By Chainika Thakar (Previously written by Sushant Ratnaparkhi)
When you are eager to learn something new, you start seeking out everything related to the learning of that subject. If you're interested in Algorithmic Trading, you probably have a bunch of questions buzzing in your mind, like:
- Where can I find algorithmic trading books?
- Are there any free algorithmic trading books?
- Where can I find a list of essential algorithmic trading books?
- What are the best algorithmic trading books?
These are some common questions that flood popular forums from aspiring novice algorithmic traders worldwide. If you are aiming to become a trader, picking up an algorithmic trading book is a fantastic starting point. In this article, we will highlight the key areas aspiring quants should focus on and recommend some excellent reads.
Now, let us walk through the following broad categories in which you will find some of the essential Algorithmic Trading books:
- Books on Market Microstructure
- Books on Statistics & Econometrics
- Books on Technical Analysis
- Books on Options Trading
- Books on Advanced Statistics
- Books on Machine Learning
- Books on Python for Algorithmic Trading
- Books on Portfolio Management
Books on Market Microstructure
Market microstructure refers to the study of the processes and systems that facilitate trading in financial markets. Understanding market microstructure is crucial for anyone interested in algorithmic trading, as it provides insights into the mechanics of how orders are processed, how prices are determined, and the behaviour of different market participants.
If you're looking to deepen your knowledge in this area, here are some essential and famous books on market microstructure:
"Market Microstructure Theory" by Maureen O'Hara
This book offers a comprehensive introduction to the theoretical aspects of market microstructure, covering key concepts such as order flow, market making, and information asymmetry. The book introduces readers to the general issues and problems in market microstructure and further delves into inventory, information-based, and strategic trader models of informed and uninformed traders. The concluding chapters in the book provide details regarding the relationship between information, pricing process and liquidity along with the similarities and dissimilarities between several financial markets.
"Trading and Exchanges: Market Microstructure for Practitioners" by Larry Harris
A practical guide that explains how markets work, designed for traders, investors, and anyone interested in understanding the dynamics of trading and exchanges. Larry Harris addresses various market structures, including auction markets and dealer markets, explaining their unique characteristics. The book details how orders are processed, the role of intermediaries, and the impact of different trading systems on market dynamics. Moreover, it covers price formation, discussing how prices are determined and the factors influencing price changes.
Additionally, the behaviour and strategies of various market players, such as retail and institutional investors, are analysed, along with the regulatory environment and its implications for market operation. Real-world examples and practical insights make this book a valuable resource.
"An Introduction to High-Frequency Finance" by Ramazan Gençay, Michel Dacorogna, Ulrich A. Müller, Richard B. Olsen, and Olivier Pictet
This book focuses on the high-frequency finance aspect of market microstructure, providing insights into the statistical properties of high-frequency data and the mechanics of high-speed trading.
The book delves into the unique statistical properties of high-frequency financial data, which are essential for understanding how prices are formed and how trades are executed in real-time. It examines the impact of high-frequency trading on market dynamics, liquidity, and efficiency, which are core elements of market microstructure. By analysing volatility, autocorrelation, and distribution patterns at high frequencies, the authors provide insights into the micro-level interactions within the market.
Furthermore, the book discusses the technological infrastructure necessary for high-frequency trading, including hardware, software, and network systems, highlighting how technological advancements influence market microstructure. The techniques for modelling high-frequency data and identifying trading patterns are crucial for developing strategies that can navigate the intricacies of market microstructure effectively.
"The Microstructure of Financial Markets" by Frank de Jong and Barbara Rindi
A detailed exploration of financial market microstructure, discussing the role of information, the impact of trading on prices, and the behaviour of market participants. This book provides a comprehensive examination of the financial market microstructure, focusing on the intricate details of how markets operate and the factors that influence trading and price behaviour. The authors investigate how information is reflected in prices and the role of information asymmetry in market behaviour. They analyse how different types of trades and trading strategies impact market prices and liquidity.
