Search icon Close icon
Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Checkout

Change country

Modal Close icon
Country selected Country selected
country flag Germany
Country selected
country flag Slovakia
Country selected
country flag Canada
Country selected
country flag Brazil
Country selected
country flag Singapore
Country selected
country flag Hungary
Country selected
country flag Philippines
Country selected
country flag Mexico
Country selected
country flag Thailand
Country selected
country flag Ukraine
Country selected
country flag Luxembourg
Country selected
country flag Estonia
Country selected
country flag Lithuania
Country selected
country flag Norway
Country selected
country flag Chile
Country selected
country flag United States
Country selected
country flag Great Britain
Country selected
country flag India
Country selected
country flag Spain
Country selected
country flag South Korea
Country selected
country flag Ecuador
Country selected
country flag Colombia
Country selected
country flag Taiwan
Country selected
country flag Switzerland
Country selected
country flag Indonesia
Country selected
country flag Cyprus
Country selected
country flag Denmark
Country selected
country flag Finland
Country selected
country flag Poland
Country selected
country flag Malta
Country selected
country flag Czechia
Country selected
country flag New Zealand
Country selected
country flag Austria
Country selected
country flag Turkey
Country selected
country flag France
Country selected
country flag Sweden
Country selected
country flag Italy
Country selected
country flag Egypt
Country selected
country flag Belgium
Country selected
country flag Portugal
Country selected
country flag Slovenia
Country selected
country flag Ireland
Country selected
country flag Romania
Country selected
country flag Greece
Country selected
country flag Argentina
Country selected
country flag Malaysia
Country selected
country flag South Africa
Country selected
country flag Netherlands
Country selected
country flag Bulgaria
Country selected
country flag Latvia
Country selected
country flag Australia
Country selected
country flag Japan
Country selected
country flag Russia
Country selected
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Home > Data > Data Analysis > Python for Algorithmic Trading Cookbook
Python for Algorithmic Trading Cookbook
Python for Algorithmic Trading Cookbook

Python for Algorithmic Trading Cookbook: Recipes for designing, building, and deploying algorithmic trading strategies with Python

Arrow left icon
Profile Icon Jason Strimpel
Arrow right icon
₱3061.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (15 Ratings)
Paperback Aug 2024 404 pages 1st Edition
eBook
₱1714.98 ₱2449.99
Paperback
₱3061.99
Subscription
Free Trial
Arrow left icon
Profile Icon Jason Strimpel
Arrow right icon
₱3061.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (15 Ratings)
Paperback Aug 2024 404 pages 1st Edition
eBook
₱1714.98 ₱2449.99
Paperback
₱3061.99
Subscription
Free Trial
eBook
₱1714.98 ₱2449.99
Paperback
₱3061.99
Subscription
Free Trial

What do you get with Print?

Product feature icon Instant access to your digital eBook copy whilst your Print order is Shipped
Product feature icon Colour book shipped to your preferred address
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR

Contact Details

Modal Close icon
Payment Processing...
tick Completed

Shipping Address

Billing Address

Shipping Methods
Table of content icon View table of contents Preview book icon Preview Book

Python for Algorithmic Trading Cookbook

Analyze and Transform Financial Market Data with pandas

The pandas library was invented by Wes McKinney while at the investment management firm AQR Capital Management, where he researched macro and credit trading strategies. He built pandas to provide flexible, easy-to-use data structures for data analysis. Since it was open sourced in 2009, pandas has become the standard tool to analyze and transform data using Python.

pandas is well-suited for working with tabular data, like that stored in spreadsheets or databases, and it integrates well with many other data analysis libraries in the Python ecosystem. Its capabilities extend to handling missing data, reshaping datasets, and merging and joining datasets, and it also provides robust tools for loading data from flat files, Excel files, databases, and HDF5 file formats. It’s widely used in academia, finance, and many areas of business due to its rich features and ease of use.

This chapter will begin by covering recipes...

Diving into pandas index types

The Index is an immutable sequence that’s used for indexing and alignment that serves as the label or key for rows in the DataFrame or elements in a series. It allows for fast lookup and relational operations and as of pandas version 2, it can contain values of any type, including integers, strings, and even tuples. Indexes in pandas are immutable, which makes them safe to share across multiple DataFrames or Series. They also have several built-in methods for common operations, such as sorting, grouping, and set operations such as union and intersection. pandas supports multiple indexes, allowing for complex, hierarchical data organization. This feature is particularly useful when dealing with high-dimensional data such as option chains. We’ll see examples of MultiIndexes later in this chapter.

