Since it is likely that both the Relative Sentiment and Trend Following strategies will underperform at some points in the future, “a 50-50 combination of TF and RS might reduce the emotional volatility an investor may experience from holding only the underperforming strategy.”
Are active managers victims of the same bias as individual investors? That is the question we’ll explore in this paper.
Soroush Ghazi and Mark Schneider authors of the August 2022 study “Market Risk and Speculation Factors” decomposed the excess market return (the equity risk premium) into speculative (in the simple sense that it is negative, reflecting a premium investors pay to hold assets that are more subject to speculative demand) and non-speculative, or risk (in the simple sense that it is positive, a necessary characteristic for a factor to reflect compensation for risk) components.
This article discusses the academic research about the Momentum Gap and the role that its predictive potential may have in reducing momentum crashes, hence possibly improving performance.
We discuss the academic research about the causal effect of indexing on arbitrage conditions and price discovery.
It is well documented in the literature that over the long term, low-investment firms have outperformed high-investment firms—with the negative relation between asset growth (AG) and future stock returns particularly featured by the overvaluation of high AG stocks.
Atilgan et al. contribute to the momentum literature with “Momentum and Downside Risk in Emerging Markets.”
This article discusses what academic research says about the relationship between the demand for leverage and management fees.
Consumer demand drives the cash flows of consumer-oriented companies. Thus, they should serve as a reliable source of information to predict future fundamentals above and beyond the information contained in financial statements and readily available market data.
We examine the short-duration premium using pre-scheduled economic, monetary policy, and earnings announcements. We provide high-frequency evidence that duration premia associated with revisions of economic growth and interest rate expectations are consistent with asset pricing models but cannot explain the short-duration premium. Instead, we show that the trading activity of sentiment-driven investors raises prices of long-duration stocks, which lowers their expected returns, and results in the short-duration premium. Long-duration stocks have the lowest institutional ownership, exhibit the largest forecast errors at earnings announcements, and show the highest mispricing scores.
An equal-weighted portfolio of Best Brands (BBs) in the U.S. earns an excess return of 25 to 35 bps per month during the period 2000-2020. This result is remarkably robust across various factor models and therefore is not driven by exposure to common (risk) factors. The excess returns of the BB portfolio are not due to firm characteristics, industry composition, or small-cap stocks. We provide evidence suggesting that expensing investments in brands (instead of capitalizing them) and the tendency to underestimate the effect of brand name on generating future earnings are two mechanisms contributing to the excess returns.
Non-standard errors capture uncertainty due to differences in research design choices. We establish substantial variation in the design choices made by researchers when constructing asset pricing factors. By purposely data mining over two thousand different versions of each factor, we find that Sharpe ratios exhibit substantial variation within a factor due to different construction choices, which results in sizable non-standard errors and allows for p-hacking. We provide simple suggestions that reduce the average non-standard error by 70%. Our study has important implications for model selection exercises.
This paper provides new evidence showing that carbon transition risk is becoming increasingly material and is priced both in equity and debt markets. We find that there is a widespread price-earnings discount linked to corporate carbon emissions. This discount varies, however, by sector and trends differently in Europe than in the US. We also find that a small discount emerges for corporate bonds, although it is statistically significant only for small caps. Finally, we find evidence that the pricing discount also emerges, albeit to a smaller extent, for other greenhouse gas emissions.
I am grateful for this book because I am less confused about sustainable investing, and I am inspired to learn more about the topic. I commend Larry and Sam’s work for being technically accurate and complete, while accessible to a reader who isn’t an expert on the subject and is looking to learn more.
Litigation finance is a rapidly growing niche asset class focused on debt and equity investments in litigation claims and law firms. We find that in-sample returns in the space have been in excess of 20% annually with limited correlation to other investment areas. This apparent excess return may be due to information asymmetry and barriers to entry in the space. Our findings highlight the opportunities and risks for investors in this nascent asset classes and suggest such excess returns are due in part to limits to the speed with which efficient markets take hold.
Across markets, momentum is one of the most prominent anomalies and leads to high risk-adjusted returns. On the downside, momentum exhibits huge tail risk as there are short but persistent periods of highly negative returns. Crashes occur in rebounding bear markets, when momentum displays negative betas and momentum volatility is high. Based on ex-ante calculations of these risk measures we construct a crash indicator that effectively isolates momentum crashes from momentum bull markets. An implementable trading strategy that combines both systematic and momentum-specific risk more than doubles the Sharpe ratio of original momentum and outperforms existing risk management strategies over the 1928–2020 period, in 5 and 10-year sub-samples, and an international momentum portfolio.
What are the consequences of widespread ESG-based portfolio exclusions on the expected returns of firms subject to exclusion? We consider two possible theoretical explanations. 1) Short-term price pressure around the exclusions leading to correction of mispricing going forward. 2) Long term changes in required returns. We use the exclusions of Norwegian Government Pension Fund Global (GPFG -`The Oil Fund') to investigate. GPFG is the world's largest SWF, and its ESG decisions are used as a model for many institutional investors. We construct various portfolios representing the GPFG exclusions. We find that these portfolios have significant superior performance (alpha) relative to a Fama-French five factor model. The sheer magnitude of these excess returns (5\% in annual terms) leads us to conclude that short-term price pressure can not be the only explanation for our results, the excluded firms expected returns must be higher in the longer term.
Using multiple short sale measures, we examine the predictive power of short sales for future stock returns in 38 countries from July 2006 to December 2014. We find that the days-to-cover ratio and the utilization ratio measures have the most robust predictive power for future stock returns in the global capital market. Our results display significant cross-country and cross-firm differences in the predictive power of alternative short sale measures. The predictive power of shorts is stronger in countries with non-prohibitive short sale regulations and for stocks with relatively low liquidity, high shorting fees, and low price efficiency.
Managed portfolios that exploit positive first-order autocorrelation in monthly excess returns of equity factor portfolios produce large alphas and gains in Sharpe ratios. We document this finding for factor portfolios formed on the broad market, size, value, momentum, investment, prof- itability, and volatility. The value-added induced by factor management via short-term momentum is a robust empirical phenomenon that survives transaction costs and carries over to multi-factor portfolios. The novel strategy established in this work compares favorably to well-known timing strategies that employ e.g. factor volatility or factor valuation. For the majority of factors, our strategies appear successful especially in recessions and times of crisis.
Reschenhofer’s findings demonstrate the important role that portfolio construction rules (such as creating efficient buy and hold ranges or imposing screens that exclude stocks with negative momentum) play in determining not only the risk and expected return of a portfolio but how efficiently the strategy can be implemented (considering the impact of turnover and trading costs)—wide (narrow) thresholds reduce (increase) portfolio turnover and transactions costs, thereby increasing after-cost returns and Sharpe ratios. His findings also provide support for multiple characteristics-based scorings to form long-only factor portfolios, encouraging the combination of slow-moving characteristics (such as value, investment and/or profitability) conditional on fast moving characteristics (such as momentum), to reduce portfolio turnover and transactions cost. Fund families such as AQR, Avantis, Bridgeway and Dimensional use such an approach, integrating multiple characteristics into their portfolios conditional on momentum signals.
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