The book explores various market designs and their implications for trading efficiency and fairness. Additionally, the behaviour and strategies of different market participants, such as informed traders, noise traders, and market makers, are studied. The authors discuss empirical techniques for analysing as well as market data and testing microstructure theories, combining theoretical frameworks with empirical evidence to make the book useful for both academic research and practical market analysis.
"High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems" by Irene Aldridge
While focusing on high-frequency trading, this book delves into the microstructure elements that high-frequency traders exploit, making it a valuable resource for understanding the intricate details of market operations. Irene Aldridge provides a detailed exploration of the microstructure elements that high-frequency traders exploit. The book is a valuable resource for understanding the intricate details of market operations, aimed at financial professionals, traders, and anyone interested in algorithmic trading.
Aldridge explains the principles of high-frequency trading and the technological infrastructure required, including hardware, software, and network systems. The book covers various algorithmic strategies used in high-frequency trading, such as market making, arbitrage, and momentum strategies. Risk management techniques specific to high-frequency trading are also discussed, which helps traders mitigate potential losses.
"Algorithmic Trading: A Rough & Ready Guide" by Vivek Krishnamoorthy and Ashutosh Dave (FREE)
This book explores the domain of algorithmic trading by briefly exploring its history and terminology. Then it takes the readers towards the discussion of pros and cons of automated trading. Furthermore, the book provides illustrative examples to elaborate on the components needed to create a robust trading system. With some key algorithmic trading strategies covered, it will give you a taste of what’s in store for those more interested.
Consisting of the skill sets needed to build a career in this domain or start your own trading desk, this book is a comprehensive read. In the end, you will also find the reading list and resources for diving deeper into automated trading for beginners.
"Algorithmic Trading: Winning Strategies and their Rationale" by Dr. Ernest P. Chan
This book serves as a practical guide to Algorithmic Trading strategies that can be implemented by both retail and institutional traders. Dr. Ernest Chan has covered a wide array of simple and linear strategies in this book. It starts with a chapter on backtesting and automated execution and covers the mean reversion strategies and their implementation for stocks, ETFs, currencies, and futures. Dr. Ernest Chan has also devoted chapters in the book to intraday momentum strategies. The book concludes with a chapter on risk management.
"Algorithmic Trading and DMA: An Introduction to Direct Access Trading Strategies" by Barry Johnson
This book is a comprehensive guide on Algorithmic Trading and Direct Market Access (DMA) for buy and sell-side traders. The book contains detailed chapters on topics like:
- orders,
- trading algorithms (TWAP, VWAP, Implementation Shortfall, and Adaptive Shortfall etc.),
- transaction costs,
- strategy execution tactics,
- advanced trading strategies, and other topics.
Okay, now let’s head to another main category of Algorithmic Trading books, which is Statistics & Econometrics.
Books on Statistics and Econometrics
Since Algorithmic Trading has become so competitive, Statistics and Econometrics provide the base for systematic trading and organised trading. For predicting the trade in the market this systematic trading system uses time series analysis and other statistical models. Moreover, if you are looking to be hired in a quant firm, you need to have a sound knowledge of Maths and Statistics.
It is an essential skill desired by new firms and hence, the following books on Statistics & Econometrics are good to start with:
"Basic Econometrics" by Damodar N. Gujarati
A well-regarded introductory textbook that makes econometrics accessible to students with a basic understanding of statistics and mathematics. It covers the fundamental concepts and techniques used to analyse economic data and test economic theories. This book is known for its clear explanations, step-by-step examples, and focus on practical applications. It is a valuable resource for those wanting to understand how economic data is analysed and how econometric models are built and used.
"Applied Econometric Times Series" by Walter Enders
This book dives into modern time series analysis, assuming you have already taken an introductory course in multiple regression analysis. It delves into the theory behind difference equations, explaining why they're crucial for all time series models. The Box-Jenkins methodology takes centre stage, but the book also explores recent advancements like unit root tests and ARCH models.
Also, the book includes numerous examples and an accompanying data disk allows you to put the techniques you learn into practice.
