QUANTGPT LEARN · RESEARCH RESOURCES · VERIFIED 2026-09-21
// 91 sources. 23 re-run in the terminal.

QUANT RESEARCH RESOURCES

From one backtest to a research process: the papers, the data, and the tape they get re-run on.

A curated list for learning systematic investing research, ordered the way the work happens: the data you test on, what makes a backtest number mean something, the factors and events the literature found, what it costs to trade them, and the markets beyond stocks.

The core list uses the paper that introduced the effect, the official documentation, or the repository that implements it. Where the terminal can re-run a paper, the entry names the data the re-run uses and links to the library study and to RUN IT. Stock re-runs use the US tape with delisted names kept and fundamentals by filing date, from 1990 at the earliest; the others run on the S&P 500 index, resolved Polymarket markets or Binance pairs. Each re-run approximates the paper rather than repeating it, and the terminal prints the approximation note with every run: what it holds, over what data, and where it departs from the original. RUN IT shows the finding as CONFIRMED, TRADE-OFF or NO EDGE, gross of costs, and says so on every output. Where the library carries the paper but has no runnable spec for it yet, the entry links to the library entry alone.

Read Start here first. After that, use it as a reference.

// START HERE: THE MINIMUM MENTAL MODEL

Read these in order if you are new to the field. The practical companion is the learn path: Become a quant and The findings system.

  1. FAMA, 1970, JOURNAL OF FINANCE
    The null hypothesis every backtest argues with.
  2. FAMA & FRENCH, 1993, JOURNAL OF FINANCIAL ECONOMICS
    Size and value as factors; the model returns still get benchmarked against.
  3. JEGADEESH & TITMAN, 1993, JOURNAL OF FINANCE
    Momentum: the anomaly that survived thirty years of scrutiny.
  4. SHUMWAY, 1997, JOURNAL OF FINANCE
    Why a universe without the dead overstates every strategy that buys small or cheap.
  5. BAILEY & LOPEZ DE PRADO, 2014, JOURNAL OF PORTFOLIO MANAGEMENT
    The Sharpe you are allowed to report after the number of trials you ran.
  6. HARVEY, LIU & ZHU, 2016, REVIEW OF FINANCIAL STUDIES
    Hundreds of published factors, and the t-statistic bar that survives them.
  7. MCLEAN & PONTIFF, 2016, JOURNAL OF FINANCE
    Returns fall after publication. The decay to expect from anything on this list.

// 1. DATA: THE TAPE YOU TEST ON

Most bad backtests are bad data. A universe without the dead, fundamentals seen before they were filed, and prices without corporate actions each add returns that never existed.

  1. SHUMWAY & WARTHER, 1999, JOURNAL OF FINANCE
    The size premium shrinks once delisting returns are filled in.
  2. BANZ & BREEN, 1986, JOURNAL OF FINANCE
    Look-ahead and survivorship in fundamentals, measured on the same strategies with and without them.
  3. FAMA & FRENCH, ONGOING, DARTMOUTH
    The factor returns everyone regresses on; monthly since 1926.
  4. CHEN & ZIMMERMANN, 2022, CRITICAL FINANCE REVIEW
    Two hundred published anomalies with code and returns, reproducible.
  5. U.S. SECURITIES AND EXCHANGE COMMISSION, DOCS, SEC.GOV
    Filings and XBRL facts with their filing dates: the raw material for point-in-time fundamentals.
  6. FEDERAL RESERVE BANK OF ST. LOUIS, DOCS, FRED.STLOUISFED.ORG
    Macro series, with ALFRED vintages for what was known when.
  7. QUANTGPT, 2026, QUANTGPT.CO
    How the warehouse is built: decades of history, 42,000 tickers including delisted from 1998, fundamentals joined by filing date, gross returns.

// 2. THE BACKTEST: WHAT MAKES A NUMBER MEAN SOMETHING

Multiple testing, overfitting, decay after publication, and how to run an event study. This section is why the terminal reports a deflated Sharpe and a walk-forward split on every run.