There are seven types of pandas indexes. The differences are dependent on the type of data used to create the index. For example, an Int64Index...

Analyze and Transform Financial Market Data with pandas

The pandas library was invented by Wes McKinney while at the investment management firm AQR Capital Management, where he researched macro and credit trading strategies. He built pandas to provide flexible, easy-to-use data structures for data analysis. Since it was open sourced in 2009, pandas has become the standard tool to analyze and transform data using Python.

pandas is well-suited for working with tabular data, like that stored in spreadsheets or databases, and it integrates well with many other data analysis libraries in the Python ecosystem. Its capabilities extend to handling missing data, reshaping datasets, and merging and joining datasets, and it also provides robust tools for loading data from flat files, Excel files, databases, and HDF5 file formats. It’s widely used in academia, finance, and many areas of business due to its rich features and ease of use.

This chapter will begin by covering recipes...

Diving into pandas index types

The Index is an immutable sequence that’s used for indexing and alignment that serves as the label or key for rows in the DataFrame or elements in a series. It allows for fast lookup and relational operations and as of pandas version 2, it can contain values of any type, including integers, strings, and even tuples. Indexes in pandas are immutable, which makes them safe to share across multiple DataFrames or Series. They also have several built-in methods for common operations, such as sorting, grouping, and set operations such as union and intersection. pandas supports multiple indexes, allowing for complex, hierarchical data organization. This feature is particularly useful when dealing with high-dimensional data such as option chains. We’ll see examples of MultiIndexes later in this chapter.

There are seven types of pandas indexes. The differences are dependent on the type of data used to create the index. For example, an Int64Index...

Building pandas Series and DataFrames

A Series is a one-dimensional labeled array that can hold any data type, including integers, floats, strings, and objects. The axis labels of a Series are collectively referred to as the index, which allows for easy data manipulation and access. A key feature of the pandas Series is its ability to handle missing data, represented as a NumPy nan (Not a Number).

Important

NumPy’s nan is a special floating-point value. It is commonly used as a marker for missing data in numerical datasets. The nan value being a float is useful because it can be used in numerical computations and included in arrays of numbers without changing their data type, which aids in maintaining consistent data types in numeric datasets. Unlike other values, nan doesn’t equal anything, which is why we need to use functions such as numpy.isnan() to check for nan.

Furthermore, the Series object provides a host of methods for operations such as statistical...

Manipulating and transforming DataFrames

Before moving on to more advanced recipes, it’s important to understand the fundamentals of working with data. DataFrames are the most common pandas data structures you’ll work with. Despite the existence of hundreds of methods for DataFrame manipulation, only a subset of these are regularly used.

In this recipe, we will show you how to manipulate a DataFrame using the following common methods:

  • Creating new columns using aggregates, Booleans, and strings
  • Concatenating two DataFrames together
  • Pivoting a DataFrame such as Excel
  • Grouping data on a key or index and applying an aggregate
  • Joining options data together to create straddle prices

Getting ready…

We’ll start by importing the necessary libraries and downloading market price data:

  1. Start by importing NumPy, pandas, and the OpenBB Platform:
    import numpy as np
import pandas as pd
from openbb import obb
obb.user.preferences...

Examining and selecting data from DataFrames

Once you’ve loaded, manipulated, and transformed data in DataFrames, the next step is retrieving the data from DataFrames. This is where indexing and selecting data come into play. This functionality allows you to access data using methods such as iloc and loc and techniques such as Boolean indexing or query functions. These methods can target data based on its position, labels, or condition based on whether you’re after a specific row, column, or combination. Inspection enables potential issues to be identified, such as missing values, outliers, or inconsistencies, that can affect analysis and modeling. Additionally, an initial inspection provides insights into the nature of data, helping determine appropriate preprocessing steps and analysis methods.

How to do it…

Let’s start by downloading stock price data:

  1. Start by importing pandas and the OpenBB Platform:
    import pandas as pd
from openbb import...

Calculating asset returns using pandas

Returns are integral to understanding the performance of a portfolio. There are two types: simple returns and compound (or log) returns.

Simple returns, which are calculated as the difference in price from one period to the next divided by the price at the beginning of the period, are beneficial in certain circumstances. They aggregate across assets, meaning the simple return of a portfolio is the aggregate of the returns of the individual assets, weighted according to their proportions. This trait makes simple returns practical for comparing assets and evaluating portfolio performance over short-term intervals.

