Mutual funds and ETFs whose main directive is index replication incur adverse selection costs from responding to changes in the composition of the stock market because indices rebalance in response to composition changes (due to IPOs, delistings, additions, deletions, new seasoned issuance, and

Dividends are the comfort food of investing. Who wouldn’t love feeling like they’re getting a seemingly “free” payout just for holding onto a stock? It’s no wonder so many investors are drawn to the siren call of yield. As with all good things, there’s a little more—perhaps a whole lot

Bond Exchange-Traded Funds (ETFs) help people invest in bonds without having to buy them one by one. Instead, they let investors buy a mix of bonds all at once, making it easier and cheaper to trade. This is especially helpful for bonds that are usually harder to buy or sell. Because of bond ETFs,

When it comes to choosing an investment strategy, most investors—whether they realize it or not—are looking for something that: Beats the benchmark Never loses money Works all the time And here’s the harsh reality: this unicorn of a strategy doesn’t exist. Anyone promising you all three is

This study looks at how stocks and bonds move together over time, using data from 1875 to 2023. The authors find that inflation, interest rates, and government stability affect this relationship. When inflation and interest rates go up, stocks and bonds tend to move in the same direction, making

Conventional wisdom can be defined as ideas that are so ingrained in our belief system that they go unchallenged. Unfortunately, much of the “conventional wisdom” about investing is wrong. One example of erroneous conventional wisdom is that investors seeking higher returns should invest in

Highly illiquid assets trade infrequently making it difficult to know their true market value. To address this issue, funds that invest in illiquid assets create fair valuation estimates at periodic intervals. These valuation estimates determine the share values at which interval and tender offer

Academics have long been aware of the risks of data mining—torturing the data until it confesses. The concern is that correlation of variables doesn’t imply that the correlation is a result of causation. That is the reason that the prevailing academic standard for researchers is that they should

Machine learning models have proven effective in predicting stock returns using lagged stock characteristics, but their success is influenced by a wide range of modeling choices. One critical, yet often overlooked, choice is how stocks are weighted in the objective function during training, with

By examining data going back to 1792, McQuarrie’s study comes up with a surprising observation : stocks are not as dominant as once thought. The variability of the performance of stocks vs. bonds across various time periods is dramatic. So buckle up, stocks do not invariably outperform bonds.

Investing formulas are simple, easy-to-implement, systematic, stock screeners that provide instructions on how to outperform the total stock market. Marcel Schwartz and Matthias Hanauer, authors of the December 2024 study, “Formula Investing,” evaluated the effectiveness of four such popular

This paper investigates the puzzling decline in the price impact of S&P 500 index additions and deletions over the past four decades, despite the rapid growth of passive investing. It explores potential explanations, including changes in market liquidity and efficiency, shifts in the composition

Systematic factor-driven value strategies have underperformed broad market indices (such as the S&P 500) over the past 15+ years. That has led many to question whether intangible assets, such as patents and proprietary software, are properly treated. Current accounting standards, which require

This paper examines various frameworks and proxies for forecasting long-term expected returns (E(R)) over periods of 10 to 20 years, focusing on out-of-sample performance and the impact of these forecasts on investment decisions. It compares models based on yield, valuation, and the combination of

This article analyzes various reasons why momentum strategies might work outside US borders. While the US story is firmly rooted in behavioral biases, is the same true on an international scale? That seems logical and likely. In fact, the authors conclude that a “slow diffusion of news best

Since the turn of the century portfolios have been exposed to four periods of crisis: the bursting of the tech bubble and the events of September 11, 2001, from 2000-2002; the Great Financial Crisis in 2007-2008, the COVID-19 pandemic in 2020, and the period of persistent inflation in 2022 when both

This paper examines the time-varying roles of subjective expectations in driving stock price and return variations. Specifically, it focuses on how subjective cash flow expectations (CF) and discount rate expectations (DR) contribute to stock price fluctuations across different economic conditions,

An anomaly is a pattern in stock returns that deviates from what is expected based on established financial theories or models. These patterns can sometimes present opportunities for abnormal returns. However, they are often inconsistent and challenging to exploit. Many anomalies have achieved

Do we have a chaotic “factor zoo” as some critics maintain? Is there a replication crisis in the research on factors? The authors of this research answer in the negative and argue that 82% of factors are replicable, the factor zoo is well-organized, and the factors are legit. Such bold

One of the big problems for the first formal asset pricing model developed by financial economists, the CAPM, was that it predicts a positive relationship between risk and return while, empirical studies have found the actual relationship to be basically flat, or even negative. In addition,

Measures of asset growth add considerable explanatory power to asset pricing models, but wait, there’s a twist. The formulation for measuring asset growth in risk models, such as the 5-Factor Fama-French (FF5F) or the Hou-Xue-Zhang (HXZ), do not necessarily align with traditional measures of firm

Among the earliest challenges to the efficient markets hypothesis was the observation that stock prices react to investor demand unrelated to fundamentals. One example is the abnormal returns to additions and deletions to the S&P 500 Index. Robin Greenwood and Marco Sammon, authors of the

While portfolio optimization typically focuses on risk and return prediction, implementation costs critically matter. Unfortunately, predicting trading costs is challenging because the largest component for a large investor is price impact, which depends on the size of the trade, the amount traded

If the task is to identify a firm’s true profitability, can AI outsmart seasoned analysts? Given the increasingly bloated nature of financial reports, decoding the twists and turns associated with events like obscure one-time gains and out-of-nowhere expenses to extract core earnings has become

Artificial Intelligence (AI) offers the intriguing potential to revolutionize investment decision-making by providing important advantages such as: Enhanced Data Analysis: AI can process and analyze vast amounts of data from various sources, including financial news, market trends, and company