"Schaum's Outline of Statistics and Econometrics" by Dominick Salvatore and Derrick Reagle
From introducing Statistics & Econometrics to adopting a problem-solving approach, this book covers everything you require for Algorithmic Trading. This book provides you with topics that include theory and principles, which are fully illustrated with examples. For the reader to be provided with ‘easy to understand’ information, this book covers numerous theoretical and practical problems with detailed step-by-step solutions.
"Analysis of Financial Time Series" by Ruey S. Tsay
If you want a book that can provide you with an introduction to Econometric models and their applications to modelling and prediction of financial time series data, then this is the one.
With this book, you’ll get to learn:
- Linear Time Series Analysis,
- Nonlinear Models,
- Multivariate Time Series Analysis,
- High-Frequency Data Analysis,
- Principal Component Analysis,
- State-Space Models,
- Kalman Filter and other related topics
Moreover, to make the application of the topics an easy task, this book has empirical examples demonstrating the application. Furthermore, another broad category covering some relevant books is Technical Analysis. Let us see which Algorithmic Trading books can be approached for learning and applying Technical Analysis.
Books on Technical Analysis
There is quite a wide usage of Technical analysis and technical indicators in trading. To use as additional filters in quantitative trading, technical indicators play an important role.
Not only the books on quantitative trading strategies by quants but also, the books on Technical Analysis find usage in Machine learning models where these are used as inputs.
"Technical Analysis of the Financial Markets" by John J. Murphy
This book is often considered the bible of technical analysis. John J. Murphy provides a comprehensive guide covering everything from the basics of chart construction to advanced technical indicators and pattern analysis.
It explains different types of charts, including bar, point-and-figure, and candlestick charts, and delves into technical indicators like moving averages, oscillators, and volume analysis. Murphy also explores the psychological aspects of trading, helping readers understand market sentiment and behaviour. This book is a must-read for anyone serious about understanding and applying technical analysis in financial markets.
"Japanese Candlestick Charting Techniques" by Steve Nison
Steve Nison's book is renowned for bringing the Japanese candlestick charting method to Western traders. It offers a thorough introduction to candlestick charts, explaining how to read and interpret various candlestick patterns. Nison covers the history of candlestick charting, its fundamental principles, and the most important patterns like doji, hammers, and shooting stars. He also discusses how to combine candlestick analysis with other technical tools to improve trading accuracy and effectiveness. This book is essential for traders looking to incorporate candlestick charting into their technical analysis toolkit.
"The Essential Application for Forecasting and Tracking Market Prices" by Thomas J. Dorsey
This extensive reference work by Thomas N. Bulkowski covers over 100 chart patterns, including classical patterns like head-and-shoulders, triangles, and flags. Each pattern is explained in detail, with statistical data on their performance, failure rates, and trading strategies. Bulkowski also includes event patterns, rare patterns, and failed patterns, providing a comprehensive resource for pattern recognition. The book is filled with real-world examples and practical tips, making it an invaluable tool for traders looking to refine their pattern recognition skills and enhance their trading strategies.
"Technical Analysis: The Complete Resource for Financial Market Technicians" by Charles D. Kirkpatrick II and Julie R. Dahlquist
This book is the official companion to the Chartered Market Technician (CMT) program. It offers an in-depth overview of technical analysis, covering a wide range of topics from the basics of charting to advanced technical indicators and trading systems. The authors explain key concepts like trend analysis, pattern recognition, and market cycles, supported by detailed illustrations and real-life examples. The book also addresses the psychological aspects of trading and provides practical advice on developing and implementing trading strategies. It's a comprehensive resource for anyone pursuing a career in technical analysis.
"Technical Analysis for Dummies" by Barbara Rockefeller
This accessible guide introduces the basics of technical analysis in a straightforward and easy-to-understand manner. Barbara Rockefeller explains essential concepts such as chart types, trend lines, support and resistance levels, and technical indicators. The book also covers trading systems and strategies, risk management, and the psychological aspects of trading. With practical examples and clear explanations, this book is ideal for beginners who want to get started with technical analysis without feeling overwhelmed by complex theories and jargon.
