Dear EFA Member,
As a current or recent EFA member, we are pleased to forward you the contents of the recently published Issue 1 of Volume 27 of the Review of Finance – the EFA’s own journal – along with digests (short summaries) and abstracts.
- Information in Financial Markets and Its Real Effects
by Itay Goldstein
- Search-Based Peer Groups and Commonality in Liquidity
by Paul Brockman, Dennis Y Chung, Neal M Snow
- Dissemination, Publication, and Impact of Finance Research: When Novelty Meets Conventionality
by Rui Dai, Lawrence Donohue, Qingyi (Freda) Drechsler, Wei Jiang
- How Does Human Capital Affect Investing? Evidence from University Endowments
by Matteo Binfarè, Gregory Brown, Robert Harris, Christian Lundblad
- How Do Options Add Value? Evidence from the Convertible Bond Market
by Inmoo Lee, Rex Wang Renjie, Patrick Verwijmeren
- Market Timing and Predictability in FX Markets
by Thomas A Maurer, Thuy-Duong Tô, Ngoc-Khanh Tran
- Small Business Lending in Financial Crises: The Role of Government-Guaranteed Loans
by John Hackney
- Moneyness, Underlying Asset Volatility, and the Cross-Section of Option Returns
by Kevin Aretz, Ming-Tsung Lin, Ser-Huang Poon
- Bear Beta or Speculative Beta?—Reconciling the Evidence on Downside Risk Premium
by Tong Wang
Authors: Itay Goldstein
Financial markets have a central role in allocating resources in modern economies. One of the main functions of financial markets is the discovery of information. This information in turn helps guide decisions in the real side of the economy. The literature on the “feedback effect” of financial markets explores this channel. Empirical work tries to identify the informational feedback from markets to corporate decisions. Theoretical work explores implications that this feedback effect has for the equilibrium in financial markets and for economic efficiency. Current trends in information technology under the FinTech revolution change the nature of information processing in financial markets and so may change the nature of the feedback effect. In this article, I review the main themes of this developing literature and connect them to the current information revolution. I also discuss directions for future research.
Authors: Paul Brockman, Dennis Y Chung, Neal M Snow
In this study, we examine the relationship between EDGAR-initiated, search-based peer (SBP) groups proposed by (Lee, Ma, and Wang, 2015) as a potential determinant of commonality in liquidity. Understanding the determinants of commonality is important since the liquidity risk associated with comovement can have a significant impact on a firm’s expected return. Our central hypothesis is that correlated searches (i.e., chronologically adjacent searches) within SBP groups will lead to correlated trading within these same groups and, consequently, to increased demand-side commonality in liquidity.
Our empirical analyses confirm that SBP membership is a statistically and economically significant source of commonality for both bid-ask spreads and volume depths. We also show that SBP-induced commonality has been increasing in significance over the past two decades. When we compare supply-side commonality from specialist-portfolio membership to demand-side commonality from SBP-group membership, we find that demand-side SBP membership has a stronger impact on both spread and depth commonality. This is a significant result, especially in light of Tham, Sojli, and Skjeltorp’s (2018, p. 2919) observation that, “Resiliency and the endogenous relation between liquidity demanders and suppliers are understudied but important in today’s electronic markets.” Finally, we track the IP addresses of EDGAR searches to distinguish between retail and institutional investor-initiated searches. The results show that retail investors play a major role in both SBP formation, and in SBP-induced commonality.
Overall, our study contributes to the market microstructure and disclosure literature in two main areas. First, we provide new evidence on the determinants of liquidity comovement by showing that membership in an SBP group increases a firm’s spread and depth commonality. In addition to identifying a new source of commonality, our findings also provide new evidence on the relative importance of demand-side versus supply-side commonality. By tracking the locations of the IP addresses that generate SBP groups, we show that retail investors are responsible for roughly 85% (54%) of the EDGAR searches that generate SBP groups (top-five SBP groups). Second, our study contributes to an emerging literature that uses internet searches to examine potential implications for investor behavior and stock market trading patterns. Our findings show that the identification of a significant source of comovement in liquidity is only possible through the application of a co-search algorithm to the SEC’s EDGAR database. Without access to investor-search data and SBP-forming algorithms, these liquidity patterns within SBP groups would have remained hidden from view. We expect that future research projects will identify other latent patterns through the application of SBPs to novel research questions.