Simple returns are defined as follows:

R t =  P t − P t−1 _ P t−1  =  P t _ P t−1  − 1

On the other hand, compound returns, which are calculated using the natural logarithm of the price-relative change, are additive over...

Measuring the volatility of a return series

Volatility plays an integral role in finance, serving as a key indicator of risk linked to a particular asset. A higher degree of volatility suggests a greater risk associated with the asset as it indicates more significant price changes and, therefore, a less predictable investment outcome.

Standard deviation is widely used as the measure of asset return volatility. It statistically quantifies the dispersion of asset returns from their mean, thus providing an effective metric for risk. When asset returns exhibit a larger standard deviation, it signifies more pronounced volatility, pointing to a higher risk level. Conversely, a lower standard deviation implies that the asset returns are more stable and less likely to deviate significantly from their average, indicating a lower risk.

The standard deviation’s value as a risk measure extends beyond its ability to quantify risk alone. It is a common component in calculating risk...

Generating a cumulative return series

Cumulative returns quantify the total change in the value of an investment over a specific period. To compute the cumulative return of a series of simple single-period returns, you need to add 1 to each return, then multiply these results together, and finally subtract 1 from the product. Recall the formula for the simple return:

R t =  P t − P t−1 _ P t−1  =  P t _ P t−1  − 1

Upon writing ( P t _ P t−2) = ( P t _ P t−1)( P t−1 _ P t−2), the two-period return can be expressed as follows:

R(2) = ( P t _ P t−1 )( P t−1 _ P t−2 ) − 1

= (1 + R t)(1 + R t−1) − 1

To compute the cumulative return of a series of continuously...

Left arrow icon

Page 1 of 11

Right arrow icon
Download code icon Download Code

Key benefits

  • Follow practical Python recipes to acquire, visualize, and store market data for market research
  • Design, backtest, and evaluate the performance of trading strategies using professional techniques
  • Deploy trading strategies built in Python to a live trading environment with API connectivity
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

Discover how Python has made algorithmic trading accessible to non-professionals with unparalleled expertise and practical insights from Jason Strimpel, founder of PyQuant News and a seasoned professional with global experience in trading and risk management. This book guides you through from the basics of quantitative finance and data acquisition to advanced stages of backtesting and live trading. Detailed recipes will help you leverage the cutting-edge OpenBB SDK to gather freely available data for stocks, options, and futures, and build your own research environment using lightning-fast storage techniques like SQLite, HDF5, and ArcticDB. This book shows you how to use SciPy and statsmodels to identify alpha factors and hedge risk, and construct momentum and mean-reversion factors. You’ll optimize strategy parameters with walk-forward optimization using VectorBT and construct a production-ready backtest using Zipline Reloaded. Implementing all that you’ve learned, you’ll set up and deploy your algorithmic trading strategies in a live trading environment using the Interactive Brokers API, allowing you to stream tick-level data, submit orders, and retrieve portfolio details. By the end of this algorithmic trading book, you'll not only have grasped the essential concepts but also the practical skills needed to implement and execute sophisticated trading strategies using Python.

Who is this book for?

Python for Algorithmic Trading Cookbook equips traders, investors, and Python developers with code to design, backtest, and deploy algorithmic trading strategies. You should have experience investing in the stock market, knowledge of Python data structures, and a basic understanding of using Python libraries like pandas. This book is also ideal for individuals with Python experience who are already active in the market or are aspiring to be.

What you will learn

  • Acquire and process freely available market data with the OpenBB Platform
  • Build a research environment and populate it with financial market data
  • Use machine learning to identify alpha factors and engineer them into signals
  • Use VectorBT to find strategy parameters using walk-forward optimization
  • Build production-ready backtests with Zipline Reloaded and evaluate factor performance
  • Set up the code framework to connect and send an order to Interactive Brokers
Estimated delivery fee Deliver to Philippines

Standard delivery 10 - 13 business days

₱492.95

Premium delivery 5 - 8 business days

₱2548.95
(Includes tracking information)

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 16, 2024
Length: 404 pages
Edition : 1st
Language : English
ISBN-13 : 9781835084700
Category :
Data
Languages :
Python
Concepts :
Data Analysis
Tools :
Zipline

What do you get with Print?

