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Literature: authors starting with L

55 studies, books and laws, each with its reference, a sentence on the content and the pages that cite it. All letters

L’Her et al. (2016) · A Bottom-Up Approach to the Risk-Adjusted Performance of the Buyout Fund Market

L’Her, Jean-François; Stoyanova, Rossitsa; Shaw, Kathryn; Scott, William; Lai, Charissa. Financial Analysts Journal 72 (4), pp. 36–48. doi:10.2469/faj.v72.n4.1

Against a levered public market index adjusted for size and industry, buyout funds no longer show a significant money-weighted excess return.

Cited in: Buyout funds and management buyouts: how LBOs, MBOs and MBIs work · Private equity explained: strategies, fund structure, fees and what research shows about returns · Measuring private markets: J-curve, cash flows, smoothing and public proxies · Glossary: Public proxy

Lachanski and Pav (2017) · Shy of the Character Limit: “Twitter Mood Predicts the Stock Market” Revisited

Lachanski, Michael; Pav, Steven. Econ Journal Watch 14 (3), pp. 302–345. Source

A re-examination of Bollen, Mao and Zeng (2011): the result could not be reproduced, and an effect appeared only in the original period and not out of sample, which is consistent with data snooping.

Cited in: Alternative data: job ads, Reddit, X, satellites and card payments

Lakonishok and Smidt (1988) · Are Seasonal Anomalies Real? A Ninety-Year Perspective

Lakonishok, Josef; Smidt, Seymour. Review of Financial Studies 1 (4), pp. 403–425. doi:10.1093/rfs/1.4.403

90 years of daily Dow Jones data: persistently anomalous returns around the turn of the week, month and year and around holidays.

Cited in: Stock market seasonality: Sell in May, the January effect and how to test calendar effects

Lakonishok and Lee (2001) · Are Insider Trades Informative?

Lakonishok, Josef; Lee, Inmoo. Review of Financial Studies 14 (1), pp. 79–111. doi:10.1093/rfs/14.1.79

Insider trades on the NYSE, AMEX and Nasdaq from 1975 to 1995: little price reaction at the time of the trade or the filing, and insiders trade as contrarians; predictive power lies mainly in purchases and small companies, while sales are uninformative.

Cited in: Insider trading: what is prohibited, what is allowed and what insider purchases reveal

Laloux et al. (1999) · Noise Dressing of Financial Correlation Matrices

Laloux, Laurent; Cizeau, Pierre; Bouchaud, Jean-Philippe; Potters, Marc. Physical Review Letters 83 (7), pp. 1467–1470. doi:10.1103/PhysRevLett.83.1467

Compares the eigenvalues of empirical correlation matrices of stocks (S&P 500 and other large markets) with the prediction for purely random matrices: the densities agree remarkably well, which casts doubt on the blind use of estimated correlations in risk management.

Cited in: Beyond Markowitz: estimation error, noise and true diversification · Dimensions methodology: how Portfolio Lab counts independent risks · Glossary: Marchenko-Pastur distribution · Glossary: Random matrix theory

Laurs and Renneboog (2019) · My kingdom for a horse (or a classic car)

Laurs, Dries; Renneboog, Luc. Journal of International Financial Markets, Institutions and Money 58, pp. 184–207. doi:10.1016/j.intfin.2018.10.002

29,000 classic car auctions 1998–2017, hedonic indices: before transaction costs, classic cars rose by 3.37% a year in real terms and 5.63% in nominal terms.

Cited in: Collectibles as an investment: what art, wine, watches and classic cars really return · Glossary: Hedonic price index

Ledoit and Wolf (2004) · Honey, I Shrunk the Sample Covariance Matrix

Ledoit, Olivier; Wolf, Michael. The Journal of Portfolio Management 30 (4), pp. 110–119. doi:10.3905/jpm.2004.110

Proposes shrinking the estimated covariance matrix toward a simple target matrix, which gives more stable weights with fewer errors.