"Technical Analysis Using Multiple Timeframes" by Brian Shannon
Brian Shannon's book focuses on the concept of analysing price action using multiple timeframes to gain a better understanding of market trends and identify optimal entry and exit points. The author introduces his Squeeze Dynamics Theory, which integrates technical analysis across different timeframes. Shannon provides practical insights, real-world examples, and detailed explanations on how to use this approach to enhance trading performance. The book is particularly useful for traders looking to develop a more nuanced and comprehensive trading strategy.
"Technical Analysis of Stock Trends" by Robert D. Edwards and John Magee
First published in 1948, this classic book remains a foundational text in technical analysis. It focuses on trend analysis and chart patterns, explaining the principles behind price movements and how to identify major market trends using the Dow Theory. The book covers various chart types, including bar charts and point-and-figure charts, and explores a wide range of chart patterns such as triangles, head-and-shoulders, and double tops and bottoms. It's a seminal work that has influenced generations of traders and continues to be a valuable resource for understanding the fundamentals of technical analysis.
Moving forward, there is another very important category under Algorithmic Trading books known as ‘Options Trading’ which is necessary to be covered when it comes to learning Algorithmic Trading.
Books on Options Trading
Options and futures are highly traded instruments in the markets. Options trading has become extremely sophisticated. To learn about options trading is important for aspiring quants and traders to have a sound understanding of volatility, Greeks, and various options strategies.
To provide you with relevant references, we have listed down the following two books on Options Trading which you'll find useful.
"Options, Futures, and Other Derivatives" by John Hull
This book offers a contemporary perspective on the derivatives market. Hull tackles cutting-edge topics like the securitisation crisis, seamlessly blending theory with real-world application.
"Positional Option Trading: An Advanced Guide" by Euan Sinclair
This book goes beyond introductory options trading, providing the in-depth knowledge and advanced techniques that professional and experienced options traders need to succeed. The book delves into quantitative approaches for directional trading, risk management for option portfolios, and the robustness of the Black-Scholes-Merton model. Sinclair emphasises the importance of identifying profitable opportunities in a volatile environment filled with uncertainty. He explores concepts like volatility premium and earnings effects to help you develop a winning strategy. After reading this book, you can improve your trading performance and navigate challenging market conditions.
"Volatility Trading" by Euan Sinclair
This updated edition of the bestselling "Volatility Trading" by Euan Sinclair, a specialist in quantitative options strategies, equips you with the tools you need. Sinclair provides a clear, step-by-step approach to understanding key concepts like option pricing, volatility measurement, and risk management.
New to this edition are in-depth explorations of realized vs. implied volatility, profiting from the variance premium, and using options to navigate specific market conditions. Packed with practical models and fresh trading strategies, this book is your guide to mastering the art of volatility trading.
"Option Trading: Pricing and Volatility Strategies and Techniques" by Euan Sinclair
Claimed as an A-to-Z guide by Euan Sinclair, a professional trader and quantitative analyst, this book equips you with everything you need to know about options. Whether you're a seasoned pro or just starting out, this book covers everything from the basics (contract types, market structure) to advanced concepts (volatility measurement, hedging).
Packed with practical information, it delves into option pricing, forecasting techniques, and the all-important "Greeks" (delta, gamma, etc.) critical for understanding option behaviour. Sinclair also explores specific strategies for using options to hedge other holdings, manage risk, or profit from market inefficiencies.
"Option Volatility and Pricing" by Sheldon Natenberg
Explanation
Sheldon Natenberg's "Option Volatility and Pricing" is considered a definitive and comprehensive guide to understanding options volatility trading. It covers both the theoretical underpinnings of options pricing models and the practical aspects of implementing trading strategies. The book focuses extensively on the concept of volatility and its crucial role in determining options prices. Natenberg explains how traders can analyse and predict volatility trends, which is essential for crafting effective trading strategies.
This book is suitable for traders who already have a basic understanding of options but want to deepen their knowledge of how volatility impacts option prices. It's highly regarded among professionals for its clear explanations and practical insights into advanced options concepts.