A weaker-than-expected July jobs report, with the unemployment rate increasing to 4.3%, officially triggered the Sahm Rule, causing investors to worry that the Federal Reserve may be behind the curve in cutting interest rates to prevent a recession. (The August report showed an increase in payroll

What are the Research Questions? The research questions are as follows: How can textual analysis of business news, specifically The Wall Street Journal (WSJ), be used to measure the state of the economy? What is the structure of news coverage related to economic events, and how do these topics

As the annual SPIVA studies demonstrate, index funds persistently outperform the vast majority of actively managed funds, even before considering taxes. With that said, most investors are unaware that there are weaknesses of index funds that result from their strategy to replicate the return of an

The annual SPIVA has documented that retail mutual funds underperform with great persistence, with any persistence of outperformance not significantly greater than would be randomly expected. The large body of research on the failure of active management led Charles Ellis to famously call it a

The research team at Verdad does some of the most interesting and innovative empirical financial research that is consistently rigorous and based on systematic approaches that are implementable and replicable, providing confidence in the findings. In a recent piece, “Analogous Market Moments,”

Regression analysis is a statistical method used to estimate and model the relation between a dependent variable and one or more independent variables. The dependent variable, also called the observation, is the variable being explained or predicted. The Independent variables are used to explain or

The paper examines several key questions related to how retail investors’ trading behaviors in cryptocurrencies differ from their behaviors in traditional asset classes like stocks and commodities. Are cryptos different? Evidence from retail trading Shimon Kogan, Igor Makarov, Marina Niessner,

Bond futures are often assumed to be more tax-efficient than bond ETFs. My analysis indicates that this assumption is frequently incorrect. Although investors might view the 60/40 tax treatment of futures as advantageous, a futures strategy faces several challenges compared to a bond ETF, including

Empirical research, including the 2020 study “An Empirical Evaluation of Tax-Loss Harvesting Alpha” and the 2023 study “Expected Loss Harvest from Tax-Loss Harvesting with Direct Indexing,” has found that tax-loss harvesting strategies in separately managed accounts (SMAs) can improve the

The research questions are as follows: How does AI perform compared to human analysts in predicting stock returns? Under what circumstances do human analysts retain their advantage over AI? What is the impact of combining human analysts with AI (the “Man + Machine” approach) on stock prediction

While the research, commentary and speculation about the failure of value factor strategies over the last decade or two continues along a number of avenues, we haven’t yet seen a movement back towards fundamental analysis or a discounted cash flow (DCF) approach. In this paper, the authors argue

As a result of the trading required to capture the premiums that drive factor strategies investors may face significant tax liabilities. The challenge for the portfolio manager is to incorporate tax-efficient trading practices at each rebalance to mitigate tax impacts and ultimately avoid

Wallstreetbets has become an increasingly prominent source of investment research, particularly for risk-seeking retail investors. The excitement from the GameStop episode resulted in the forum growing from 500,000 users in July of 2018 to 10.7 million users by June 2021. Do their recommendations

What is a Bayesian solution? Good question. Bayesian statistics, named for Thomas Bayes, is a structured framework that allows one to update the probability of an event occurring as new data about that event becomes available. In the context of the infamous Factor Zoo in investing, Bayes’ rule

While publicly traded stocks, bonds, and real estate have their prices constantly adjusted throughout the day, leading to lots of volatility, private capital managers have significant discretion as to when and how they mark-to-market or mark-to-model their portfolios (typically valued quarterly).

It is well documented in the literature that retail investors have an irrational preference (from a traditional finance perspective) for investing in high-volatility stocks which have lottery-like distributions—those that exhibit positive skewness and excess kurtosis (fat tails). Studies, such as

This paper explores several key aspects related to household consumption behavior during the Great Financial Crisis of 2008-2009, with a focus on the impact of salient adverse macroeconomic announcements. Spending Less After (Seemingly) Bad News Garmaise, Levi and Lustig Journal of Finance, 2024 A

Over the period January 2000-March 2024, the S&P 500 Index returned 7.4% per annum, outperforming the return of 2.2% per annum of Japanese large stocks (MSCI/Nomura data) by 5.2 percentage points per annum. The outperformance has been even greater since 2010, with the S&P 500 Index returning

The focus of this paper is to test an effective rebalancing method that prioritizes trades with the strongest signals to capture more of the factor premium while reducing turnover and trading costs. The authors coined the term “smart rebalancing” which involves prioritizing trades based on the

The important role played by short sellers, who, through their actions, keep prices efficient by preventing overpricing and the formation of price bubbles in financial markets, has received increasing academic attention in recent years. Research into the information contained in short-selling

This paper explores the effectiveness of the BJZZ algorithm, developed by Boehmer, Jones, Zhang, and Zhang (2021), in identifying and signing retail trades executed off exchanges with subpenny price improvements. A (Sub)penny For Your Thoughts: Tracking Retail Investor Activity in TAQ Barber, Huang,

Volatility laundering causes the risk-adjusted returns and the diversification benefits of private equity to be significantly overstated. However, the problem of volatility laundering is not a problem for all private investments, specifically not for high-quality, floating rate, private credit.

Finance has seen unprecedented growth in the use of artificial intelligence, specifically in machine learning models. Applications have included portfolio construction, stock analysis and in this case, the prediction of stock market returns. This paper discusses the benefits of using complex models

Of the hundreds of equity factors identified in the financial literature, there were only five that met the criteria Andrew Berkin and I established in our book Your Complete Guide to Factor-Based Investing. To be considered for investment, a factor must have provided a premium that was persistent

Among the many factors cited in academic research, only a handful have been sufficiently reliable for use in asset pricing models. One of those is momentum. The evidence has been robust for not only cross-sectional (relative) and time-series (absolute or trend) momentum, but also for factor