Cited in: Efficient frontier: Markowitz portfolio optimization · Beyond Markowitz: estimation error, noise and true diversification · Covariance estimation: why optimizers need shrinkage · Michaud resampled optimization: more stable portfolio weights through simulation · Optimization methodology: estimation, objectives, Black-Litterman, resampling and walk-forward · Dimensions methodology: how Portfolio Lab counts independent risks · Glossary: Ledoit-Wolf shrinkage

Ledoit and Wolf (2004) · A well-conditioned estimator for large-dimensional covariance matrices

Ledoit, Olivier; Wolf, Michael. Journal of Multivariate Analysis 88 (2), pp. 365–411. doi:10.1016/s0047-259x(03)00096-4

The mathematical foundation of shrinkage estimation: the optimal shrinkage intensity for large covariance matrices.

Cited in: Beyond Markowitz: estimation error, noise and true diversification · Covariance estimation: why optimizers need shrinkage · Risk & attribution: methodology of risk decomposition and Brinson attribution · Glossary: Ledoit-Wolf shrinkage

Lehmann (1990) · Fads, Martingales, and Market Efficiency

Lehmann, Bruce N.. The Quarterly Journal of Economics 105 (1). doi:10.2307/2937816

One week's winners and losers reverse markedly in the following week; the profits survive bid-ask spreads and plausible transaction costs.

Cited in: Pairs trading and statistical arbitrage: idea, methods, research

Leibowitz and Henriksson (1988) · Portfolio Optimization Within a Surplus Framework

Leibowitz, Martin L.; Henriksson, Roy D.. Financial Analysts Journal 44 (2), pp. 43–51. doi:10.2469/faj.v44.n2.43

Markowitz optimization applied to the surplus of assets over liabilities: the risk-free asset is then an immunized bond portfolio rather than cash, and the optimal mix can differ greatly from the one without liabilities.

Cited in: Liability-driven investing and cash flow driven investing: covering liabilities with bonds · Glossary: Matching portfolio

Leisen and Reimer (1996) · Binomial models for option valuation - examining and improving convergence

Leisen, Dietmar P. J.; Reimer, Matthias. Applied Mathematical Finance 3 (4), pp. 319–346. doi:10.1080/13504869600000015

Convergence of binomial trees; new trees that converge to Black-Scholes smoothly and with order two (Leisen-Reimer).

Cited in: Option pricing: where fair option prices come from · Option pricer: how Portfolio Lab values options · Glossary: Binomial tree

Leland (1980) · Who Should Buy Portfolio Insurance?

Leland, Hayne E.. The Journal of Finance 35 (2), pp. 581–594. doi:10.1111/j.1540-6261.1980.tb02190.x

Asks for which investors portfolio insurance with limited losses and open-ended gains is worthwhile.

Cited in: CPPI: portfolio insurance with cushion, floor and multiplier · Glossary: Portfolio insurance

Leland (1988) · Portfolio Insurance and October 19th

Leland, Hayne E.. California Management Review 30 (4), pp. 80–89. doi:10.2307/41166528

A provider's look back at the 1987 crash: insurance became more expensive but did protect, and he attributes the crash to a lack of liquidity.

Cited in: CPPI: portfolio insurance with cushion, floor and multiplier · Glossary: Portfolio insurance

Lempérière et al. (2014) · Two Centuries of Trend Following

Lempérière, Yves; Deremble, Cyril; Seager, Philip; Potters, Marc; Bouchaud, Jean-Philippe. The Journal of Investment Strategies 3 (3), pp. 41–61. doi:10.21314/jois.2014.043

Trend following across four asset classes since 1800 (futures since 1960) with very high statistical significance; long-term trends show no decay, while short-term trends have weakened markedly.

Cited in: CTAs and managed futures: industry, position sizing, costs and crisis protection

Lenkey (2024) · The market impact of leveraged ETFs: A Survey of the literature

Lenkey, Stephen L.. Quantitative Finance and Economics 8 (4), pp. 815–840. doi:10.3934/qfe.2024031

Survey of studies on the effect of leveraged ETFs on end-of-day prices: mostly statistically significant but economically small relationships, often with methodological weaknesses; the market has enough liquidity for the rebalancing.

Cited in: How leveraged ETFs are built: swaps, daily rebalancing and gamma risk

Lerner and Nanda (2020) · Venture Capital's Role in Financing Innovation: What We Know and How Much We Still Need to Learn

Lerner, Josh; Nanda, Ramana. Journal of Economic Perspectives 34 (3), pp. 237–261. doi:10.1257/jep.34.3.237

The limits of the venture model: only a narrow band of technologies fits, a few investors direct a large share of the capital, and investor oversight has weakened.

