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

The increased popularity of social media as a forum for market participants to post and exchange opinions has been accompanied by heightened interest from academic researchers who have sought to determine if there is valuable information in the postings. For example, the June 2020 study “Do

In the research reviewed here, the authors analyze the relationship of aggregate market liquidity to the time-series performance of reversal strategies. The strength and persistence of reversals and reversal driven strategies appear to be different depending on specific risk features of those

The ability to predict stock returns and the equity risk premium (ERP) is of great interest to academics, financial practitioners, and investors, as future estimated returns have implications for asset allocations. To date, the best metric we have for forecasting future equity returns and the ERP is

Momentum continues to receive much attention from researchers because of the strong empirical evidence. Out of the hundreds of exhibits in the factor zoo, momentum (both cross-sectional [long-short] and absolute [trend]) was one of just five equity factors that met all the criteria (persistent,

Can AI models improve on the failures in predicting returns strictly from a practical point of view? In this paper, the possibilities are tested with a battery of AI models including linear regression, dimensional reduction methods, regression trees and neural networks. These machine learning models

The justification for neutralizing sectors in factor strategies is a work in progress. To date, academic researchers haven’t had an empirical model to mimic the impact of removing sector “effects” on the measurement and performance of factor strategies. The authors develop and test a

While empirical research on cross-sectional (long-short) momentum has shown high returns, investors have also experienced huge drawdowns—momentum exhibits both high kurtosis and negative skewness. Since 1926, there have been several momentum crashes that featured short but persistent periods of

Out of the hundreds of exhibits in the factor zoo, momentum was one of just five equity factors that met all the criteria (persistent, pervasive, robust, implementable, and intuitive) Andrew Berkin and I established in our book Your Complete Guide to Factor-Based Investing. Because of the strong

The benefits of diversification are well known. In fact, it’s been called the only free lunch in investing. Investors who seek to benefit from diversification of the sources of risk and return of their portfolios must accept that adding unique sources of risk means that their portfolio will

Perhaps the most well-documented and researched asset pricing anomaly is momentum—the tendency of past winner stocks to outperform past loser stocks over the next several months. While average time-series momentum (trend following) returns have been high, strategies employing trend following have

Academic research, including the studies “Do Investors Overpay for Stocks with Lottery-like Payoffs? An Examination of the Returns on OTC Stocks,” “Lottery Preference and Anomalies” and “Do the Rich Gamble in the Stock Market? Low Risk Anomalies and Wealthy Households,” has found that

“Conventional wisdom” can be defined as ideas that are so accepted that they go unquestioned. Unfortunately, conventional wisdom is often wrong. Two examples are that millions of people once believed the conventional wisdom that the Earth is flat, and millions also believed that the Earth is the

The academic research, including the 2023 studies “Lottery Preference and Anomalies” and “Do the Rich Gamble in the Stock Market? Low Risk Anomalies and Wealthy Households,” the 2022 study “Lottery Demand and the Asset Growth Anomaly,” and the 2014 study “Do Investors Overpay for

The paper aims to provide insights into the dynamics of benchmark selection, the effectiveness of Relative Performance Evaluation ( RPE ) incentivization, and the broader implications for fund performance and market competition. Self-Declared Benchmarks and Fund Manager Intent: “Cheating” or

Expectations of future earnings growth matter a great deal to valuations because investors, in their collective wisdom, assign higher valuations to companies they expect will grow more quickly in the future (growth stocks). In contrast, firms expected to show slower growth (value stocks) are

One use of the NLP (natural language processing) features of ChatGPT is to search out patterns in the immense amounts of news, data and other sources of information about specific stocks, and then efficiently convert them into summaries valuable for all types of investors. Can this be accomplished

In our book The Incredible Shrinking Alpha, Andrew Berkin and I presented the evidence demonstrating that the markets have become more efficient over time, making it more difficult to outperform the market on a risk-adjusted basis. Market efficiency explains the lack of persistent outperformance of

In our book, “The Incredible Shrinking Alpha,” Andrew Berkin and I identified four key trends that were increasing the hurdles for active managers in their quest to generate alpha: Academic research has been converting what was once alpha into beta (common factors that could be accessed at much

What are the Research Questions? This paper examines the decisions of sophisticated market participants – experienced institutional portfolio managers (PMs) – and the authors ask the following questions: Is there a significant difference in performance between buying and selling decisions made

Because of the strong evidence, momentum continues to receive much attention from researchers. Out of the hundreds of exhibits in the factor zoo, one of just five equity factors that met all the criteria (persistent, pervasive, robust, implementable, and intuitive) Andrew Berkin and I established in

