語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Quantitative trading strategies usin...
~
Liu, Peng.
FindBook
Google Book
Amazon
博客來
Quantitative trading strategies using Python = technical analysis, statistical testing, and machine learning /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Quantitative trading strategies using Python/ by Peng Liu.
其他題名:
technical analysis, statistical testing, and machine learning /
作者:
Liu, Peng.
出版者:
Berkeley, CA :Apress : : 2023.,
面頁冊數:
xi, 337 p. :ill. (chiefly color), digital ;24 cm.
內容註:
Chapter 1: Introduction to Quantitative Trading -- Chapter 2: Understanding the Electronic Market -- Chapter 3: Understanding Risk and Return -- Chapter 4: Forward and Futures Contracts -- Chapter 5: Trend Following Strategy -- Chapter 6: Momentum Trading Strategy -- Chapter 7: Backtesting A Trading Strategy -- Chapter 8: Statistical Arbitrage with Hypothesis Testing -- Chapter 9: Optimizing Trading Strategies with Bayesian Optimization -- Chapter 10: Optimizing Trading Strategies with Machine Learning.
Contained By:
Springer Nature eBook
標題:
Electronic trading of securities. -
電子資源:
https://doi.org/10.1007/978-1-4842-9675-2
ISBN:
9781484296752
Quantitative trading strategies using Python = technical analysis, statistical testing, and machine learning /
Liu, Peng.
Quantitative trading strategies using Python
technical analysis, statistical testing, and machine learning /[electronic resource] :by Peng Liu. - Berkeley, CA :Apress :2023. - xi, 337 p. :ill. (chiefly color), digital ;24 cm.
Chapter 1: Introduction to Quantitative Trading -- Chapter 2: Understanding the Electronic Market -- Chapter 3: Understanding Risk and Return -- Chapter 4: Forward and Futures Contracts -- Chapter 5: Trend Following Strategy -- Chapter 6: Momentum Trading Strategy -- Chapter 7: Backtesting A Trading Strategy -- Chapter 8: Statistical Arbitrage with Hypothesis Testing -- Chapter 9: Optimizing Trading Strategies with Bayesian Optimization -- Chapter 10: Optimizing Trading Strategies with Machine Learning.
Build and implement trading strategies using Python. This book will introduce you to the fundamental concepts of quantitative trading and shows how to use Python and popular libraries to build trading models and strategies from scratch. It covers practical trading strategies coupled with step-by-step implementations that touch upon a wide range of topics, including data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning, all coupled with practical examples in Python. Part one of Quantitative Trading Strategies with Python covers the fundamentals of trading strategies, including an introduction to quantitative trading, the electronic market, risk and return, and forward and futures contracts. Part II introduces common trading strategies, including trend-following, momentum trading, and evaluation process via backtesting. Part III covers more advanced topics, including statistical arbitrage using hypothesis testing, optimizing trading parameters using Bayesian optimization, and generating trading signals using a machine learning approach. Whether you're an experienced trader looking to automate your trading strategies or a beginner interested in learning quantitative trading, this book will be a valuable resource. Written in a clear and concise style that makes complex topics easy to understand, and chock full of examples and exercises to help reinforce the key concepts, you'll come away from it with a firm understanding of core trading strategies and how to use Python to implement them. You will: Master the fundamental concepts of quantitative trading Use Python and its popular libraries to build trading models and strategies from scratch Perform data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning for trading strategies using Python Utilize common trading strategies such as trend-following, momentum trading, and pairs trading Evaluate different quantitative trading strategies by applying the relevant performance measures and statistics in a scientific manner during backtesting.
ISBN: 9781484296752
Standard No.: 10.1007/978-1-4842-9675-2doiSubjects--Topical Terms:
721458
Electronic trading of securities.
LC Class. No.: QA76.73.P98 / L58 2023
Dewey Class. No.: 332.632283
Quantitative trading strategies using Python = technical analysis, statistical testing, and machine learning /
LDR
:03722nmm a2200325 a 4500
001
2334955
003
DE-He213
005
20230909104805.0
006
m d
007
cr nn 008maaau
008
240402s2023 cau s 0 eng d
020
$a
9781484296752
$q
(electronic bk.)
020
$a
9781484296745
$q
(paper)
024
7
$a
10.1007/978-1-4842-9675-2
$2
doi
035
$a
978-1-4842-9675-2
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.73.P98
$b
L58 2023
072
7
$a
UMX
$2
bicssc
072
7
$a
COM051360
$2
bisacsh
072
7
$a
UMX
$2
thema
082
0 4
$a
332.632283
$2
23
090
$a
QA76.73.P98
$b
L783 2023
100
1
$a
Liu, Peng.
$3
1005586
245
1 0
$a
Quantitative trading strategies using Python
$h
[electronic resource] :
$b
technical analysis, statistical testing, and machine learning /
$c
by Peng Liu.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2023.
300
$a
xi, 337 p. :
$b
ill. (chiefly color), digital ;
$c
24 cm.
505
0
$a
Chapter 1: Introduction to Quantitative Trading -- Chapter 2: Understanding the Electronic Market -- Chapter 3: Understanding Risk and Return -- Chapter 4: Forward and Futures Contracts -- Chapter 5: Trend Following Strategy -- Chapter 6: Momentum Trading Strategy -- Chapter 7: Backtesting A Trading Strategy -- Chapter 8: Statistical Arbitrage with Hypothesis Testing -- Chapter 9: Optimizing Trading Strategies with Bayesian Optimization -- Chapter 10: Optimizing Trading Strategies with Machine Learning.
520
$a
Build and implement trading strategies using Python. This book will introduce you to the fundamental concepts of quantitative trading and shows how to use Python and popular libraries to build trading models and strategies from scratch. It covers practical trading strategies coupled with step-by-step implementations that touch upon a wide range of topics, including data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning, all coupled with practical examples in Python. Part one of Quantitative Trading Strategies with Python covers the fundamentals of trading strategies, including an introduction to quantitative trading, the electronic market, risk and return, and forward and futures contracts. Part II introduces common trading strategies, including trend-following, momentum trading, and evaluation process via backtesting. Part III covers more advanced topics, including statistical arbitrage using hypothesis testing, optimizing trading parameters using Bayesian optimization, and generating trading signals using a machine learning approach. Whether you're an experienced trader looking to automate your trading strategies or a beginner interested in learning quantitative trading, this book will be a valuable resource. Written in a clear and concise style that makes complex topics easy to understand, and chock full of examples and exercises to help reinforce the key concepts, you'll come away from it with a firm understanding of core trading strategies and how to use Python to implement them. You will: Master the fundamental concepts of quantitative trading Use Python and its popular libraries to build trading models and strategies from scratch Perform data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning for trading strategies using Python Utilize common trading strategies such as trend-following, momentum trading, and pairs trading Evaluate different quantitative trading strategies by applying the relevant performance measures and statistics in a scientific manner during backtesting.
650
0
$a
Electronic trading of securities.
$3
721458
650
0
$a
Python (Computer program language)
$3
729789
650
1 4
$a
Python.
$3
3201289
650
2 4
$a
Financial Services.
$3
2194957
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
856
4 0
$u
https://doi.org/10.1007/978-1-4842-9675-2
950
$a
Professional and Applied Computing (SpringerNature-12059)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9461160
電子資源
11.線上閱覽_V
電子書
EB QA76.73.P98 L58 2023
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入