Cited in: Venture capital: funding rounds, valuation, the power law and what research knows about returns

Leuz et al. (2017) · Who Falls Prey to the Wolf of Wall Street? Investor Participation in Market Manipulation

Leuz, Christian; Meyer, Steffen; Muhn, Maximilian; Soltes, Eugene; Hackethal, Andreas. National Bureau of Economic Research, Working Paper 24083 (November 2017, revised October 2023). doi:10.3386/w24083

Examines 470 pump-and-dump schemes in the German market using account data of more than 110,000 clients of a German bank: who takes part, how much is lost and how BaFin warnings work.

Cited in: Pump and dump and penny stocks: how the scam works · Glossary: Penny stock · Glossary: Pump and dump

Levine and Pedersen (2016) · Which Trend Is Your Friend?

Levine, Ari; Pedersen, Lasse Heje. Financial Analysts Journal 72 (3), pp. 51–66. doi:10.2469/faj.v72.n3.3

Time-series momentum and moving-average crossovers are equivalent in their general form; many trend filters can be written as weighted past returns.

Cited in: CTAs and managed futures: industry, position sizing, costs and crisis protection

Levy (1992) · Pricing European average rate currency options

Levy, Edmond. Journal of International Money and Finance 11 (5), pp. 474–491. doi:10.1016/0261-5606(92)90013-N

A lognormal approximation for average options that uses the exact first two moments of the arithmetic average.

Cited in: Option pricer: how Portfolio Lab values options · Glossary: Asian option

Lewis et al. (2022) · Measuring real activity using a weekly economic index

Lewis, Daniel J.; Mertens, Karel; Stock, James H.; Trivedi, Mihir. Journal of Applied Econometrics 37 (4), pp. 667–687. doi:10.1002/jae.2873

Describes the Weekly Economic Index (WEI) for the US, a weekly index of real economic activity built from ten series, eight of which are available on the Thursday after the week; in the first half of 2020 it gave an accurate estimate of GDP growth in the current quarter, and in the second half a less accurate one.

Cited in: Economic pulse: how Portfolio Lab calculates early indicators · Glossary: Leading indicator · Glossary: Weekly Economic Index

Lewis (1999) · Trying to Explain Home Bias in Equities and Consumption

Lewis, Karen K.. Journal of Economic Literature 37 (2), pp. 571–608. doi:10.1257/jel.37.2.571

A survey of explanations for home bias: investors hold far more domestic equities than portfolio theory suggests.

Cited in: Home bias: the preference for your home market and what it costs

Lewis (2010) · The Big Short: Inside the Doomsday Machine

Lewis, Michael. W. W. Norton.

Investors who bet against US subprime mortgages before the financial crisis, including Michael Burry with Scion Capital through credit default swaps.

Cited in: Legendary investors: the investment styles of the most famous investors, from Graham to Simons

Li et al. (2025) · Cryptocurrency Pump-and-Dump Schemes

Li, Tao; Shin, Donghwa; Wang, Baolian. Journal of Financial and Quantitative Analysis 60 (8), pp. 3622–3659. doi:10.1017/S0022109025000201

Cryptocurrency pump-and-dump schemes cause short spikes in price, volume and volatility followed by a rapid reversal, and transfer wealth from outsiders to insiders.

Cited in: Pump and dump and penny stocks: how the scam works · Crypto in institutional portfolios: access, custody, regulation and risk budget

Liao and Caramichael (2022) · Stablecoins: Growth Potential and Impact on Banking

Liao, Gordon Y.; Caramichael, John. Board of Governors of the Federal Reserve System, International Finance Discussion Papers 1334. doi:10.17016/IFDP.2022.1334

How stablecoins affect banks and lending depends on flows and reserves; a narrow-bank model gives the most stable peg but drains deposits from banks.

Cited in: Digital assets: tokenization, stablecoins, crypto securities and the digital euro

Ling and Naranjo (2015) · Returns and Information Transmission Dynamics in Public and Private Real Estate Markets

Ling, David C.; Naranjo, Andy. Real Estate Economics 43 (1), pp. 163–208. doi:10.1111/1540-6229.12069

US 1994–2012, adjusted for leverage, property types and fees: unlevered core REITs outperformed private real estate by 49 basis points a year and process new information faster.

