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Investing for Programmers: Understanding markets through data and code
Maximize your portfolio, analyze markets, and make data-driven investment decisions using Python and generative AI.
Investing for Programmers shows you how you can turn your existing skills as a programmer into a knack for making sharper investment choices. You’ll learn how to use the Python ecosystem, modern analytic methods, and cutting-edge AI tools to make better decisions and improve the odds of long-term financial success.
In Investing for Programmers you’ll learn how
• Build stock analysis tools and predictive models
• Identify market-beating investment opportunities
• Design and evaluate algorithmic trading strategies
• Use AI to automate investment research
• Analyze market sentiments with media data mining
In Investing for Programmers you'll learn the basics of financial investment as you conduct real market analysis, connect with trading APIs to automate buy-sell, and develop a systematic approach to risk management. Don’t worry—there’s no dodgy financial advice or flimsy get-rich-quick schemes. Real-life examples help you build your own intuition about financial markets, and make better decisions for retirement, financial independence, and getting more from your hard-earned money.
About the technology
A programmer has a unique edge when it comes to investing. Using open-source Python libraries and AI tools, you can perform sophisticated analysis normally reserved for expensive financial professionals. This book guides you step-by-step through building your own stock analysis tools, forecasting models, and more so you can make smart, data-driven investment decisions.
About the book
Investing for Programmers shows you how to analyze investment opportunities using Python and machine learning. In this easy-to-read handbook, experienced algorithmic investor Stefan Papp shows you how to use Pandas, NumPy, and Matplotlib to dissect stock market data, uncover patterns, and build your own trading models. You’ll also discover how to use AI agents and LLMs to enhance your financial research and decision-making process.
What's inside
• Build stock analysis tools and predictive models
• Design algorithmic trading strategies
• Use AI to automate investment research
• Analyze market sentiment with media data mining
About the reader
For professional and hobbyist Python programmers with basic personal finance experience.
About the author
Stefan Papp combines 20 years of investment experience in stocks, cryptocurrency, and bonds with decades of work as a data engineer, architect, and software consultant.
Table of Contents
1 The analytical investor
2 Investment essentials
3 Collecting data
4 Growth portfolios
5 Income portfolios
6 Building an asset monitor
7 Risk management
8 AI for financial research
9 AI agents
10 Charts and technical analysis
11 Algorithmic trading
12 Private Investing in start-ups
13 The road goes ever on and on
A Setting up the environment
Investing for Programmers shows you how you can turn your existing skills as a programmer into a knack for making sharper investment choices. You’ll learn how to use the Python ecosystem, modern analytic methods, and cutting-edge AI tools to make better decisions and improve the odds of long-term financial success.
In Investing for Programmers you’ll learn how
• Build stock analysis tools and predictive models
• Identify market-beating investment opportunities
• Design and evaluate algorithmic trading strategies
• Use AI to automate investment research
• Analyze market sentiments with media data mining
In Investing for Programmers you'll learn the basics of financial investment as you conduct real market analysis, connect with trading APIs to automate buy-sell, and develop a systematic approach to risk management. Don’t worry—there’s no dodgy financial advice or flimsy get-rich-quick schemes. Real-life examples help you build your own intuition about financial markets, and make better decisions for retirement, financial independence, and getting more from your hard-earned money.
About the technology
A programmer has a unique edge when it comes to investing. Using open-source Python libraries and AI tools, you can perform sophisticated analysis normally reserved for expensive financial professionals. This book guides you step-by-step through building your own stock analysis tools, forecasting models, and more so you can make smart, data-driven investment decisions.
About the book
Investing for Programmers shows you how to analyze investment opportunities using Python and machine learning. In this easy-to-read handbook, experienced algorithmic investor Stefan Papp shows you how to use Pandas, NumPy, and Matplotlib to dissect stock market data, uncover patterns, and build your own trading models. You’ll also discover how to use AI agents and LLMs to enhance your financial research and decision-making process.
What's inside
• Build stock analysis tools and predictive models
• Design algorithmic trading strategies
• Use AI to automate investment research
• Analyze market sentiment with media data mining
About the reader
For professional and hobbyist Python programmers with basic personal finance experience.
About the author
Stefan Papp combines 20 years of investment experience in stocks, cryptocurrency, and bonds with decades of work as a data engineer, architect, and software consultant.
Table of Contents
1 The analytical investor
2 Investment essentials
3 Collecting data
4 Growth portfolios
5 Income portfolios
6 Building an asset monitor
7 Risk management
8 AI for financial research
9 AI agents
10 Charts and technical analysis
11 Algorithmic trading
12 Private Investing in start-ups
13 The road goes ever on and on
A Setting up the environment
- GenresFinance
368 pages, Paperback
Published October 14, 2025
About the author
Stefan Papp
14 books12 followersAuthor of four books... Now an avid reader. I live in Armenia, where I enjoy a great culture.
Not yet decided if I want to write a book again
Not yet decided if I want to write a book again
Ratings & Reviews
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Community Reviews
Displaying 1 - 2 of 2 reviews
April 5, 2026
I have read the full book - from cover to cover.
It was such a refreshing book to read, as it was a straightforward, no BS, and a no handwaving book. I am glad that this book exists.
This book is written with an attitude, a tone of a mentor, senior, or a friend who cares about you. S/he sits you down, and teaches you about investing, and shares with you ready-to-use Python snippets. This is what I like the most about this book.
This book doesn't have even an iota of toxic finance-bro energy that is common in many investing books.
This book isn't your guide to setting up an ultra-cool algorithmic trading software, or finding edges through secret means. It teaches you what is common and known, and how to use them in fitting scenarios.
