Hello all,

We hope your year is off to a great start! In this year's first newsletter, we're excited to announce the publication of the first issue of the RF for 2025, featuring nine articles. Below, you'll find their summaries and abstracts.

Happy reading!

Volume 29, Issue 1, January 2025

ARTICLES

• Liquidity and the strategic value of information (Editor's Choice)
  by Ohad Kadan and Asaf Manela
• Securities financing and asset markets: new evidence
  by Tomas Breach and Thomas B King
• Trust and delegated investing: a Money Doctors experiment
  by Maximilian Germann, Lukas Mertes, Martin Weber, and Benjamin Loos
• Tradable Risk Factors for Institutional and Retail Investors
  by Andreas Johansson, Riccardo Sabbatucci, and Andrea Tamoni
• Margin constraints and asset prices
  by Jungkyu Ahn
• Credit ratings: strategic issuer disclosure and optimal screening
  by Jonathan B Cohn, Uday Rajan, and Günter Strobl
• Large orders in small markets: execution with endogenous liquidity supply
  by Agostino Capponi, Albert J. Menkveld, and Hongzhong Zhang
• Empirical determinants of momentum: a perspective using international data
  by Amit Goyal, Narasimhan Jegadeesh, and Avanidhar Subrahmanyam
• It’s not (only) personal, it’s business: personal bankruptcy exemptions and business credit
  by Rebel A Cole, Jason Damm, John Hackney, and Masim Suleymanov

For the full issue, please visit Issue 1 of Volume 29 on our website.

Liquidity and the strategic value of information (Editor's choice)

Authors: Ohad Kadan and Asaf Manela

In financial markets, the value of information is a crucial factor for investors, analysts, and money managers who allocate resources to research assets. Understanding how much investors would pay for information has broad implications, from determining security analysts’ compensation to penalizing insider trading.

Our paper presents a simple yet powerful measure for estimating the value of information, even in complex markets. Building on the framework introduced by Kyle (1985), where a monopolist informed trader’s value of information is determined by the ratio of an asset’s fundamental variance to its price impact, we extend this to a more general setting. In our model, multiple investors receive imperfect signals about asset fundamentals, and each trader must account for their effect on prices. The ratio of fundamental variance to price impact still serves as a tight approximation for the value of information in this scenario.

Our theoretical contribution shows that this ratio provides a good estimate of the value of information in markets with multiple informed investors, as long as their signals are not highly correlated. This statistic can be easily estimated using high-frequency stock data, providing practical insights for both researchers and practitioners.

Empirically, we estimate this value of information for US-listed stocks on a daily basis over an extended sample period, leveraging intraday data. The findings indicate that the value of information spikes during periods of market turbulence. For example, the most significant increases occurred during the financial crisis of 2008 and the COVID-19 pandemic in 2020, as both periods were marked by dramatic rises in uncertainty and liquidity interventions by the Federal Reserve.

Additionally, we observe that the value of information is higher for large-cap, growth, and momentum stocks compared to smaller or value-oriented stocks. Despite their generally lower volatility, larger stocks’ superior liquidity makes information more valuable for strategic traders.

This paper is the first to empirically estimate the value of information for strategic investors who internalize their price impact. By developing and estimating this simple and intuitive measure, our research opens new avenues for understanding the value of asset-specific information. Our results also contribute to ongoing debates about market efficiency, the role of private information in capital allocation, and the dynamics of trading during financial crises.

We believe that these insights will be valuable for both academic researchers and practitioners. From an academic perspective, this work highlights the importance of liquidity and volatility in determining the value of information. Practitioners can use this measure to better understand the profitability of information acquisition, making it relevant for asset managers, data vendors, and regulatory bodies focused on market transparency and insider trading enforcement.

Figure: Liquidity and the Strategic Value of Information.

Notes: The solid line is the monthly information value averaged over stocks and days surrounded by its 95 percent confidence interval, based on time-clustered variance estimates. The value of information is annualized variance divided by price impact and reported in millions of dollars. The mean and standard deviation of the value of information are estimated with the delta method to alleviate measurement error of this ratio. The log information value equals log annualized return variance less log price impact, so we also report the mean of log annualized return variance (dashed line) and the mean of log price impact (dotted line). Shades indicate recessions.