Product feature icon Instant access to your digital eBook copy whilst your Print order is Shipped
Product feature icon Colour book shipped to your preferred address
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR

Contact Details

Modal Close icon
Payment Processing...
tick Completed

Shipping Address

Billing Address

Shipping Methods
Estimated delivery fee Deliver to Philippines

Standard delivery 10 - 13 business days

₱492.95

Premium delivery 5 - 8 business days

₱2548.95
(Includes tracking information)

Product Details

Publication date : Aug 16, 2024
Length: 404 pages
Edition : 1st
Language : English
ISBN-13 : 9781835084700
Category :
Data
Languages :
Python
Concepts :
Data Analysis
Tools :
Zipline

Packt Subscriptions

See our plans and pricing
Modal Close icon
$19.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
START FREE TRIAL
BUY NOW
$199.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just ₱5 each
Feature tick icon Exclusive print discounts
START FREE TRIAL
BUY NOW
$279.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just ₱5 each
Feature tick icon Exclusive print discounts
START FREE TRIAL
BUY NOW

Frequently bought together

Modern Time Series Forecasting with Python
Modern Time Series Forecasting with Python
Read more
Nov 2022 552 pages
Full star icon 4.2 (30)
eBook
eBook
  • eBook eBook ₱1513.99
  • Paperback Paperback ₱2704.99
₱1513.99 ₱2163.99
₱2704.99
Python Feature Engineering Cookbook
Python Feature Engineering Cookbook
Read more
Aug 2024 396 pages
eBook
eBook
  • eBook eBook ₱1284.99
  • Paperback Paperback ₱2296.99
₱1284.99 ₱1836.99
₱2296.99
Python for Algorithmic Trading Cookbook
Python for Algorithmic Trading Cookbook
Read more
Aug 2024 404 pages
Full star icon 4.6 (15)
eBook
eBook
  • eBook eBook ₱1714.98
  • Paperback Paperback ₱3061.99
₱1714.98 ₱2449.99
₱3061.99
Stars icon
Total ₱ 8,063.97
Modern Time Series Forecasting with Python
₱2704.99
Python Feature Engineering Cookbook
₱2296.99
Python for Algorithmic Trading Cookbook
₱3061.99
Total ₱ 8,063.97 Stars icon