Popular benchmarks in academic research studies to evaluate the performance of investment strategies are cap-weighted (market-, or value-weighted), and equal-weighted portfolios. Capitalization-weighted portfolios are used because they are the simplest and cheapest to implement, representing the

As professor John Cochrane observed, the literature on investment factors now fills a veritable “factor zoo,” with hundreds of options. How do investors select from among this huge array of possibilities? In order to minimize the risk that outcomes result from data mining, in our book “Your

Is there a defensive equity factor? Can one be built? Although it seems like an easy question, the answer is not straightforward. The authors of this piece argue for a careful assessment of factor strategies to deliver a defensive profile convincing enough to attract investors. A defensive

Arbitrageurs keep markets efficient by moving prices to reflect their fundamental values. However, anomalies can persist because of limits to arbitrage—the costs and risks of shorting. The costs and risks of shorting, however, are not the only risks that arbitrageurs face. The publication of

That riskier assets should command higher expected returns is the most basic of asset pricing theories. Clearly, financial distress is a risk characteristic, but it presents a puzzle, as there has not been a linear relationship between it and stock returns. For example, John Birge and Yi Zhang,

The question of whether stock returns are predictable is of long-standing interest to both academics and investment practitioners. Commonly accepted investment strategies, for example, will behave quite differently in the presence of stock return predictability. The research literature is unclear on

Because of the strong evidence, momentum continues to receive much attention from researchers. Out of the hundreds of exhibits in the factor zoo, one of just five equity factors that met all the criteria (persistent, pervasive, robust, implementable, and intuitive) Andrew Berkin and I established in

The study emphasizes the importance of integrating machine learning with other tools for investment managers, pension-plan administrators, financial advisors, and independent analysts to help investors select active mutual funds with positive alpha. It also highlights the significance of fund

The timing of equity factor premiums has a strong allure for investors because academic research has found that factor premiums are both time-varying and dependent on the economic cycle. For example, Arnav Sheth and Tee Lim, authors of the December 2017 study “Fama-French Factors and Business

Abstract: One of the problems for investment funds is that success contains the seeds of destruction as cash inflows follow outperformance. In his seminal 2005 paper, “Five Myths of Active Portfolio Management,” Jonathan Berk suggested asking, “Who gets money to manage?” He answered that

Market efficiency, higher trading costs and higher expense ratios are not the only hurdles to successful active management (market timing and individual security selection). For taxable investors, the burden of higher taxes raises the hurdle.(1) From 2002 until now, S&P Dow Jones Indices has

Momentum investors utilize different timeframes to identify high momentum equities: past 6, 9, 12 months as an example. Obviously, there is a significant degree of overlap in momentum stocks identified across various past time frames. However, there has been little research focused on understanding

Many retail investors focus on generating what they consider to be income, leading to the popularity of dividend-focused strategies. To take advantage of this demand, investment firms have marketed covered call strategies that are purported to not only generate income but also reduce volatility.

How long will it take for the current level of inflation to subside? If history is any guide, it could take quite a while. Across 198 policy interest rate hikes of at least 1%, a decrease of 1% in inflation took 2 to 4 years (Havranke and Rusnak, 2013). The authors of this research article conduct

Attracted by the glamour and potential for lottery-like returns, global private equity (PE) assets under management reached $4.2 trillion in 2022. PE involves pooling capital to invest in private companies by providing venture capital (VC) to startups or by taking over and restructuring mature firms

This paper focuses on “organization capital,” representing intangible assets in a firm’s key employees that is not captured by classic value measures such as book-to-market. The authors propose a structural model to analyze the impact of organizational capital on asset prices and argue that

The increasing role of intangible assets compared to physical assets in our economy has been accompanied by increased research into their impact on asset prices and returns. Studies such as the 2020 papers “Explaining the Recent Failure of Value Investing,” “Intangible Capital and the Value

Idiosyncratic volatility (IVOL) is the volatility of a security that cannot be explained by overall market volatility—it is the risk unique to a particular security. IVOL contrasts with systematic risk, which is the risk that affects all securities in a market (such as changes in interest rates or

This paper acknowledges the pivotal role of earnings calls in disseminating value-relevant information, with particular emphasis on the Q&A segment. However, it confronts the inherent challenge posed by the unstructured nature of language in these calls, complicating quantitative analysis. In

The Jegadeesh and Titman (1993) paper on momentum established that an equity trading strategy consisting of buying past winners and selling past losers, reliably produced risk-adjusted excess returns. The Jegadeesh results have been replicated in international markets and across asset classes. As

Financial time series that are structured as data sampled at a uniform time interval, e.g., hourly, daily, weekly, or monthly, are called discrete-time time series and referred to, from a digital signal processing (DSP) perspective, as being in the “time domain.” Technical market analysts