Authors: Rui Dai, Lawrence Donohue, Qingyi (Freda) Drechsler, Wei Jiang
Using numeric and textual data extracted from over 50,000 finance articles in SSRN’s Financial and Economics Network (FEN) during 2001–2019, our study is the first large-scale empirical research that uncovers the determinants of research outcomes, such as publication outlet, impact and readership in academic finance. We aim to reconcile—confirming, contrasting, and uncovering nuances—the empirical data with the anecdotal evidence and common wisdom regarding how research is evaluated and recognized by the community and its premier outlets, i.e., acceptance at top journals, such as Journal of Finance, and conferences, such as American Finance Association (AFA) annual meeting.
Leveraging on current-state of art machine learning techniques (Universal Sentence Encoder) and applying on a large body of both published work and working papers, we show that conventionality, measured as semantic similarity with existent research, helps boost readership and publication prospects. This is probably because both readers and journals welcome papers that have a large footprint on the existing knowledge, possibly because audience and reviewers are better able to connect and resonate with such research.
On the other hand, novelty, measured in the forms of emerging topics and novel databases, is associated with better publishing outcomes, after controlling for various authors and institutions characteristics. We also show that studies that do not easily map into established finance subfields or that introduce non-finance elements face a higher hurdle in the publication process, partially due to the fact that referees and editors are risk averse and under time/resource constraint, and are thus reluctant to endorse research whose quality is difficult to assess. Thus, there seems to be a contrast in our profession’s attitude toward papers whose research questions span multiple fields versus papers that build on prior knowledge from multiple fields. Readers and journals in finance value authors’ effort and ability in bridging knowledge from different research elements but are nevertheless skeptical of research that tackles questions without a well-defined habitat.
Finally, we confirm that admissions into top conferences such as AFA and WFA are significant precursors to publication and impact. Being on the program of either conference predicts a 48.1% increase in the probability of publishing in the top three finance journals relative to propensity-matched control papers, and an 87.3% increase in citation.
The main findings of our study probably confirm the common understanding that while exploratory projects have the potential for high recognition, researchers need to first overcome the hurdles of the publication process, especially the completeness and robustness requirements expected at top outlets and the uncertainty in receiving proper valuations from referees from the more conventional domains. We hope the analysis presented in this research can provide comprehensive and objective evidence that could help the profession, especially its leaders, to reflect on the prevailing patterns and to think of creative ways to encourage and promote innovations in research.
Authors: Matteo Binfarè, Gregory Brown, Robert Harris, Christian Lundblad
We examine the links between human capital and endowment investing. University endowments spend billions of dollars a year to support higher education in the United States. Rather than rely on investments in public securities such as stocks and bonds to fund this spending, many (and especially large) endowments have substantial allocations to “alternative” assets, such as hedge funds, private equity, or venture capital. Given the mission and profile of nonprofit endowments, these endowments can bear the illiquidity of alternative investments, with the opportunity to earn higher risk-adjusted returns. As most endowments often have an infinite investment horizon, few investment constraints, in-house expertise, and links to successful alumni, they can invest with top performing managers in private assets that would otherwise be difficult to access. These arguments are at the core of the “endowment model”, popularized by David Swensen at Yale, which advocates that endowments hold a low allocation to public markets and high allocations to alternative investments.
This paper studies the role of human capital in the investment management of university endowments by examining links to asset allocations and resulting returns. To measure human capital, we look at the professional backgrounds of endowment investment committee members, whether there is a chief investment officer (CIO), and the size of the in-house professional investment team. These provide broad measures of the skills, knowledge, and experience that the endowment uses in the investment process. We pay particular attention to alternative assets (hedge funds, private equity and venture capital) which play a large role in the “endowment model” and may require specialized expertise for investing.