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Securities financing and asset markets: new evidence

Authors: Tomas Breach and Thomas B King

Short-term borrowing arrangements collateralized by financial assets—collectively referred to as “securities financing” transactions—are key mechanisms through which investors obtain leverage and engage in arbitrage. An important but opaque segment of this market involves dealers funding the securities positions of their clients, most often through bilateral repurchase agreements (repo), though such activity may also include margin lending and other similar transactions. Despite the theoretical interest in this market and its evident practical relevance, empirical facts are remarkably hard to come by. For example, while there is broad consensus that financing constraints had important effects on the liquidity and pricing of certain securities during the GFC, there is no systematic evidence on their impact during normal times or in the more-recent market deterioration around the advent of COVID-19.

We provide new evidence on bilateral dealer-to-client securities financing and its relationship to the respective cash markets for securities by exploiting the Senior Credit Officer Opinion Survey, or “SCOOS.” Every quarter, the SCOOS surveys the credit officers responsible for setting securities-financing terms at the roughly twenty broker-dealers with the largest presence in bilateral securities financing. The survey asks about the various terms on financing transactions and related information. Our data cover seven asset classes over the period 2010-2020.

The survey shows that dealers tend to change all types of terms (financing spreads, haircuts, credit limits, and maturity limits) together, suggesting that one or more common factors drive bilateral financing conditions. We present evidence on what those factors are by matching the SCOOS—by quarter and, where possible, by asset class—with a variety of data on market conditions, including financing and trading volumes, asset returns, securities issuance, and various measures of risk and volatility. The factor that emerges as most important is the liquidity of the underlying securities markets. Indeed, the inclusion of liquidity largely renders other measures of market conditions, such as volatilities and credit-risk spreads, insignificant in regressions. However, we do also find evidence that dealer balance-sheet constraints play a role in funding markets. In particular, controlling for other market conditions, we show that dealers tighten financing spreads and haircuts for less-liquid asset classes (consumer ABS, CMBS, and private-label RMBS) when their own equity positions worsen, suggesting a desire to preserve capital.

As an additional empirical exercise, we ask whether changes in funding terms themselves have explanatory power for market conditions, using as instruments self-reported changes in terms that are due to “market conventions.” We find that funding terms typically have little effect on asset-market liquidity and returns, although we do find some significant effects during the stress of early 2020.

Taken together, our results provide a number of facts about bilateral securities financing that may help to refine theoretical work in this area. Although our primary contribution is empirical, we also sketch a simple theoretical model that can rationalize our main results.

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Trust and delegated investing: a Money Doctors experiment

Authors: Maximilian Germann, Lukas Mertes, Martin Weber, and Benjamin Loos

The more trust investors place in a money manager, the more confident they are to take risk. We test this theory in a laboratory experiment using the amount returned from a trust game as measure of trustworthiness. Investors increase the share invested in risky assets with high-cost money managers compared to those with low costs when the high-cost money managers are more trustworthy than the low-cost ones. The willingness to take more risk with high-cost money managers is increasing in the difference in trustworthiness. Up to a third of the difference in trustworthiness translates into an increasing risky share. Vice versa, investors are willing to accept higher costs for investments made through more trustworthy money managers. Our findings are robust to alternative explanations, demonstrating that the risk-aversion channel can be sufficient for trust to influence behavior.

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Tradable Risk Factors for Institutional and Retail Investors

Authors: Andreas Johansson, Riccardo Sabbatucci, and Andrea Tamoni

We construct tradable risk factors for institutional and retail investors by combining large, liquid mutual funds for the long leg and ETFs for both long and short legs. Our study reveals that neither retail nor institutional investors can effectively track the standard “on-paper” size, value, momentum, profitability, and investment factors.

When we compare the performance of our tradable factors to the “on-paper” factors, we find an annual performance gap of 2% to 4%. We term this discrepancy the implementation shortfall (IS), drawing from the terminology of Perold (1988) and Pedersen (2015). The IS encompasses both trading costs (TC) and the opportunity costs (OC) associated with trading adjustments aimed at minimizing transaction costs in practical scenarios. We quantify the portion of the IS attributed to TC, and infer the opportunity cost of not trading the exact “on-paper” portfolio as the difference between IS and TC.