  1. LO & MACKINLAY, 1990, REVIEW OF FINANCIAL STUDIES
    The original warning: sort on a characteristic you already know predicts returns and the test is rigged.
  2. BAILEY, BORWEIN, LOPEZ DE PRADO & ZHU, 2014, NOTICES OF THE AMS
    How many trials it takes to find a Sharpe of one in noise. Fewer than you think.
  3. HARVEY & LIU, 2015, JOURNAL OF PORTFOLIO MANAGEMENT
    Haircuts for Sharpe ratios under multiple testing, with the formulas.
  4. ARNOTT, HARVEY & MARKOWITZ, 2019, JOURNAL OF FINANCIAL DATA SCIENCE
    A checklist for research you can trust: economic foundation, out-of-sample discipline, no peeking.
  5. LOPEZ DE PRADO, 2018, WILEY
    Purged and embargoed cross-validation, the probability of backtest overfitting, and why leakage is the default.
  6. HOU, XUE & ZHANG, 2020, REVIEW OF FINANCIAL STUDIES
    Most published anomalies fail once microcaps are handled properly.
  7. JENSEN, KELLY & PEDERSEN, 2023, JOURNAL OF FINANCE
    The other side: with a Bayesian prior and global data, most factors replicate. Read both.
  8. MACKINLAY, 1997, JOURNAL OF ECONOMIC LITERATURE
    The standard event-study method: estimation window, event window, abnormal returns.
  9. BROWN & WARNER, 1985, JOURNAL OF FINANCIAL ECONOMICS
    What daily data does to event-study tests, and which simple methods hold up.
  10. QUANTGPT, 2026, QUANTGPT.CO
    CONFIRMED needs both axes (CAGR and Sharpe) in both windows (training and walk-forward). The methodology, stated in full.

// 3. FACTORS AND ANOMALIES

The cross-section: value, momentum, quality, low risk, size, reversal. Every entry links the original paper, the library study where there is one, and RUN IT where the terminal re-runs it on US stocks.