Cited in: Real estate as an investment: rental property, REITs, open-end funds and private real estate

Lintner (1965) · The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets

Lintner, John. The Review of Economics and Statistics 47 (1). doi:10.2307/1924119

Develops the CAPM independently of Sharpe and links the choice of risky assets with borrowing at the risk-free rate.

Cited in: Beta and alpha: how closely a fund moves with the market · CAPM: the capital asset pricing model and the security market line · Glossary: CAPM

Litterman (2003) · Modern Investment Management: An Equilibrium Approach

Litterman, Bob. Wiley.

An equilibrium approach to investment management (Goldman Sachs), covering Black-Litterman and risk budgets, among other topics.

Cited in: Black-Litterman: incorporating your own views cleanly · Risk contribution: breaking portfolio risk down into its parts

Litterman (1996) · Hot Spots™ and Hedges

Litterman, Robert. The Journal of Portfolio Management 23 (5), pp. 52–75. doi:10.3905/jpm.1996.052

Breaks a portfolio's risk down into contributions per position in order to identify risk concentrations and effective hedges.

Cited in: Crypto in institutional portfolios: access, custody, regulation and risk budget · Risk & attribution: methodology of risk decomposition and Brinson attribution

Liu et al. (2023) · Anatomy of a Run: The Terra Luna Crash

Liu, Jiageng; Makarov, Igor; Schoar, Antoinette. National Bureau of Economic Research, Working Paper 31160. doi:10.3386/w31160

Reconstructs the run on the Terra ecosystem in May 2022 from blockchain and exchange data: large, better-informed holders withdrew first and lost less.

Cited in: Crypto in institutional portfolios: access, custody, regulation and risk budget · Digital assets: tokenization, stablecoins, crypto securities and the digital euro

Liu and Tsyvinski (2021) · Risks and Returns of Cryptocurrency

Liu, Yukun; Tsyvinski, Aleh. The Review of Financial Studies 34 (6), pp. 2689–2727. doi:10.1093/rfs/hhaa113

Crypto returns depend on crypto-specific factors (network and user growth rather than production costs), show strong time-series momentum and can be predicted with measures of investor attention.

Cited in: Crypto in institutional portfolios: access, custody, regulation and risk budget

Liu et al. (2022) · Common Risk Factors in Cryptocurrency

Liu, Yukun; Tsyvinski, Aleh; Wu, Xi. The Journal of Finance 77 (2), pp. 1133–1177. doi:10.1111/jofi.13119

Three factors (crypto market, size and momentum) explain the differences in expected returns across cryptocurrencies, including those of ten successful long-short strategies.

Cited in: Crypto in institutional portfolios: access, custody, regulation and risk budget

Ljung and Box (1978) · On a measure of lack of fit in time series models

Ljung, G. M.; Box, G. E. P.. Biometrika 65 (2), pp. 297–303. doi:10.1093/biomet/65.2.297

The Ljung-Box test for autocorrelation across several lags.

Cited in: Return forecasting models: ARIMA, GARCH, LSTM and machine learning · Asset analysis: methodology from correlation to cointegration · Glossary: Ljung-Box test

Lloyd (1982) · Least squares quantization in PCM

Lloyd, S.. IEEE Transactions on Information Theory 28 (2), pp. 129–137. doi:10.1109/tit.1982.1056489

The basis of the k-means method: alternately assign points to the nearest center and recompute the centers.

Cited in: Regime models: hidden Markov, Markov switching and more

Lo and MacKinlay (1988) · Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test

Lo, Andrew W.; MacKinlay, A. Craig. Review of Financial Studies 1 (1), pp. 41–66. doi:10.1093/rfs/1.1.41

Variance ratio test: US stock returns in 1962–1985 do not follow a pure random walk.

Cited in: Return forecasting models: ARIMA, GARCH, LSTM and machine learning · Asset analysis: methodology from correlation to cointegration · Glossary: Random walk · Glossary: Variance ratio

Lo and MacKinlay (1990) · When Are Contrarian Profits Due to Stock Market Overreaction?

Lo, Andrew W.; MacKinlay, A. Craig. Review of Financial Studies 3 (2), pp. 175–205. doi:10.1093/rfs/3.2.175

A substantial part of the profits from contrarian strategies comes from cross-autocorrelations: large stocks lead small ones.