One great thing about this book is that it assumes that you are a professional programmer, who is new to investing. So, it teaches you, with much care, the basics of markets, investing, and finance. So, someone new to programming will not feel out-of-depth.
The book covers Sharpe ratio, MACD, Markowitz portfolio theory, etc. and teaches you how to implement them from scratch in Python. There's a lot of ground covered in this book.
The author is deep into investing, and is well-read. Even though the book is about programming, the book is not devoid of traditional programming wisdom. The author has lived and is living the advices that are highly revered in this field - from greats like Peter Lynch, Warren Buffett, Charlie Munger, etc.
The book has a last chapter that includes investment lessons for mid to senior level programmers - private equity. I feel that this chapter was not needed, and the information can be found elsewhere. Verbal descriptions of what Series A, Series B, angel investors are or why failed entrepreneurs are valuable. But that is just one chapter, and the rest of the book is valuable and perfect.
This could be a very good book for a non-programmer, too. Investing and finance concepts are taught here with much care, and are described with ease. I will recommend the non-programming parts to my friends who want to get started with programming.
There is a chapter on agentic coding, and that also serves a decent introduction to agentic coding!
This book, through and through, is a champion of common sense, fighting emotions, having checks and balances - the sensible stuff.
There was one great aspect of this book - this book not only gives you concrete ways to do market research, executing orders, etc. but this book also teaches you how to use programming tools to augment your thinking rather than replacing it. Using simple Machine Learning algorithms for looking for undervalued stocks was something that when I came across it in the book, I was like, why didn't I come up with it? This kind of usage opens a whole door of possibilities for programmers and independent thinkers.
This book, although for programmers, teaches you basic candle patterns, basics of fundamental and technical analysis, etc.
The book is also great as a reference. You don't need to apply everything you learn here to your own investing. You can pick up the book when you need to look something up. The book, at the time of writing this review, is also very up-to-date. The names of websites, tools, libraries, etc. that you come to learn from this book are available on online communities, sure, but you will need an immersion period of 6-8 months to learn them. This book can teach those to you in mere weeks in which you finish this book.
This book touches upon many things that you can learn about if you are interested. The inclusion of these also make the book very valuable.
This book is very, very far from being a dry manual. It is a friendly, psychologically sound, technically strong piece of work that always comes with a 'why', and advices you to do the same.
I will highly recommend this book to programmers, beginner investors and experienced ones - all alike. Happy reading and thanks to the author.
It was such a refreshing book to read, as it was a straightforward, no BS, and a no handwaving book. I am glad that this book exists.
This book is written with an attitude, a tone of a mentor, senior, or a friend who cares about you. S/he sits you down, and teaches you about investing, and shares with you ready-to-use Python snippets. This is what I like the most about this book.
This book doesn't have even an iota of toxic finance-bro energy that is common in many investing books.
This book isn't your guide to setting up an ultra-cool algorithmic trading software, or finding edges through secret means. It teaches you what is common and known, and how to use them in fitting scenarios.
One great thing about this book is that it assumes that you are a professional programmer, who is new to investing. So, it teaches you, with much care, the basics of markets, investing, and finance. So, someone new to programming will not feel out-of-depth.
The book covers Sharpe ratio, MACD, Markowitz portfolio theory, etc. and teaches you how to implement them from scratch in Python. There's a lot of ground covered in this book.
The author is deep into investing, and is well-read. Even though the book is about programming, the book is not devoid of traditional programming wisdom. The author has lived and is living the advices that are highly revered in this field - from greats like Peter Lynch, Warren Buffett, Charlie Munger, etc.
The book has a last chapter that includes investment lessons for mid to senior level programmers - private equity. I feel that this chapter was not needed, and the information can be found elsewhere. Verbal descriptions of what Series A, Series B, angel investors are or why failed entrepreneurs are valuable. But that is just one chapter, and the rest of the book is valuable and perfect.
This could be a very good book for a non-programmer, too. Investing and finance concepts are taught here with much care, and are described with ease. I will recommend the non-programming parts to my friends who want to get started with programming.
There is a chapter on agentic coding, and that also serves a decent introduction to agentic coding!
This book, through and through, is a champion of common sense, fighting emotions, having checks and balances - the sensible stuff.
There was one great aspect of this book - this book not only gives you concrete ways to do market research, executing orders, etc. but this book also teaches you how to use programming tools to augment your thinking rather than replacing it. Using simple Machine Learning algorithms for looking for undervalued stocks was something that when I came across it in the book, I was like, why didn't I come up with it? This kind of usage opens a whole door of possibilities for programmers and independent thinkers.
This book, although for programmers, teaches you basic candle patterns, basics of fundamental and technical analysis, etc.
The book is also great as a reference. You don't need to apply everything you learn here to your own investing. You can pick up the book when you need to look something up. The book, at the time of writing this review, is also very up-to-date. The names of websites, tools, libraries, etc. that you come to learn from this book are available on online communities, sure, but you will need an immersion period of 6-8 months to learn them. This book can teach those to you in mere weeks in which you finish this book.
This book touches upon many things that you can learn about if you are interested. The inclusion of these also make the book very valuable.
This book is very, very far from being a dry manual. It is a friendly, psychologically sound, technically strong piece of work that always comes with a 'why', and advices you to do the same.
I will highly recommend this book to programmers, beginner investors and experienced ones - all alike. Happy reading and thanks to the author.
February 28, 2026
This excellent book not only covers the theory behind various investment approaches but also provides code to help readers evaluate and identify trading opportunities. By using historical stock data, it allows anyone to easily test the discussed strategies. This combination of theory and practice is refreshing and helps a lot.
Displaying 1 - 2 of 2 reviews