"Options as a Strategic Investment" by Lawrence G. McMillan
Explanation
Lawrence G. McMillan's "Options as a Strategic Investment" is a comprehensive guide that covers a wide range of options trading strategies and their applications. It explores various ways to use options to hedge risk, generate income, and speculate in the market. The book includes detailed explanations of different options strategies, such as spreads, straddles, and collars, along with guidance on when and how to implement them based on market conditions.
This book is suitable for traders looking to expand their knowledge of options trading strategies. It's particularly valuable for those interested in learning about more advanced options techniques and how to integrate options into their overall investment strategy.
"The Options Playbook" by Brian Overby
Brian Overby's "The Options Playbook" is designed as a practical guide for beginners in options trading. It starts with the basics of options trading, explaining concepts such as calls, puts, and basic strategies like covered calls and protective puts. The book then progresses to more advanced strategies, providing clear explanations and real-life examples to illustrate each concept. It's known for its accessible writing style and hands-on approach to learning options trading. This book is ideal for beginners who are new to options trading and want a step-by-step guide to understanding and implementing different options strategies. It's also useful for more experienced traders looking to refresh their knowledge or simply explore new strategies.
These books cater to different levels of expertise and provide valuable insights into various aspects of options trading, from basic concepts to advanced strategies. Whether you are just starting or looking to deepen your understanding, these books offer practical knowledge and guidance to help you navigate the complexities of the options market.
Okay, now since some other categories serve the purpose when it comes to learning Algorithmic Trading, let us explore what books can be referred to for learning from the viewpoint of ‘Advanced Statistics’.
Books on Advanced Statistics
Advanced statistics is a concept for testing the relationship between two statistical datasets. It helps in organising and representing datasets consisting of numerical values. Generally, statistics deals with facts. In this, the facts are analysed, and then a dataset is created out of them. For Algorithmic Trading, the dataset plays an important role since the past dataset helps in predicting future values.
Now, let’s take a look at the books on Advanced Statistics that you can refer to for Algorithmic Trading:
"Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
This book is a complete package of important topics concerning statistical learning and finance. The authors have collectively worked on the content of this book with graphical representations and real-world examples. In this book, you will find the most relevant techniques with useful concepts.
The broad concepts include:
- Random forests
- Ensemble methods
- Least angle regression and
- Path algorithms for the lasso
- Non-negative matrix factorisation, and
- Spectral clustering
"Introduction to Statistical Thought" by Michael Lavine
This book consists of the knowledge of calculus for beginners and is also meant for all the students who are undergraduates. Also, anyone who has a good knowledge of calculus is sure to benefit from this book. Furthermore, this book makes use of computer calculations and simulation as a way of helping you learn in-depth topics.
"Statistical Inference" by George Casella and Roger L. Berger
"Statistical Inference" by Casella and Berger is a classic textbook that delves deep into the theoretical foundations of statistical inference. It covers topics such as hypothesis testing, estimation, Bayesian inference, and advanced methods like linear models and nonparametric inference. The book is known for its rigorous treatment of statistical theory, accompanied by numerous examples and exercises that help reinforce understanding. This book is ideal for graduate students and researchers in statistics, data science, and related fields who need a thorough understanding of statistical inference and its applications.
"All of Statistics: A Concise Course in Statistical Inference" by Larry Wasserman
Larry Wasserman's "All of Statistics" provides a comprehensive overview of statistical theory and its practical applications. It covers foundational concepts such as probability, random variables, sampling distributions, and statistical inference methods including parametric and nonparametric techniques. The book emphasises a concise and intuitive approach to understanding complex statistical concepts, making it accessible to both students and practitioners.
This book is suitable for undergraduate and graduate students in statistics, data science, and related fields as well as practitioners who want a thorough yet accessible reference on statistical methods. These books cover a range of advanced statistical topics, from theoretical foundations to practical applications, catering to different levels of expertise and interests in the field of statistics. Whether you are studying statistics academically or applying it professionally, these books provide valuable insights and knowledge to deepen your understanding of advanced statistical concepts.
Alright! Machine Learning is another critical category for making trading algorithms. Since it helps human beings by reducing their time and effort, you will see the books related to Machine Learning next.
Books on Machine Learning
Seen as a subset of Artificial Intelligence, the concept of Machine Learning is computational statistics, which implies using computers to make predictions. Machine learning is also known as predictive analysis since it uses computerised systems to analyse and predict the future values of a dataset. In this concept, initially, human intervention is required for programming the computer, but later the computer makes improvements and decisions on its own based on past data. Let us take a look at all these books now.
"Machine Learning in Trading: Step by step implementation of Machine Learning models" by Ishan Shah and Rekhit Pachanekar (FREE)
This book provides an elementary introduction to the world of machine learning, focusing on its foundational principles and real-life applications. The emphasis is that theory alone is insufficient for retaining knowledge; practical application is key. Therefore, this book includes numerous real-world examples, particularly in the field of trading. However, the concepts presented are transferable to any discipline that involves data analysis.
"Machine Learning for Asset Managers (Elements in Quantitative Finance)" by Marcos M. Lopez De Prado
This book covers the Machine Learning techniques popularly used by asset managers. The content emphasises the importance of investment theories and how Machine Learning (ML) can help discover them. ML offers advantages over traditional methods by focusing on real-world results, handling complexity, and identifying subtle data relationships.
"Quantitative Trading: How to Build Your Own Algorithmic Trading Business" by Dr. Ernest P. Chan
The completely revised "Quantitative Trading" by Dr. Chan equips you for success in algorithmic trading. Explore established and innovative strategies, then dive into using machine learning for investment analysis (with code examples!). The book even tackles adapting your strategies to changing markets and building a winning investment team. Whether you're a seasoned pro or just starting out, this book is your guide to navigating the world of algorithmic trading.
"Advances in Financial Machine Learning" by Marcos Lopez De Prado
This book will provide you with an in-depth knowledge of structuring big data, conducting research with Machine Learning algorithms and using computing methods which are much more improved. It has comprehensive content on real-life problems that are faced by those who use Machine Learning on a regular basis. You can even test the solutions in a particular setting and be equipped with powerful tools to succeed.
"Hands-On Machine Learning for Algorithmic Trading" by Stefan Jansen
This book helps you learn how to access the market and learn algorithms like Bayesian. Also, it gives you in-depth knowledge about using pandas, statsmodels, XGboost, lightgbm, etc. Furthermore, you learn to take out features from text data with spaCy. Learning includes the classification of news and sentiment scores. With this book, you also learn how to build and evaluate neural networks successfully. And, it will provide you with reinforcement learning for trading strategies in the OpenAI Gym.
"Neural Networks & Deep Learning" by Michael A. Nielsen (FREE)
This is an immersive online book to help you acquire knowledge in advanced ML concepts like Deep Learning and Neural Networks. This book covers Neural Networks and Deep Learning and also gives you the feel of an expert teaching you personally. Moreover, the diagrams and equations are explained elaborately with examples to make the learning better. You can also understand more about the applications of neural networks in trading and enhance your skills.
Okay! After Machine Learning, yet another important category to help you with Algorithmic Trading is Python language.
Books on Python for Algorithmic Trading
You all must have heard of or already know about the Python programming language, which is also being widely used in the domain of algorithmic and quantitative trading. Now, you will see all the books for learning Python for trading to make the best trading algorithms.
"Python Basics: With Illustrations From The Financial Markets" by Vivek Krishnamoorthy, Jay Parmar and Mario Pisa Peña (FREE)
To begin learning Python, you must refer to this book since it has everything for basic learning of Python. Moreover, with a lot of direct examples, you will gain a good understanding of the concepts. With this book, you can learn the most relevant information before starting to practically use Python.
This book is also meant for those programmers who want to quickly refresh their knowledge on Python for data analysis. One of the best parts is that it is available for FREE.
"Learn Python in One Day & Learn it Well" by Jamie Chan
What it says is what it does! This book provides everything you need to learn Python from the basic level to the advanced level. This is sure to provide you with a great foundation for later building advanced and specific models with libraries like Pandas, Numpy and Scipy.
Since it aims to provide you with everything relevant in brief yet quite informative, it makes the learning quick. The more you will practise the better you will become at using Python for data analysis and for creating algorithms.
"Pandas Cookbook by" Theodore Petrou
This book is an amazing read for you all who are looking for a quick recipe to ‘learning the tricks’. And thus, to simplify those operations that once may have made you wish for a book like this. Alas! This is nothing but your wish come true and I feel grateful for going through this book myself. It is a great book to make you learn Pandas with in-depth knowledge and is a MUST if you want to explore trading with Python’s pandas This book is aimed at providing you with practical situations for a thorough learning.
"Python for Finance: Mastering Data-Driven Finance" by Yves Hilpisch
This book is an excellent in-depth read providing you with direct applications and important functions. You will get a wonderful insight into data handling, time series analysis etc. with this book. Moreover, it teaches you to form a full-fledged framework for Monte Carlo Simulation based derivatives and risk analytics.
Moving further to the end of this blog, let us see some essential books in the field of portfolio management.
Books on Portfolio Management
Portfolio management is the process of selecting and managing a group of investments that meet the long-term financial objectives and risk tolerance of an investor or institution.
"The Intelligent Asset Allocator: How to Build Your Portfolio to Maximize Returns and Minimize Risk" by William Bernstein
William Bernstein's "The Intelligent Asset Allocator" focuses on asset allocation strategies based on the principles of modern portfolio theory and efficient market hypothesis. The book explains the importance of diversification, asset allocation across different asset classes (stocks, bonds, etc.), and rebalancing techniques. It offers practical insights into designing portfolios that aim to maximise returns while managing risk effectively.
This book is suitable for individual investors, financial advisors, and anyone interested in learning systematic approaches to asset allocation and portfolio construction to achieve long-term investment goals.
"A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing" by Burton G. Malkiel
Burton G. Malkiel's "A Random Walk Down Wall Street" is a classic investment book that covers various aspects of investing, including portfolio management. It discusses the efficient market hypothesis, passive investing strategies (like index funds), asset allocation principles, and behavioural finance insights. The book is known for its easy language and practical advice on building diversified portfolios that align with long-term financial goals.
This book is recommended for investors of all levels, from beginners to seasoned professionals, who want to understand the fundamentals of investing and portfolio management using evidence-based strategies.
"Investment Valuation: Tools and Techniques for Determining the Value of Any Asset" by Aswath Damodaran
Aswath Damodaran's "Investment Valuation" is a comprehensive guide to valuation techniques that are fundamental to portfolio management. The book covers various methods for valuing different types of assets, including stocks, bonds, and businesses. It emphasises the importance of understanding the intrinsic value of investments and how valuation impacts portfolio decisions. The book also explores risk assessment and the integration of valuation into portfolio strategies.
This book is suitable for analysts, portfolio managers, and investors who want to deepen their understanding of valuation principles and apply them effectively in managing investment portfolios.
Great! After a whole lot of lists of various Algorithmic Trading books belonging to different categories, we have reached the end of this blog.
Conclusion
We have covered most of the important books belonging to the relevant fields in terms of Algorithmic Trading. We hope that the aforementioned books will help you get started with your Algorithmic Trading journey.
The intention was to consider all those books which are imperative when it comes to learning the Algorithmic form of trading. There are also some free resources to learn Algorithmic Trading. We had also previously covered the most popular blogs for algo trading written by experts!
In case you wish to learn more algorithmic trading in depth under the mentorship of leading industry experts, QuantInsti's Executive Programme in Algorithmic Trading (EPAT) is the algo trading course you need. Get in touch with course counsellors to know more about the EPAT programme and its benefits. Enroll now!
Note: The original post has been revamped on 15th July 2024 for recentness, and accuracy.
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