Project Sherlock

Finance & Investing

Quantitative Finance

Mathematical modelling of markets.

11 topics · 12 curated works

Topics

  • 01Foundations & Overviews
  • 02Stochastic Calculus in Finance1
  • 03Ito's Lemma1
  • 04Monte Carlo Pricing1
  • 05Risk-Neutral Valuation1
  • 06Time Series Models of Returns1
  • 07Statistical Arbitrage1
  • 08Algorithmic Trading2
  • 09Market Microstructure2
  • 10High-Frequency Trading1
  • 11Machine Learning in Finance1

Reading in Quantitative Finance

12

A way in

  1. Start here

    No prior grounding assumed.

    Equity Market Structure Literature Review, Part II: High Frequency Trading Synopsis

    U.S. Securities and Exchange Commission, Division of Trading and Markets · 2014

    Synthesises the empirical literature on high-frequency trading, concluding most studies find HFT narrows spreads and adds liquidity in normal markets…

  2. Then

    Assumes you know the vocabulary.

    Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance

    David H. Bailey, Jonathan M. Borwein, Marcos Lopez de Prado & Qiji Jim Zhu · 2014

    Given enough trials an impressive backtest can be manufactured from pure noise, so a Sharpe ratio quoted without the number of configurations tried…

    +1 more at this level

  3. Go deeper

    Primary sources and full treatments.

    On a Formula Concerning Stochastic Differentials

    Kiyosi Ito · 1951

    Derives the chain rule for functions of a stochastic process now known as Ito's Lemma, the calculus that lets a smooth function of a random path be…

    +8 more at this level

12 works

Paper2022

Quantifying the High-Frequency Trading "Arms Race"

Matteo Aquilina, Eric Budish & Peter O'Neill

Uses regulatory data from a UK exchange to measure the resources firms spend racing each other to react to public information a fraction of a millisecond faster, and finds this arms race is a large, continuing tax on liquidity provision with no offsetting gain in market quality.

link checked 17 Sept 2026
Paper1976

The Valuation of Options for Alternative Stochastic Processes

John C. Cox & Stephen A. Ross

Shows an option can be priced as if all investors were risk-neutral, discounting expected payoffs at the riskless rate under an adjusted probability measure, because a perfectly hedged option position removes the need to know the underlying's true expected return.

Paper1977

Options: A Monte Carlo Approach

Phelim P. Boyle

Introduces simulating many random paths of an underlying asset and averaging the discounted payoff as a way to price options for which no closed-form formula exists, the origin of Monte Carlo methods in finance.

Paper1985

Continuous Auctions and Insider Trading

Albert S. Kyle

Models how an informed trader optimally hides behind noise traders, showing market depth and the informativeness of prices are jointly determined by how aggressively the informed trader exploits private information.

Paper2020

Empirical Asset Pricing via Machine Learning

Shihao Gu, Bryan Kelly & Dacheng Xiu

Benchmarks machine learning methods against traditional linear factor models for predicting stock returns and finds tree-based and neural network models substantially outperform, with nonlinear interactions among a small set of characteristics doing most of the work.

link checked 17 Sept 2026

In order written

1951 – 2025
  1. 1976The Valuation of Options for Alternative Stochastic ProcessesJohn C. Cox & Stephen A. Ross
  2. 1977Options: A Monte Carlo ApproachPhelim P. Boyle
  3. 1985Continuous Auctions and Insider TradingAlbert S. Kyle
  4. 2014Equity Market Structure Literature Review, Part II: High Frequency Trading SynopsisU.S. Securities and Exchange Commission, Division of Trading and Markets
  5. 2014Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample PerformanceDavid H. Bailey, Jonathan M. Borwein, Marcos Lopez de Prado & Qiji Jim Zhu
  6. 2020Empirical Asset Pricing via Machine LearningShihao Gu, Bryan Kelly & Dacheng Xiu
  7. 2022Quantifying the High-Frequency Trading "Arms Race"Matteo Aquilina, Eric Budish & Peter O'Neill
  8. 2025AI-Powered Trading, Algorithmic Collusion, and Price EfficiencyWinston Wei Dou, Itay Goldstein & Yan Ji

Also covered elsewhere

This subject genuinely sits in more than one domain. These fields approach the same ground with different methods.

Elsewhere in Finance & Investing