Cited in: Pairs trading and statistical arbitrage: idea, methods, research

Lo et al. (2000) · Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation

Lo, Andrew W.; Mamaysky, Harry; Wang, Jiang. The Journal of Finance 55 (4), pp. 1705–1765. doi:10.1111/0022-1082.00265

Detects chart patterns such as head-and-shoulders or double bottoms automatically with kernel regression and compares the subsequent returns with the unconditional distribution.

Cited in: Technical analysis, chart patterns and candlesticks from a quant perspective

Lobosco and DiBartolomeo (1997) · Approximating the Confidence Intervals for Sharpe Style Weights

Lobosco, Angelo; DiBartolomeo, Dan. Financial Analysts Journal 53 (4), pp. 80–85. doi:10.2469/faj.v53.n4.2103

Derives approximate confidence intervals for the weights in style analysis.

Cited in: Sharpe's style analysis: what a fund really does · Returns-based style analysis: methodology

Long and Nickels (1996) · A Private Investment Benchmark

Long, Austin M.; Nickels, Craig J.. Presentation at the AIMR Conference on Venture Capital Investing, February 13, 1996; accessed October 27, 2026. Source

Proposes measuring private investments against a stock market index whose time-weighted return is converted into a money-weighted one (IRR); this became the Long-Nickels PME (index comparison method).

Cited in: Private markets methodology: analyzing funds, forecasting cash flows, planning commitments

López de Prado (2016) · Building Diversified Portfolios that Outperform Out of Sample

López de Prado, Marcos. The Journal of Portfolio Management 42 (4), pp. 59–69. doi:10.3905/jpm.2016.42.4.059

Introduces hierarchical risk parity: weights based on a hierarchical clustering of correlations instead of the inverse of the covariance matrix.

Cited in: Beyond Markowitz: estimation error, noise and true diversification · Hierarchical risk parity: building portfolios from clusters · Glossary: Hierarchical risk parity

López de Prado (2018) · Advances in Financial Machine Learning

López de Prado, Marcos. Wiley.

Textbook on backtesting and machine learning in finance, covering overfitting and HRP, among other topics.

Cited in: Backtest overfitting: when the past looks too good · Hierarchical risk parity: building portfolios from clusters · Probability of backtest overfitting: does the best variant deliver what the backtest promises? · Return forecasting models: ARIMA, GARCH, LSTM and machine learning · Glossary: Overfitting · Glossary: Cross-validation

López de Prado and Lewis (2019) · Detection of false investment strategies using unsupervised learning methods

López de Prado, Marcos; Lewis, Michael J.. Quantitative Finance 19 (9), pp. 1555–1565. doi:10.1080/14697688.2019.1622311

Uses a clustering method to estimate the number of effectively uncorrelated trials, the quantity needed for multiple testing and the deflated Sharpe ratio.

Cited in: Overfitting check and diversification return: the calculations in Backtest and Tactical · Glossary: Effective number of trials

Lopez-Lira and Tang (2026) · Can ChatGPT forecast stock price movements? Return predictability and large language models

Lopez-Lira, Alejandro; Tang, Yuehua. Journal of Financial Economics 184, pp. 104335. doi:10.1016/j.jfineco.2026.104335

Language models rate headlines and predict the price reaction and the subsequent drift, especially for small stocks and bad news; returns decline as adoption spreads.

Cited in: Alternative data: job ads, Reddit, X, satellites and card payments · Return forecasting models: ARIMA, GARCH, LSTM and machine learning · Glossary: Sentiment analysis · Glossary: Language model

Lou and Polk (2022) · Comomentum: Inferring Arbitrage Activity from Return Correlations

Lou, Dong; Polk, Christopher. The Review of Financial Studies 35 (7), pp. 3272–3302. doi:10.1093/rfs/hhab117

Comomentum measures the correlation of excess returns among the stocks a typical momentum strategy bets on; when it is high, the returns of momentum stocks reverse sharply, which is a sign of crowded momentum trading.

