Python for Algorithmic Trading from idea to cloud development Yves Hilpisch |
| title_fullStr | Python for Algorithmic Trading from idea to cloud development Yves Hilpisch |
| title_full_unstemmed | Python for Algorithmic Trading from idea to cloud development Yves Hilpisch |
| title_short | Python for Algorithmic Trading |
| title_sort | python for algorithmic trading from idea to cloud development |
| title_sub | from idea to cloud development |
| work_keys_str_mv | AT hilpischyves pythonforalgorithmictradingfromideatoclouddevelopment |