  1. FAMA & FRENCH, 1992, JOURNAL OF FINANCE
    Book-to-market and size explain returns; beta does not.
    RE-RUN ON US STOCKS: VALUE FACTOR (HML)·RUN IT ▸
  2. BASU, 1977, JOURNAL OF FINANCE
    Low P/E portfolios, the first modern value test.
  3. LAKONISHOK, SHLEIFER & VISHNY, 1994, JOURNAL OF FINANCE
    Value works because investors extrapolate, not because it is riskier.
    RE-RUN ON US STOCKS: CONTRARIAN VALUE (LSV)·RUN IT ▸
  4. PIOTROSKI, 2000, JOURNAL OF ACCOUNTING RESEARCH
    The F-score: nine accounting signals that sort cheap stocks into winners and losers.
    RE-RUN ON US STOCKS: PIOTROSKI F-SCORE·RUN IT ▸
  5. CAMPBELL & SHILLER, 1988, JOURNAL OF FINANCE
    The cyclically adjusted P/E and what it says about the next decade.
  6. CARHART, 1997, JOURNAL OF FINANCE
    Momentum becomes the fourth factor.
  7. GEORGE & HWANG, 2004, JOURNAL OF FINANCE
    Nearness to the 52-week high predicts returns better than past returns do.
    RE-RUN ON US STOCKS: 52-WEEK HIGH MOMENTUM·RUN IT ▸
  8. MOSKOWITZ & GRINBLATT, 1999, JOURNAL OF FINANCE
    Much of stock momentum is industry momentum.
    IN THE LIBRARY: INDUSTRY MOMENTUM
  9. MOSKOWITZ, OOI & PEDERSEN, 2012, JOURNAL OF FINANCIAL ECONOMICS
    Trend in 58 futures markets: an asset's own past return predicts its future.
  10. DANIEL & MOSKOWITZ, 2016, JOURNAL OF FINANCIAL ECONOMICS
    When momentum loses half its value in months, and why.
    IN THE LIBRARY: MOMENTUM CRASHES
  11. BARROSO & SANTA-CLARA, 2015, JOURNAL OF FINANCIAL ECONOMICS
    Scale momentum by its own volatility and the crashes mostly go away.
  12. NOVY-MARX, 2012, JOURNAL OF FINANCIAL ECONOMICS
    Returns from 12 to 7 months ago predict better than the most recent months.
  13. DE BONDT & THALER, 1985, JOURNAL OF FINANCE
    Three-to-five-year losers beat winners. Long-term reversal.
    IN THE LIBRARY: LONG-TERM LOSER REVERSAL
  14. ASNESS, MOSKOWITZ & PEDERSEN, 2013, JOURNAL OF FINANCE
    The same two premia in eight markets and four asset classes, negatively correlated.
  15. EHSANI & LINNAINMAA, 2022, JOURNAL OF FINANCE
    Factors themselves have momentum, and it explains stock momentum.
    IN THE LIBRARY: FACTOR MOMENTUM
  16. NOVY-MARX, 2013, JOURNAL OF FINANCIAL ECONOMICS
    Gross profits over assets predicts returns as well as book-to-market.
    RE-RUN ON US STOCKS: GROSS PROFITABILITY·RUN IT ▸
  17. ASNESS, FRAZZINI & PEDERSEN, 2019, REVIEW OF ACCOUNTING STUDIES
    Profitable, growing, safe companies earn more than they should.
    RE-RUN ON US STOCKS: QUALITY MINUS JUNK (QMJ)·RUN IT ▸
  18. SLOAN, 1996, THE ACCOUNTING REVIEW
    Earnings made of accruals mean-revert; the market does not price it.
    RE-RUN ON US STOCKS: ACCRUALS ANOMALY·RUN IT ▸
  19. COOPER, GULEN & SCHILL, 2008, JOURNAL OF FINANCE
    Companies that grow their balance sheet fastest earn the least after.
    RE-RUN ON US STOCKS: ASSET GROWTH ANOMALY·RUN IT ▸
  20. FAMA & FRENCH, 2015, JOURNAL OF FINANCIAL ECONOMICS
    Profitability and investment join size and value.
  21. ALTMAN, 1968, JOURNAL OF FINANCE
    The Z-score. Still the screen most people mean by distress.
    IN THE LIBRARY: ALTMAN Z-SCORE
  22. CAMPBELL, HILSCHER & SZILAGYI, 2008, JOURNAL OF FINANCE
    Distressed stocks earn less, not more. The anomaly that runs the wrong way for risk stories.
  23. FRAZZINI & PEDERSEN, 2014, JOURNAL OF FINANCIAL ECONOMICS
    Low-beta assets earn more per unit of risk because leverage is constrained.
  24. ANG, HODRICK, XING & ZHANG, 2006, JOURNAL OF FINANCE
    High idiosyncratic volatility, low returns. The puzzle behind low-vol investing.
  25. BANZ, 1981, JOURNAL OF FINANCIAL ECONOMICS
    The size effect, before the delisting bias took a bite out of it.
  26. AMIHUD, 2002, JOURNAL OF FINANCIAL MARKETS
    The illiquidity measure every liquidity filter descends from.

// 4. EVENTS, FLOWS AND SEASONALITY

What happens after earnings, buybacks, dividends, index changes and insider trades, and the calendar effects that refuse to die.