Table of Contents

15 Chapters
Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries Chevron down icon Chevron up icon
Chapter 1: Acquire Free Financial Market Data with Cutting-Edge Python Libraries
Technical requirements
Working with stock market data with the OpenBB Platform
Fetching historic futures data with the OpenBB Platform
Navigating options market data with the OpenBB Platform
Harnessing factor data using pandas_datareader
Chapter 2: Analyze and Transform Financial Market Data with pandas Chevron down icon Chevron up icon
Chapter 2: Analyze and Transform Financial Market Data with pandas
Diving into pandas index types
Building pandas Series and DataFrames
Manipulating and transforming DataFrames
Examining and selecting data from DataFrames
Calculating asset returns using pandas
Measuring the volatility of a return series
Generating a cumulative return series
Resampling data for different time frames
Addressing missing data issues
Applying custom functions to analyze time series data
Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash Chevron down icon Chevron up icon
Chapter 3: Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash
Quickly visualizing data using pandas
Animating the evolution of the yield curve with Matplotlib
Plotting options implied volatility surfaces with Matplotlib
Visualizing statistical relationships with Seaborn
Creating an interactive PCA analytics dashboard with Plotly Dash
Chapter 4: Store Financial Market Data on Your Computer Chevron down icon Chevron up icon
Chapter 4: Store Financial Market Data on Your Computer
Storing data on disk in CSV format
Storing data on disk with SQLite
Storing data in a PostgreSQL database server
Storing data in ultra-fast HDF5 format
Chapter 5: Build Alpha Factors for Stock Portfolios Chevron down icon Chevron up icon
Chapter 5: Build Alpha Factors for Stock Portfolios
Identifying latent return drivers using principal component analysis
Finding and hedging portfolio beta using linear regression
Analyzing portfolio sensitivities to the Fama-French factors
Assessing market inefficiency based on volatility
Preparing a factor ranking model using Zipline Pipelines
Chapter 6: Vector-Based Backtesting with VectorBT Chevron down icon Chevron up icon
Chapter 6: Vector-Based Backtesting with VectorBT
Building technical strategies with VectorBT
Conducting walk-forward optimization with VectorBT
Optimizing the SuperTrend strategy with VectorBT Pro
Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded Chevron down icon Chevron up icon
Chapter 7: Event-Based Backtesting Factor Portfolios with Zipline Reloaded
Technical Requirements
Backtesting a momentum factor strategy with Zipline Reloaded
Exploring a mean reversion strategy with Zipline Reloaded
Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded Chevron down icon Chevron up icon
Chapter 8: Evaluate Factor Risk and Performance with Alphalens Reloaded
Preparing backtest results
Evaluating the information coefficient
Examining factor return performance
Evaluating factor turnover
Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio Chevron down icon Chevron up icon
Chapter 9: Assess Backtest Risk and Performance Metrics with Pyfolio
Preparing Zipline backtest results for Pyfolio Reloaded
Generating strategy performance and return analytics
Building a drawdown and rolling risk analysis
Analyzing strategy holdings, leverage, exposure, and sector allocations
Breaking Down Strategy Performance to Trade Level
Chapter 10: Set Up the Interactive Brokers Python API Chevron down icon Chevron up icon
Chapter 10: Set Up the Interactive Brokers Python API
Building an algorithmic trading app
Creating a Contract object with the IB API
Creating an Order object with the IB API
Fetching historical market data
Getting a market data snapshot
Streaming live market data
Storing live tick data in a local SQL database
Chapter 11: Manage Orders, Positions, and Portfolios with the IB API Chevron down icon Chevron up icon
Chapter 11: Manage Orders, Positions, and Portfolios with the IB API
Executing orders with the IB API
Managing orders once they’re placed
Getting details about your portfolio
Inspecting positions and position details
Computing portfolio profit and loss
Chapter 12: Deploy Strategies to a Live Environment Chevron down icon Chevron up icon
Chapter 12: Deploy Strategies to a Live Environment
Calculating real-time key performance and risk indicators
Sending orders based on portfolio targets
Deploying a monthly factor portfolio strategy
Deploying an options combo strategy
Deploying an intraday multi-asset mean reversion strategy
Chapter 13: Advanced Recipes for Market Data and Strategy Management Chevron down icon Chevron up icon
Chapter 13: Advanced Recipes for Market Data and Strategy Management
Streaming real-time options data with ThetaData
Using the ArcticDB DataFrame database for tick storage
Triggering real-time risk limit alerts
Storing trade execution details in a SQL database
Index Chevron down icon Chevron up icon
Index
Why subscribe?
Other Books You May Enjoy Chevron down icon Chevron up icon
Other Books You May Enjoy
Packt is searching for authors like you
Share Your Thoughts
Download a free PDF copy of this book

Recommendations for you

Left arrow icon
Python Machine Learning By Example
Python Machine Learning By Example
Read more
Jul 2024 518 pages
Full star icon 4.9 (8)
eBook
eBook
  • eBook eBook ₱1313.99
  • Paperback Paperback ₱2347.99
₱1313.99 ₱1877.99
₱2347.99
Unlocking Data with Generative AI and RAG
Unlocking Data with Generative AI and RAG
Read more
Sep 2024 346 pages
eBook
eBook
  • eBook eBook ₱1142.99
  • Paperback Paperback ₱2040.99
₱1142.99 ₱1632.99
₱2040.99
Building LLM Powered Applications
Building LLM Powered Applications
Read more
May 2024 342 pages
Full star icon 4.2 (22)
eBook
eBook
  • eBook eBook ₱1427.99
  • Paperback Paperback ₱2551.99
₱1427.99 ₱2040.99
₱2551.99
Python for Algorithmic Trading Cookbook
Python for Algorithmic Trading Cookbook
Read more
Aug 2024 404 pages
Full star icon 4.6 (15)
eBook
eBook
  • eBook eBook ₱1714.98
  • Paperback Paperback ₱3061.99
₱1714.98 ₱2449.99
₱3061.99
Machine Learning with PyTorch and Scikit-Learn
Machine Learning with PyTorch and Scikit-Learn
Read more
Feb 2022 774 pages
Full star icon 4.4 (95)
eBook
eBook
  • eBook eBook ₱1571.99
  • Paperback Paperback ₱2806.99
₱1571.99 ₱2245.99
₱2806.99
Artificial Intelligence Engines
Artificial Intelligence Engines
Read more
Nov 2024 217 pages
eBook
eBook
  • eBook eBook ₱342.98
₱342.98 ₱489.99
AI Product Manager's Handbook
AI Product Manager's Handbook
Read more
Nov 2024 484 pages
eBook
eBook
  • eBook eBook ₱1427.99
  • Paperback Paperback ₱2551.99
₱1427.99 ₱2040.99
₱2551.99
RAG-Driven Generative AI
RAG-Driven Generative AI
Read more
Sep 2024 334 pages
Full star icon 4.5 (13)
eBook
eBook
  • eBook eBook ₱1256.99
  • Paperback Paperback ₱2245.99
₱1256.99 ₱1796.99
₱2245.99
Hands-On Reinforcement Learning with Python
Hands-On Reinforcement Learning with Python
Read more
Jun 2018 318 pages
Full star icon 2.6 (18)
eBook
eBook
  • eBook eBook ₱1113.99
  • Paperback Paperback ₱1989.99
₱1113.99 ₱1591.99
₱1989.99
LLM Engineer's Handbook
LLM Engineer's Handbook
Read more
Oct 2024 522 pages
Full star icon 4.9 (14)
eBook
eBook
  • eBook eBook ₱2449.99
  • Paperback Paperback ₱3061.99
₱2449.99
₱3061.99
Right arrow icon

