Python for Algorithmic Trading: From Idea to Cloud Deployment (Record no. 98800)

MARC details
000 -LEADER
fixed length control field 02169 a2200193 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 241122b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789385889547
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.74015
Cutter HIL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Hilpisch Yves
245 ## - TITLE STATEMENT
Title Python for Algorithmic Trading: From Idea to Cloud Deployment
250 ## - EDITION STATEMENT
Edition statement 1st Ed
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Shroff Publishers & Distributors Pvt. Ltd.
Date of publication, distribution, etc 2020
Place of publication, distribution, etc Mumbai
300 ## - PHYSICAL DESCRIPTION
Extent 380
520 ## - Remark
Summary, etc Algorithmic 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.<br/><br/>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.<br/><br/>Set up a proper Python environment for algorithmic trading<br/>Learn how to retrieve financial data from public and proprietary data sources<br/>Explore vectorization for financial analytics with NumPy and pandas<br/>Master vectorized backtesting of different algorithmic trading strategies<br/>Generate market predictions by using machine learning and deep learning<br/>Tackle real-time processing of streaming data with socket programming tools<br/>Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms<br/><br/>Source: https://www.amazon.in/Python-Algorithmic-Trading-Deployment-Grayscale/dp/9385889540/ref=sr_1_1?crid=14TGWI2N65QH5&dib=eyJ2IjoiMSJ9.OcFiY1GmgH5ovMPLRaSjug.__5wtBlGUudjgcd7Bps0lx3TSLLNQF1mnGXWzEW9C3g&dib_tag=se&keywords=9789385889547&qid=1732283612&sprefix=9781593276515%2Caps%2C243&sr=8-1
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Python
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithmic Trading
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a Business Analytics
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Item type Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Collection Type Programme Full call number Barcode Date last seen Date last borrowed Cost, replacement price Koha item type
    Dewey Decimal Classification     Main Library Main Library Analytics 28/10/2024 Shroff Publishers 1180.00 Foreign Book   005.74015 HIL 119568 17/03/2025 27/02/2025 1475.00 Book

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