Our construction of tradable factors takes into account not only trading, but also shorting costs, which play a crucial role in explaining the implementation shortfall. Interestingly, tradable factors tend to have lower shorting fees than their “on-paper” counterparts. Thus, shorting costs play a crucial role in explaining the implementation shortfall. When accounting for shorting fees in the “on-paper” factors, the gap between tradable and “on-paper” factors narrows. This is illustrated in Figure 1 where the squared symbols (“on-paper” factors net of shorting fees) are closer to zero compared to the filled circles representing standard Fama-French factors. In essence, accounting for shorting fees in the Fama-French factors reduces the implementation shortfall.

We further investigate the contribution of trading costs to the IS between our tradable factors and the “on-paper” factors. Although our tradable factors already reflect the trading costs of individual securities held by the funds—costs implicitly accounted for in realized fund returns—the “on-paper” factors do not. However, “on-paper” factor portfolios, which comprise hundreds of stocks and experience high turnover, incur significant trading costs. Our findings indicate that the IS is reduced more significantly when accounting for shorting costs rather than trading costs. For instance, focusing on institutional investors, we observe that the alphas for HML and MOM decrease by 36% and 22% (in absolute value), respectively, when accounting for shorting costs, compared to reductions of 25% and 17% when accounting for trading costs.Overall, shorting fees and transaction costs contribute to 58% of the performance differential between tradable and “on-paper” factors. As shown in Figure 1, the remaining alphas – interpreted as an opportunity cost of not trading the exact “on-paper” portfolio, highlight additional frictions, such as the illiquidity of many stocks in the short leg of the “on-paper” factors, that are accounted for when using funds.

Overall, our analysis underscores a substantial performance gap between tradable risk factors, constructed using large and liquid mutual funds and ETFs, and the widely used “on-paper” factors.

Figure: Performance gap between tradable and Fama-French “on-paper” factors considering the impact of trading and shorting costs.

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Margin constraints and asset prices

Authors: Jungkyu Ahn

I study the effects of regulatory policy changes on interest rate option prices: margin tightening from the introduction of mandatory interest rate swap clearing by the Dodd–Frank Act in 2010 and margin loosening from the counterbalance of voluntary swaption clearing and synthetic derivatives to the uncleared margin rule in 2016. Employing these variations as exogenous shocks for a quasi-experimental design, I show that swaption prices consistently respond to changes in margin requirements. The results are consistent with theories on the expected margin premium, where the constrained agent holds short positions in zero net supply.

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Credit ratings: strategic issuer disclosure and optimal screening

Authors: Jonathan B Cohn, Uday Rajan, and Günter Strobl

We consider a model in which a security issuer can manipulate information observed by a credit rating agency (CRA). We show that stricter screening by the CRA can sometimes lead to increased manipulation by the issuer. Accounting for the issuer’s behavior pulls optimal CRA screening toward the extremes of laxness or stringency. Surprisingly, an improvement in prior asset quality can result in more rating errors. In a two-period version of the model, stricter screening can result in more short-run rating errors. Our results suggest complex interplay between issuer and CRA behavior, complicating the evaluation of CRA policy effectiveness.

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Large orders in small markets: execution with endogenous liquidity supply

Authors: Agostino Capponi, Albert J. Menkveld, and Hongzhong Zhang

Institutional investors have become so large in many markets that their orders experience substantial price impact. In response, they started to algorithmically shred the order into smaller pieces that are sent to the market over a particular time interval. Transaction cost, therefore, has become a function of two parameters: the size of the order and its duration. Transaction cost for large investors becomes a three-dimensional object: a liquidity surface.

When optimizing, an institutional investor is mindful of the strategic response of market makers. These market makers solve a dynamic inventory model, whereby they effectively intermediate between the institutional investor and randomly arriving small investors. The price is endogenous; it is the outcome of a market-clearing condition. This equilibrium price is ultimately driving transaction cost of the institutional investor.

We model this environment in such a way that the equilibrium is tractable and yields analytic expressions. We calibrate it to real-world data to yield a liquidity surface for actively traded equities. One of the outcomes is an equilibrium liquidity surface that is included in this post. We further use the model to answer how the presence of a large investor affects welfare of other market participants. Do market makers benefit? And, more importantly from a regulatory perspective, do small investors benefit?

Our analysis contributes to a large theoretical literature on market liquidity, in which information is symmetric across participants. One set of models studies best execution in the presence of exogenous liquidity supply. Another set does the opposite. It assumes that liquidity demand is exogenous and endogenizes liquidity supply. We endogenize both sides in the sense that optimal execution is studied in a market where liquidity supply is endogenous.