We document the substantial shift to alternative assets which is especially pronounced for larger endowments. These endowments employ higher levels of specialized human capital in their investment process. We find that higher asset allocations to alternative assets accompany higher levels of human capital in the endowment’s investment process. Moreover, high levels of human capital are linked to larger returns, even on a risk-adjusted basis. The improved investment outcomes arise because endowments i) capture higher returns that can accompany alternative assets, ii) select or have access to high performing managers, and iii) minimize fees by accessing funds directly rather than through funds of funds. For instance, we find that human capital affects how endowments navigate choices between accessing funds directly rather than through funds of funds. Endowments with more human capital resident in their investment committees and professional staffs are more likely to use direct funds to invest in alternative assets.
Lastly, to provide additional insights on how allocations and performance are linked to human capital and networks, we conduct a survey of endowments to dig further into the investment process. We confirm that specialized human capital is central in facilitating alternative investments.
Authors: Inmoo Lee, Rex Wang Renjie, Patrick Verwijmeren
In this paper, we study whether options add value to issuers of underlying stocks in the context of convertible bond issues. Convertible bonds provide an interesting empirical setting to study the role of options because pricing convertibles requires essentially the same set of information necessary to price options. If the options market provides additional information that is useful in pricing convertibles (e.g., implied volatilities) and convertible bond issuers and investors actively utilize it, the availability of listed options will reduce adverse selection problems and affect convertible bond valuation.
We collect a sample of 1,357 convertible bond offerings issued by 815 unique U.S. public firms. Consistent with prior studies, convertible bonds in our sample are offered at significant discounts. We find that the offering discount from issues with listed options is about 26% smaller relative to issues without options. Of course, option exchanges do not randomly select underlying stocks for individual stock option listing. The smaller discount for issues with listed options could be due to unobserved factors that simultaneously influence the availability of options and the pricing of convertible bonds. To address this concern, our main conclusions are based on analyses that exploit the Securities and Exchange Commission’s minimum stock price requirement for option listing. This ad hoc price cutoff creates a discontinuity in the likelihood of option listing.
Using the distance between an issuer’s average stock price and the cutoff price as the forcing variable, we employ a fuzzy regression discontinuity design. We find that the likelihood of option listing increases from below 30% to above 50% as soon as the forcing variable passes the threshold. We then use this listing eligibility as an instrumental variable for the availability of options and estimate two-stage least squares (2SLS) regressions controlling for the forcing variable and other firm characteristics. The 2SLS results indicate that the availability of listed options significantly reduces convertible bond underpricing after addressing concerns regarding the endogeneity of option listing decisions.
We further investigate through which channels options affect the convertible market and find evidence of both information- and hedging-related channels. The relation between the availability of options and offering discounts is stronger when the information environment of issuers is poor. Transaction prices of convertible bonds with listed options also converge more quickly to their theoretical prices in the years after issuance, which is in line with a continuing provision of implied volatility estimates through option prices. Moreover, the availability of options significantly increases the number of convertible bond buyers. The increase in demand comes from both hedge funds who can use options to implement convertible arbitrage strategies and long-only institutional investors who benefit from the information provided by options.
Overall, our findings accord with the notion that individual stock options enable issuers of underlying stocks to attract more capital suppliers when they issue convertible bonds through both an improved information environment and a facilitation of arbitrage strategies.
Authors: Thomas A Maurer, Thuy-Duong Tô, Ngoc-Khanh Tran
Mean-variance optimized portfolios earn high out-of-sample (OOS) returns in foreign exchange (FX) markets [Baz et al., 2001, Della Corte et al., 2009, Ackermann et al., 2016, Daniel et al., 2017]. We investigate the time-series performance of these portfolios, and show that the conditional Sharpe ratio and crash risks are time-varying and predictable. We can exploit this information, and trade more (less) aggressively when prices of risks are higher (lower). This market timing is valuable and significantly improves the performance compared to strategies that use inferior market timing policies.