  1. BALL & BROWN, 1968, JOURNAL OF ACCOUNTING RESEARCH
    Prices keep drifting after earnings news. The origin of post-earnings drift.
  2. BERNARD & THOMAS, 1989, JOURNAL OF ACCOUNTING RESEARCH
    Standardized unexpected earnings, and the drift measured properly.
  3. FRAZZINI & LAMONT, 2007, NBER WORKING PAPER 13090
    Stocks earn more in the month they announce.
  4. HARRIS & GUREL, 1986, JOURNAL OF FINANCE
    Index inclusion moves prices, then some of it reverses.
    IN THE LIBRARY: S&P 500 INCLUSION EFFECT
  5. IKENBERRY, LAKONISHOK & VERMAELEN, 1995, JOURNAL OF FINANCIAL ECONOMICS
    Buyback announcements are followed by years of drift.
  6. MICHAELY, THALER & WOMACK, 1995, JOURNAL OF FINANCE
    Initiations drift up, omissions drift down, for a year.
  7. LAKONISHOK & LEE, 2001, REVIEW OF FINANCIAL STUDIES
    Insider buying predicts returns; selling mostly does not.
    RE-RUN IN THE TERMINAL: INSIDER BUYING SIGNAL·RUN IT ▸
  8. COHEN, MALLOY & POMORSKI, 2012, JOURNAL OF FINANCE
    Separate routine insider trades from opportunistic ones and the signal doubles.
    RE-RUN IN THE TERMINAL: INSIDER CLUSTER BUYS·RUN IT ▸
  9. KEIM, 1983, JOURNAL OF FINANCIAL ECONOMICS
    Half the size premium arrives in January, much of it in the first week.
  10. BOUMAN & JACOBSEN, 2002, AMERICAN ECONOMIC REVIEW
    November to April beats May to October in 36 of 37 countries.
    RE-RUN ON THE S&P 500 INDEX: SELL IN MAY (HALLOWEEN INDICATOR)·RUN IT ▸
  11. HESTON & SADKA, 2008, JOURNAL OF FINANCIAL ECONOMICS
    Stocks that did well in a calendar month tend to do well in that month again.

// 5. MACRO, RATES AND OTHER ASSET CLASSES

The Fed, the curve, recessions, currencies, commodities and bonds.

  1. BERNANKE & KUTTNER, 2005, JOURNAL OF FINANCE
    A surprise 25 basis point cut moves stocks about one percent. The event-study method for rate decisions.
  2. LUCCA & MOENCH, 2015, JOURNAL OF FINANCE
    A large share of the equity premium is earned in the 24 hours before Fed announcements.
  3. SAHM; FRED, 2019, FRED.STLOUISFED.ORG
    The unemployment trigger, as it was known at the time.
  4. SCHNEIDER & TROEGER, 2006, JOURNAL OF CONFLICT RESOLUTION
    How markets price conflict onsets and escalations; the method behind the war study.
  5. COCHRANE & PIAZZESI, 2005, AMERICAN ECONOMIC REVIEW
    One tent-shaped combination of forward rates predicts bond returns.
  6. GORTON & ROUWENHORST, 2006, FINANCIAL ANALYSTS JOURNAL
    Commodity futures as an asset class, and where the return comes from.
  7. MENKHOFF, SARNO, SCHMELING & SCHRIMPF, 2012, JOURNAL OF FINANCIAL ECONOMICS
    Momentum in currencies, and the costs that eat part of it.
    IN THE LIBRARY: CURRENCY MOMENTUM

// 6. COSTS, EXECUTION AND SIZING

Gross returns are the start of the conversation. These are the papers on what is left after trading, and how much to bet.

  1. NOVY-MARX & VELIKOV, 2016, REVIEW OF FINANCIAL STUDIES
    Which anomalies survive transaction costs, and the tricks that help them survive.
  2. FRAZZINI, ISRAEL & MOSKOWITZ, 2018, SSRN WORKING PAPER
    Real trading costs from a large manager's own trades. Lower than academic estimates, still not zero.
  3. PEROLD, 1988, JOURNAL OF PORTFOLIO MANAGEMENT
    The gap between the paper portfolio and the real one, named.
  4. ALMGREN & CHRISS, 2001, JOURNAL OF RISK
    How to trade a position over time when trading moves the price.
  5. KELLY, 1956, BELL SYSTEM TECHNICAL JOURNAL
    The bet size that maximizes growth, and why half of it is what people actually use.

// 7. ALT MARKETS: PREDICTION MARKETS, CRYPTO, SPORTS, MEMECOINS

Markets with their own literature and their own data problems. The memecoin graveyard has no paper yet because no free feed sells the dead; QuantGPT records them.

  1. WOLFERS & ZITZEWITZ, 2004, JOURNAL OF ECONOMIC PERSPECTIVES
    What prediction market prices mean and how well they forecast.
  2. SNOWBERG & WOLFERS, 2010, JOURNAL OF POLITICAL ECONOMY
    Longshots are overpriced and favorites underpriced, and it is misperception, not risk appetite.
  3. PAGE & CLEMEN, 2013, ECONOMIC JOURNAL
    Calibration is good near resolution and worse far from it.
  4. LIU, TSYVINSKI & WU, 2022, JOURNAL OF FINANCE
    Size and momentum work in crypto too; a three-factor model for coins.
  5. LIU & TSYVINSKI, 2021, REVIEW OF FINANCIAL STUDIES
    Crypto returns are not explained by stock, currency or commodity factors; network effects and attention matter.
  6. LEVITT, 2004, ECONOMIC JOURNAL
    Bookmakers set prices to exploit bettor bias, not to balance the book.
  7. QUANTGPT, 2026, QUANTGPT.CO
    Every new pool recorded the day it appears and followed until long after it dies, because no free feed sells the dead. Survival by launch month; a token dead by the next month-end is a total loss.

// 8. MACHINE LEARNING IN ASSET PRICING

Where the field is going, and the two papers to read before believing a model.

  1. GU, KELLY & XIU, 2020, REVIEW OF FINANCIAL STUDIES
    Trees and neural nets against the cross-section, with the out-of-sample discipline stated.
  2. KELLY, MALAMUD & ZHOU, 2024, JOURNAL OF FINANCE
    Bigger models predict better even past the point where they interpolate the data. Controversial; read with the backtesting protocol next to it.

// 9. TOOLS AND OPEN DATA

Official sources and open code. This list is the papers and the tape; awesome-quant is the code.

  1. QUANTGPT, 2026, QUANTGPT.CO
    The warehouse and the engine as tools your own AI calls: backtests, screens, event studies, the library.
  2. QUANTGPT, 2026, QUANTGPT.CO
    170+ documented strategies from the papers on this page, each with its thesis and criteria; runnable on the terminal.
  3. DUCKDB FOUNDATION, DOCS, DUCKDB.ORG
    The engine under the warehouse. The same SQL runs on a laptop.
  4. WILSON FREITAS AND CONTRIBUTORS, ONGOING, GITHUB
    The community index of quant libraries and tools, by language.

// FRONTIER AND WATCHLIST

Kept apart from the core list because the evidence changes quickly. Verified on the date at the top.

  1. LOPEZ-LIRA & TANG, 2026, JOURNAL OF FINANCIAL ECONOMICS
    LLM sentiment on headlines predicts next-day returns in-sample. The multiple-testing warning applies twice.
  2. Watchlist: AI-generated strategies
    Agents that write and test thousands of rules a night are a multiple-testing machine. Any published result needs the trial count and a deflated Sharpe, or the number is omitted.
  3. Watchlist: prediction market calibration since 2024
    Volumes on Polymarket and Kalshi are a different regime from the data in the 2004 to 2013 papers. Calibration by category and time to close, on the resolved record, is the open question.
  4. Watchlist: memecoin survival base rates
    The graveyard is months old. Survival at 30, 90 and 180 days by launch month becomes a citable base rate once it holds a year of cohorts.
  5. Watchlist: on-chain and funding factors
    Funding rates, exchange flows and holder concentration as factors, pending a survivorship-complete universe to test them on.

// SOURCE POLICY

A core source must be one of the following: the paper that introduced the effect; the specification or official documentation that defines the data; the repository that implements it; or a replication that states its universe, window, survivorship treatment, costs and out-of-sample method.

Return claims need the universe, the window, the survivorship treatment, the cost assumption and the out-of-sample method. Otherwise the number is omitted.

Where an entry carries RUN IT, the terminal shows the finding (CONFIRMED, TRADE-OFF or NO EDGE) with the walk-forward split and a deflated Sharpe, gross of costs, and says so on every output. Nothing on this page is investment advice.