Cited in: Momentum crashes: why momentum collapses rarely but violently, and what volatility scaling and crowding measures show · Glossary: Crowding · Glossary: Comomentum

Loudon et al. (2006) · Hedge Fund Risk Factors and the Value at Risk of Fixed Income Trading Strategies

Loudon, Geoff; Okunev, John; White, Derek. The Journal of Fixed Income 16 (2), pp. 46–61. doi:10.3905/jfi.2006.656009

Develops a procedure that removes autocorrelation of any order from reported returns (Okunev-White method) and then estimates the risk factors and value at risk of hedge funds.

Cited in: Measuring private markets: J-curve, cash flows, smoothing and public proxies

Loughran and McDonald (2011) · When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks

Loughran, Tim; McDonald, Bill. The Journal of Finance 66 (1), pp. 35–65. doi:10.1111/j.1540-6261.2010.01625.x

General-purpose dictionaries wrongly classify many words in annual reports as negative; the authors develop their own word lists for financial texts.

Cited in: Alternative data: job ads, Reddit, X, satellites and card payments · Glossary: Sentiment analysis

Lusardi and Mitchell (2014) · The Economic Importance of Financial Literacy: Theory and Evidence

Lusardi, Annamaria; Mitchell, Olivia S.. Journal of Economic Literature 52 (1), pp. 5–44. doi:10.1257/jel.52.1.5

Survey of research on financial knowledge: financial literacy as an investment in human capital, measurement with surveys, poorly informed groups and consequences for decisions.

Cited in: Glossary: Financial literacy

Lustig and Verdelhan (2007) · The Cross Section of Foreign Currency Risk Premia and Consumption Growth Risk

Lustig, Hanno; Verdelhan, Adrien. American Economic Review 97 (1), pp. 89–117. doi:10.1257/aer.97.1.89

Portfolios of high-interest currencies earn positive excess returns and portfolios of low-interest currencies negative ones, explained by consumption risk, because high-interest currencies depreciate when consumption growth is weak.

Cited in: Carry trade: earning interest with currencies and bonds · Glossary: Carry trade

Lustig et al. (2011) · Common Risk Factors in Currency Markets

Lustig, Hanno; Roussanov, Nikolai; Verdelhan, Adrien. Review of Financial Studies 24 (11), pp. 3731–3777. doi:10.1093/rfs/hhr068

A slope factor of high-minus-low interest rate currencies explains most of the return differences; buying high-interest currencies and borrowing in low-interest currencies means bearing global risk.

Cited in: Carry trade: earning interest with currencies and bonds · Carry backtest: methodology for FX and bond carry · Glossary: Target currency · Glossary: Dollar factor

Lux and Marchesi (1999) · Scaling and criticality in a stochastic multi-agent model of a financial market

Lux, Thomas; Marchesi, Michele. Nature 397 (6719), pp. 498–500. doi:10.1038/17290

In a model with many traders, scaling laws of prices arise from the interaction of participants, although the news has neither power laws nor volatility clustering.

Cited in: Glossary: Agent-based model

Lynch and Mendenhall (1997) · New Evidence on Stock Price Effects Associated with Changes in the S&P 500 Index

Lynch, Anthony W.; Mendenhall, Richard R.. The Journal of Business 70 (3), pp. 351–383. doi:10.1086/209722

Since October 1989, S&P has announced index changes about a week in advance where possible; additions and deletions then show abnormal returns that only partly reverse.

Cited in: Smart indexing: added value for index funds around corporate actions and index changes

Lynch and Rothchild (2000) · One Up on Wall Street: How to Use What You Already Know to Make Money in the Market

Lynch, Peter; Rothchild, John. Simon & Schuster, revised edition (first published 1989).

The former manager of the Fidelity Magellan Fund on stock picking for private investors: understand the business, sort stocks into categories, measure the P/E against earnings growth.

Cited in: Legendary investors: the investment styles of the most famous investors, from Graham to Simons · Glossary: GARP

Lyon et al. (1999) · Improved Methods for Tests of Long-Run Abnormal Stock Returns

Lyon, John D.; Barber, Brad M.; Tsai, Chih-Ling. The Journal of Finance 54 (1), pp. 165–201. doi:10.1111/0022-1082.00101

BHARs with carefully constructed reference portfolios and a skewness-adjusted t-test, or calendar-time portfolios, are well specified in random samples but often not in non-random ones.

Cited in: Event studies: how to measure and test price reactions to events · Glossary: Buy-and-hold abnormal return

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