This is a curated list of high-impact tutorials, libraries, papers, books, courses and anything related to the high frequency trading. Feel free to make a pull request to contribute to this list.
Market microstructure research primarily focuses on the structure of exchanges and trading venues (e.g. displayed and dark), the price discovery process, determinants of spreads and quotes, intraday trading behavior, and transaction costs
| Era | General Interest |
|---|---|
| 1970 - 1990 | Spreads, Quotes, Price Evolution, Risk Premium |
| 1990 - 2000 | Transaction Costs, Slippage, Cost Measurement, Friction |
| 2000 - 2010 | Algorithms, Pre-Trade, Black Box Models, Optimal Trading Strategies |
| 2010 - present | Market Fragmentation, High Frequency, Multi-Assets, and Portfolio Construction |
Empirical Market Microstructure
Empirical Market Microstructure is about the institutions that have evolved to handle our trading needs, the economic forces that guide our strategies, and statistical methods of using and interpreting the vast amount of information that these markets produce.
Algorithmic and High-Frequency Trading
In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice.
Quantitative Trading: Algorithms, Analytics, Data, Models, Optimization
The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.
Joel Hasbrouck: @ Stern School of Business, New York University
Sebastian Jaimungal: @ Department of Statistical Sciences, University of Toronto
Xin Guo: @ Department of Industrial Engineering and Operations Research, University of California, Berkeley