Customer reviews

Top Reviews
  • Top Reviews
  • Most Recent
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6
(15 Ratings)
5 star 86.7%
4 star 0%
3 star 6.7%
2 star 0%
1 star 6.7%
Filter icon Filter
Top Reviews
  • Top Reviews
  • Most Recent

Filter reviews by

Lucas Aug 17, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Subscriber review Packt
kasidit asavakittikawin Sep 09, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
"Python for Algorithmic Trading Cookbook" stands out as a practical and accessible guide for those seeking to enhance their algorithmic trading knowledge. The author's hands-on experience and understanding of the needs of beginners shine through in this well-structured book.Practical Approach: The book is filled with actionable Python recipes for acquiring, visualizing, storing, and analyzing market data. It walks readers through the entire process of designing, backtesting, and deploying trading strategies, making the complex world of algo trading manageable.Updated Data Sources: The book provides free and updated data sources, a valuable resource for those looking to apply the concepts in a real-world setting.
Amazon Verified review Amazon
Didier Lopes Sep 15, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
If you are starting using Python to do algorithmic trading - you should get this book. I recommend the paperback version personally, particularly to have it by your desk in a way that you can access it easily.The book is packed with clear, hands-on examples that make complex topics feel easy - Jason is one of the best people I know at doing this. That's why he has hundreds of thousands of followers and has had over 1000 students attending his cohorts.I also love how practical the book is. All theory has real-world examples that myself, as the reader, can use to better understand the topic at hand.It goes from basic technical analysis to more advanced strategies like machine learning, so there's a lot of room to grow your skills.If you're like me and appreciate learning by doing, this book is perfect. The code examples are super clear, and you can quickly get a strategy up and running or modify it to fit your own ideas.PS: I also particularly love that the book features OpenBB!
Amazon Verified review Amazon
Roger A. Strimpel Aug 29, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent book!!
Amazon Verified review Amazon
Amazon Customer Aug 24, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I thought this book was very insightful and excellent source for information. The charts were understandable!
Amazon Verified review Amazon

About the author

Profile icon Jason Strimpel
Jason Strimpel
LinkedIn icon Github icon
Jason Strimpel is the founder of PyQuant News and co-founder of Trade Blotter, with a career spanning over 20 years in trading, risk management, and data science. He previously traded for a Chicago-based hedge fund, served as a risk manager at JPMorgan, and managed production risk technology for an energy derivatives trading firm in London. In Singapore, Jason served as the APAC CIO for an agricultural trading firm and built the data science team for a global metals trading firm. He holds degrees in finance and economics and a Master's in quantitative finance from the Illinois Institute of Technology. His career has taken him across America, Europe, and Asia. Jason shares his expertise through the PyQuant Newsletter, social media, and teaches the course "Getting Started With Python for Quant Finance."
Read more
See other products by Jason Strimpel
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is the delivery time and cost of print book? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela
What is custom duty/charge? Chevron down icon Chevron up icon

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order? Chevron down icon Chevron up icon

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges? Chevron down icon Chevron up icon

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

  • If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
  • Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.
How can I cancel my order? Chevron down icon Chevron up icon

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy? Chevron down icon Chevron up icon

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

  1. If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
  2. Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
  3. You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
  4. Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
  5. If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
  6. Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged? Chevron down icon Chevron up icon

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use? Chevron down icon Chevron up icon

You can pay with the following card types:

  1. Visa Debit
  2. Visa Credit
  3. MasterCard
  4. PayPal
What is the delivery time and cost of print books? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela