How do I learn algorithmic trading?
What are the steps to start Algo trading?
Which are the essential books on Algorithmic trading?
How do I start doing research in algorithmic trading?
Which is the best Algo trading institute?
These are some of the questions that popular forums get inundated with from aspiring novice algorithmic traders around the world. A good starting point for a wannabe trader would be to pick up a good book, immerse oneself, and absorb all that the book has to offer. This post details down the core areas in which aspiring quants need to focus on, and covers some of the good reads in each of these categories. At the end of the post we have also shared a comprehensive list of books that are considered good reads in this field.
Market microstructure details how trades/exchanges occur in markets, and it delves on market participants, trading methods, liquidity, price discovery, transaction costs etc. Market microstructure is useful in developing algorithmic trading systems and thus, sound knowledge of market microstructure is an important pre-requisite for high frequency traders, and market makers. Here are a couple of important reads –
The book is a good read for anyone interested in understanding the way markets work. The primary objective of the book as mentioned by the author is to understand the origins of the market quality characteristics like liquidity, transaction costs, informative prices, volatility, and trading profits. The book also details how market structure – trading rules and information systems affects the above mentioned market characteristics.
This book provides a comprehensive guide to the theoretical work in market microstructure research and is an essential read for a high frequency trader.
The book introduces readers to the general issues and problems in market microstructure, and further delves on inventory models, information-based models, and strategic trader models of informed and uninformed traders. The concluding chapters in the book detail the relationship between information and the price process, liquidity and the relationship between markets.
Algorithmic trading strategies form the core of quantitative trading. For aspiring quants it is essential to know the process of developing trading systems and their implementation in the markets. We have chosen the following two popular books on algorithmic trading
This book is 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.
The book starts with a chapter on backtesting and automated execution, and then covers the mean reversion strategies and their implementation for stocks, ETFs, currencies, and futures. Dr. Ernest Chan has also devoted chapters in the book for interday and intraday momentum strategies. The book concludes with a chapter on risk management.
The book covers multiple statistical techniques for detecting “time series” mean reversion or stationarity, and for detecting cointegration of a portfolio of instruments. Simple techniques for trading mean–reverting portfolios like linear, Bollinger band, and Kalman filter have been explained by the author in the book.
In the section on momentum based strategies, Dr. Ernest Chan details the four main drivers of momentum in stocks and futures, and the strategies based on time series and cross sectional momentum. Newer momentum strategies based on news events and sentiment, leveraged ETFs, order flow, and high–frequency trading have also been covered in the book.
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 various topics.
Books for Statistics & Econometrics
In an increasingly competitive trading landscape, Math and statistics provide very powerful tools to succeed in systematic trading. Trading systems use time series analysis and other statistical models to predict and trade in the markets. Sound knowledge of Math and statistics is an essential skill that is desired by quant firms looking to hire new recruits. Following books are a good read to get initiated.
This book presents a clear and concise introduction to statistics and econometrics. The book adopts a problem-solving approach. Topics covered in the book include their theory part, principles, and are fully illustrated with examples. The book covers numerous theoretical and practical problems with detailed, step-by-step solutions.
The book is an excellent introduction to econometric models and their applications to modeling and prediction of financial time series data.
The book covers important topics like Linear Time Series Analysis, Nonlinear Models, Multivariate Time Series Analysis, High-Frequency Data Analysis, PCA, State-Space Models, Kalman Filter and other topics. Empirical examples are used to demonstrate the application of the topics covered in the book.
Books for Technical Analysis
Technical analysis and technical indicators find a very wide usage in trading. Technical indicators can be used as additional filters in quantitative trading strategies by quants. Technical indicators also find usage in Machine learning models where these are used as inputs in the model.
The book is considered the bible of technical analysis. The book offers deep insight into technical analysis of financial markets and has been written in a simple and easy-to-understand language by the author. It is a recommended reading for day traders as well as for long-term investors.
The book covers chart construction, basic concepts of trend, reversal patterns, moving averages, oscillators, stock market indicators, advanced technical indicators, volume and open interest, and various other topics.
The book is a good read on technical analysis and the practical examples illustrated in the book can be applied in the real world trading. The book comprises of three parts: Part 1 details trend determining techniques, Part 2 describes the Market Structure, and Part 3 discusses other aspects of market analysis.
The author believes that there is a rough correlation between the reliability of the technical indicators and the time span being monitored. Hence, most of the discussion in the book is oriented towards intermediate-term and long-term trends. The books also offers practical advice for avoiding false, contra-trend signals that may arise in short-term time spans.
Books for Options Trading
Options and futures are highly traded instruments in the markets. Options trading has become extremely sophisticated and it is really important for aspiring quants and traders to have a sound understanding of volatility, Greeks, and various options strategies. We have listed the following two books which are good reads on Options.
This book is an essential read for those interested in quantitative finance. The author has covered difficult topics with numerous examples and explanations. The initial chapters of book cover the basics of derivative contracts. In this book, Hull has covered different topics on the Options markets which include Mechanics of Options markets, properties of stock Options, Options Trading strategies, Black-Scholes-Merton model, Options on stock indices, Futures Options, and currencies, Greeks, Volatility smiles etc. The book is a good read for those who want to learn about the intricacies of options to become successful at options trading.
The book is a good read for traders and deals with the practicalities of hedging the risks of standard and exotic options, as part of the larger framework of risk management.
The book comprises of four parts: Part 1 defines Market microstructure and products, Part 2 defines the basics of vanilla option risk and measurement tools, Part 3 describes the risks of exotic options, and Part 4 provides quantitative tools of analysis.
The book covers the behavior of Greeks, Volatility and Correlation, Volatility Trading, Trading and Hedging Exotic Options, and various other topics. Advanced mathematical topics are discussed in the last part of the book under the “Modules’ category.
These were some of the essential books on algorithmic trading that we thought of sharing with our readers. For a more exhaustive list of books, you can refer to slide share here.
If you enjoyed this post you might also want to start practising what you have learned in these resources with help of our blog on ‘An Example Of A Trading Strategy Coded Using Quantmod Package In R‘. This is an easy to follow tutorial that will help you back-test your trading strategy in R.