عنوان
پدید آورنده
موضوع
رده
HG104
HG104
کتابخانه
محل استقرار
شابک
شابک
1789342716
شابک
9781789342710
شابک اشتباه
178934641X
شابک اشتباه
9781789346411
عنوان و نام پديدآور
عنوان اصلي
Hands-on machine learning for algorithmic trading :
نام عام مواد
[Book]
ساير اطلاعات عنواني
design and implement investment strategies based on smart algorithms that learn from data using Python /
نام نخستين پديدآور
Stefan Jansen.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Birmingham, UK :
نام ناشر، پخش کننده و غيره
Packt Publishing,
تاریخ نشرو بخش و غیره
2018.
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (1 volume) :
ساير جزييات
illustrations
یادداشتهای مربوط به مندرجات
متن يادداشت
Cover; Title Page; Copyright and Credits; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Machine Learning for Trading; How to read this book; What to expect; Who should read this book; How the book is organized; Part I - the framework - from data to strategy design; Part 2 - ML fundamentals; Part 3 - natural language processing; Part 4 -- deep and reinforcement learning; What you need to succeed; Data sources; GitHub repository; Python libraries; The rise of ML in the investment industry; From electronic to high-frequency trading; Factor investing and smart beta funds
متن يادداشت
Algorithmic pioneers outperform humans at scaleML driven funds attract 1 trillion AUM; The emergence of quantamental funds; Investments in strategic capabilities; ML and alternative data; Crowdsourcing of trading algorithms; Design and execution of a trading strategy; Sourcing and managing data; Alpha factor research and evaluation; Portfolio optimization and risk management; Strategy backtesting; ML and algorithmic trading strategies; Use Cases of ML for Trading ; Data mining for feature extraction; Supervised learning for alpha factor creation and aggregation; Asset allocation
متن يادداشت
Evaluating alternative datasetsEvaluation criteria; Quality of the signal content; Asset classes; Investment style; Risk premiums; Alpha content and quality; Quality of the data; Legal and reputational risks; Exclusivity; Time horizon; Frequency; Reliability; Technical aspects; Latency; Format; The market for alternative data; Data providers and use cases; Social sentiment data; Dataminr; StockTwits; RavenPack; Satellite data; Geolocation data; Email receipt data; Working with alternative data; Scraping OpenTable data; Extracting data from HTML using requests and BeautifulSoup
متن يادداشت
Other market-data providersHow to work with fundamental data; Financial statement data; Automated processing -- XBRL; Building a fundamental data time series; Extracting the financial statements and notes dataset; Retrieving all quarterly Apple filings; Building a price/earnings time series; Other fundamental data sources; pandas_datareader - macro and industry data; Efficient data storage with pandas; Summary; Chapter 3: Alternative Data for Finance; The alternative data revolution; Sources of alternative data; Individuals; Business processes; Sensors; Satellites; Geolocation data
متن يادداشت
Testing trade ideasReinforcement learning; Summary; Chapter 2: Market and Fundamental Data; How to work with market data; Market microstructure; Marketplaces; Types of orders; Working with order book data; The FIX protocol; Nasdaq TotalView-ITCH Order Book data; Parsing binary ITCH messages; Reconstructing trades and the order book; Regularizing tick data; Tick bars; Time bars; Volume bars; Dollar bars; API access to market data; Remote data access using pandas; Reading html tables; pandas-datareader for market data; The Investor Exchange ; Quantopian; Zipline; Quandl
بدون عنوان
0
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
With the help of this book, you'll build smart algorithmic models using machine learning algorithms covering tasks such as time series forecasting, backtesting, trade predictions, and more using easy-to-follow examples. By the end, you'll be able to adopt algorithmic trading in your own business and implement intelligent investigative strategies.
یادداشتهای مربوط به سفارشات
منبع سفارش / آدرس اشتراک
OverDrive, Inc.
منبع سفارش / آدرس اشتراک
Safari Books Online
شماره انبار
99B6A1DC-1E78-43C2-969E-8CB874E3827E
شماره انبار
CL0501000030
ویراست دیگر از اثر در قالب دیگر رسانه
عنوان
Hands-On Machine Learning for Algorithmic Trading : Design and Implement Investment Strategies Based on Smart Algorithms That Learn from Data Using Python
شماره استاندارد بين المللي کتاب و موسيقي
9781789346411
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Finance-- Data processing.
موضوع مستند نشده
Finance-- Statistical methods.
موضوع مستند نشده
Machine learning.
موضوع مستند نشده
Python (Computer program language)
موضوع مستند نشده
COMPUTERS / General.
موضوع مستند نشده
Finance-- Data processing.
موضوع مستند نشده
Finance-- Statistical methods.
موضوع مستند نشده
Machine learning.
موضوع مستند نشده
Python (Computer program language)
مقوله موضوعی
موضوع مستند نشده
COM-- 000000
رده بندی ديویی
شماره
006
.
31
ويراست
23
رده بندی کنگره
شماره رده
HG104
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
Jansen, Stefan
مبدا اصلی
تاريخ عمليات
20200823060654.0
قواعد فهرست نويسي ( بخش توصيفي )
pn
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب اطلاعات رکورد کتابشناسی
نوع ماده
[Book]
اطلاعات دسترسی رکورد
تكميل شده
Y