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Empirical determinants of momentum: a perspective using international data

Authors: Amit Goyal, Narasimhan Jegadeesh, and Avanidhar Subrahmanyam

Ever since the publication of Jegadeesh and Titman (1993), the profession has been puzzling over the causes of stock return momentum (the tendency for the relative performance of stocks over the past 3-12 months to repeat itself). Because this evidence is not explained by well-known asset pricing models, the literature proposes and empirically tests several other explanations. Although the empirical work testing the explanations mostly uses U.S. data, momentum strategies are profitable in many international markets as well. Because the pattern of momentum is similar in both the U.S. and internationally, a natural question that arises is which, if any, of the explanations apply internationally. This is the issue addressed in the paper.

One strand of momentum explanations proposes behavioral theories. One of them proposes that momentum is due to investor overconfidence. The idea here is that overconfidence builds as investors receive public signals that confirm their initial beliefs but does not subside equally when they receive contradictory ones, which causes investors to continue to overreact to an initial belief. Another prominent explanation, labeled “frog-in-the-pan” hypothesis, posits that because of their limited attention span, investors underreact to information that arrives in small bits but correctly react when information arrives in large chunks. Another explanation in the same category is that stocks less followed by analysts have slower news diffusion, and this leads to overall momentum. A further explanation posits that investors anchor their valuation to 52-week high prices and hence stocks that are close to this high tend to be perceived as expensive and therefore underreact to good news (and vice versa). A risk-based explanation posits that momentum is due to time-varying value of real options. Under this explanation, winning stocks have more growth options, implying higher risk, and therefore higher required returns.

We test the above explanations with international data using regression based and portfolio approaches. We test them with the full international sample and within subsamples stratified into developed and emerging markets. Across all samples, we find consistently strong support for the frog-in-the-pan explanation. This explanation is proxied by a quantity that represents the degree to which the signs of daily returns match the sign of the past momentum return. To a lesser extent, we find support for overconfidence, captured by the market-to-book ratio. We also obtain confirmation of another U.S.-based result across all samples: that momentum profits are higher in up-market and low-volatility states; these are states hypothesized in the literature as those in which investor confidence is greater.

Overall, our paper provides strong international support for the notion that momentum arises from slow news diffusion, and to a more modest extent, investor overconfidence.

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It’s not (only) personal, it’s business: personal bankruptcy exemptions and business credit

Authors: Rebel A Cole, Jason Damm, John Hackney, and Masim Suleymanov

In the U.S., state-level exemption laws determine the amount of property that individuals can protect from creditor liquidation during the debt settlement process of bankruptcy proceedings. We exploit discontinuities in personal bankruptcy exemptions created by state borders to identify the spillover effects of these laws on business credit extended to small firms. While exemption limits pertain to personal bankruptcy filings, entrepreneurs often provide personal guarantees and/or personal collateral in order to obtain business credit. We demonstrate that greater asset protection for individuals negatively impacts the amount of credit available to small businesses, as creditors can expect individuals to file for bankruptcy more often and to recover less ex post. Small business owners are often liable for company debts because of business structure or personal guarantees. Despite the intuitive linkages between business and personal balance sheets, evidence suggests that policymakers are unaware of the consequences of these laws for small businesses.

We collect time-varying data on home equity (homestead) bankruptcy exemption limits across all U.S. states from 2006 – 2018 to estimate the effect of changes in the level of debtor protection on small business credit extended by banks. We document 70 exemption increases over the sample period. Subsequent to these law changes, we find a reduction of 1–2% in originations of business credit, for a rough estimate of –$4.2 to –$7.1 billion over the sample period. The effect is strongest for the smallest firms, which are more financially constrained.

We then provide household-level evidence that both business debt and personal debt decline for borrowers whose home equity becomes covered by the exemption change, indicating that overall credit availability declines for small business owners. We also rule out other potential credit substitutes such as those from FinTech lenders or the Small Business Administration.

Finally, we examine the real economic consequences of this reduction in business credit. We find that exemption changes contribute to a decline in the number of local establishments and employment, but only for the smallest firms. Meanwhile, there is no corresponding impact on medium-size or large-size firms. These results reveal that changes in the level of personal bankruptcy protection have particularly harmful consequences for the smallest firms, which are generally the most financially constrained. We also demonstrate that this impact is particularly prevalent in industries that are most dependent on external finance, suggesting that negative real economic effects occur via a credit market channel.

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