Trading research worth reading, from microseconds to months.
A hand-picked library of market microstructure, HFT and quant trading research. Every paper is tagged by level, horizon and the data you need to test it, with a plain-English summary.
124 papers & books12 reading paths73 free to readWeekly new picks
Start with a reading path
All 12 paths →Start here: how markets actually work
6 papers, starting with Trading and Exchanges: Market Microstructure for Practitioners
Market making, from dealers to HFT
7 papers, starting with Liquidity and Market Structure
Short-term alpha from the order book
7 papers, starting with Inferring Trade Direction from Intraday Data
Options and volatility for index-options traders
9 papers, starting with Option Volatility and Pricing: Advanced Trading Strategies and Techniques
Don't fool yourself: backtesting hygiene
7 papers, starting with Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance
The Indian market: who trades, who loses, who leads
7 papers, starting with Analysis of Intraday Trading by Individuals in Equity Cash Segment
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Browse everything →Browse by theme
What's New: Launch issue
All issues →Profitability of Individual Traders in the Equity Derivatives Segment (FY25–FY26)
SEBI's newest look at F&O traders (August 2026). Fewer individuals traded in FY26, and the share of loss-makers fell to 87.7%, but those still trading lost slightly more on average.
Trading Behaviour of Individual Traders in the Equity Derivatives Segment (FY25–FY26)
The companion study: who buys and who sells options, how much capital they use, and how losses differ between option buyers and option sellers.
Deep Learning Statistical Arbitrage
Deep Learning Statistical Arbitrage is now published in Management Science (2026).