Research

Research notes and preprints, plus a reading list of 18 papers — the ones we think are worth the evening, from the equilibrium arguments the whole field rests on to what deep learning has actually established about price formation.

Papers we come back to. Each note says why it earns the spot rather than restating the abstract — read the notes to decide what to open, then read the paper. Every link goes to the canonical source: a DOI, arXiv, SSRN, or the publisher's own PDF. Some sit behind a paywall; a preprint is usually a search away.

★ Core MicrostructureMarket Design 2015

Trading Strategies and Market Microstructure: Evidence from a Prediction Market

David M. Rothschild, Rajiv Sethi

Account-level data on 6,300 traders in the Intrade 2012 election market — a whole market ecology laid bare, including evidence of manipulation by one large trader. Rare visibility into who is actually on the other side.

SSRN / The Journal of Prediction Markets Open ↗
★ Core FactorsPractitioner 2013

Foundations of Factor Investing

Jennifer Bender, Remy Briand, Dimitris Melas, Raman Aylur Subramanian

The clearest bridge from academic factor papers to what an index provider actually builds. Read it when you need to explain factors to someone who allocates capital.

MSCI Research Insight Open ↗
★ Core FactorsAsset Pricing 2006

The Value Premium and the CAPM

Eugene F. Fama, Kenneth R. French

The direct sequel to Sharpe: value beats the market, and the CAPM beta cannot explain it. Pairs with the 1993 three-factor paper below.

The Journal of Finance Open ↗
★ Core Asset PricingFoundations 2003

A Simple Approach to the Theory of Asset Prices

Riccardo Cesari, Carlo D'Adda

Prices assets as bundles of moment-characteristics without assuming expected utility. A useful antidote if you have only ever seen pricing derived one way.

SSRN Working Paper (Università di Bologna) Open ↗
★ Core Asset PricingFoundations 1964

Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk

William F. Sharpe

The CAPM. Read it for the argument, not the result: Sharpe derives a single price of risk from equilibrium alone, and every factor model since is a fight about what he left out.

The Journal of Finance Open ↗
Machine LearningFactors 2020

Empirical Asset Pricing via Machine Learning

Shihao Gu, Bryan Kelly, Dacheng Xiu

The reference comparison of ML methods for return prediction. The interesting result is not that trees and nets win, but that their gains come from allowing interactions and nonlinearity — not from more data.

The Review of Financial Studies Open ↗
Machine LearningMicrostructure 2019

DeepLOB: Deep Convolutional Neural Networks for Limit Order Books

Zihao Zhang, Stefan Zohren, Stephen Roberts

A concrete, reproducible architecture for learning directly from raw order book state. Good starting point if you want to move past hand-engineered microstructure features.

IEEE Transactions on Signal Processing / arXiv Open ↗
Machine LearningMicrostructure 2018

Universal Features of Price Formation in Financial Markets: Perspectives from Deep Learning

Justin Sirignano, Rama Cont

A single deep network trained across stocks beats per-stock models, which is evidence that price formation has a universal component. The strongest argument for pooling data that we know of.

arXiv / Quantitative Finance Open ↗
Multiple TestingFactors 2016

… and the Cross-Section of Expected Returns

Campbell R. Harvey, Yan Liu, Heqing Zhu

Hundreds of published factors, one multiple-testing correction, and most of them stop being significant. The single most useful paper for staying honest about your own research.

The Review of Financial Studies Open ↗
Multiple TestingBacktesting 2014

The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting and Non-Normality

David H. Bailey, Marcos López de Prado

How to discount a Sharpe ratio for the number of trials it took to find it. Practical, and it usually deflates your favourite strategy more than you expect.

Journal of Portfolio Management / SSRN Open ↗
ExecutionMicrostructure 2001

Optimal Execution of Portfolio Transactions

Robert Almgren, Neil Chriss

The trade-off between market impact and timing risk, made tractable. If your backtest assumes fills at mid, this is the paper that tells you what you owe.

Journal of Risk Open ↗
FactorsMomentum 1997

On Persistence in Mutual Fund Performance

Mark M. Carhart

Adds momentum to the three-factor model and, in doing so, explains away most of what looked like fund manager skill. A lesson in attribution before admiration.

The Journal of Finance Open ↗
FactorsAsset Pricing 1993

Common Risk Factors in the Returns on Stocks and Bonds

Eugene F. Fama, Kenneth R. French

Size and value as priced factors. The three-factor model is the baseline any new signal has to beat before it is worth a second look.

Journal of Financial Economics Open ↗
FactorsMomentum 1993

Returns to Buying Winners and Selling Losers

Narasimhan Jegadeesh, Sheridan Titman

Momentum: the anomaly that refused to be explained away and still has not been. Note how carefully they handle overlapping holding periods — the method matters as much as the finding.

The Journal of Finance Open ↗
Microstructure 1985

Continuous Auctions and Insider Trading

Albert S. Kyle

Where market impact comes from. Kyle’s lambda is still the unit in which execution desks think about how much your order moves the price.

Econometrica Open ↗
DerivativesFoundations 1973

The Pricing of Options and Corporate Liabilities

Fischer Black, Myron Scholes

Replication, not forecasting. The insight that a dynamic hedge pins down a price is the template for most modern derivatives work — and its assumptions are the standard list of what breaks in practice.

Journal of Political Economy Open ↗
FoundationsAsset Pricing 1970

Efficient Capital Markets: A Review of Theory and Empirical Work

Eugene F. Fama

The joint-hypothesis problem lives here: you can never test market efficiency without also testing your pricing model. Worth rereading whenever a backtest looks too good.

The Journal of Finance Open ↗
PortfolioFoundations 1952

Portfolio Selection

Harry Markowitz

Fourteen pages that turned investing into an optimization problem. Everything downstream — risk models, covariance shrinkage, risk parity — is an argument with this paper.

The Journal of Finance Open ↗