All conditionally mean-variance efficient strategies have proportional portfolio weights, and achieve the same conditional Sharpe ratio. However, these strategies generally differ with respect to the asset allocation, i.e., the time-variation in the notional value or leverage. Since the conditional Sharpe ratio varies over time, differences in the time-variation in the notional value implies that these portfolios earn different unconditional Sharpe ratios. We denote this time-variation as market timing.
Our main focus is the strategy MV that maximizes μ-θσ2, where μ and σ2 are the conditional expected excess return and variance of the currency portfolio, and θ is a time-invariant parameter. MV delivers the optimal conditional Sharpe ratio. Moreover, it invests more (less) when market prices of risk in FX markets are high (low). Therefore, MV’s market timing exploits the time-variation in the conditional Sharpe ratio, leading to an attractive unconditional return distribution.
In comparison, MVCN maximizes the conditional Sharpe ratio and rescales the portfolio such that the notional value is constant and equal to one. Thus, there is no market timing by design. Due to the lack of market timing, we expect MVCN to underperform MV. Next, MVCV maximize the conditional expected return subject to a constant target volatility. Thus, the notional value only varies with the conditional return volatility, but not the conditional expected return. We expect that the MV is superior to MVCN due to volatility timing, but inferior to MV as MV also uses information about expected returns for the market timing. Finally, MVCY minimizes the conditional portfolio variance subject to a constant target yield. This implies a low (high) notional value when the conditional expected return is high (low). Accordingly, the strategy invests less (more) aggressive when conditional prices of risk are high (low), which is opposite to MV, and we expect a relatively poor unconditional performance.
We use FX returns from 1983 to 2016 to compare the out-of-sample performance of the four strategies. Confirming our intuition, we find that MV has a significantly higher unconditional Sharpe ratio, higher skewness, and lower maximum draw down than MVCV, MVCY, and MVCN. The superior performance of MV has important implications for asset allocations. Our results suggest that leverage or risk limits are costly when market conditions are time-varying and market timing is highly profitable. In practice, such limits are often imposed on portfolio managers (in addition to less tight regulatory constraints). Thus, it is important to understand the implicit costs associated with such leverage or risk limits.
Authors: John Hackney
The role of the government in ensuring access to credit for small businesses has been the focus of considerable research and policy debate. The disproportionately negative effect of the COVID-19 pandemic on small businesses has once again brought this subject to the fore. Much of the discussion arises from the belief that small firms are the engine of economic growth, yet face significant difficulty in accessing the credit markets on which they depend. Small business credit access is a particularly relevant topic during crises, when research shows bank-dependent firms face even greater difficulty obtaining capital.
I ask in this paper whether and how a particular type of indirect government intervention, partial credit guarantees, can ease financial constraints for small businesses during crises, and whether this can in turn translate to better real outcomes. I use geographic variation in the presence of lenders who participate in the Small Business Administration’s 7(a) loan program to answer this question, along with a novel IV analysis exploiting the distance between these lenders and the SBA’s loan processing center.
The results indicate that during the 2007-2009 financial crisis, areas with a greater share of Small Business Administration 7(a) lenders experienced: 1) a 2.2% increase in small business loan volume, 2) a 3.7% increase in small firm employment and 3.5% increase in establishments, and 3) lower loan default rates. Bank-county-year analysis suggests that SBA banks increase their share of lending when they are capital-constrained, and when local median income is lower. The findings suggest that targeted government support can play a beneficial role in the presence of private credit market frictions, especially when bank capital is limited and small business financial constraints are severe.
Authors: Kevin Aretz, Ming-Tsung Lin, Ser-Huang Poon
While a large literature in finance suggests that the expected returns of European call (put) options fall (rise) with underlying asset volatility, the studies in that literature implicitly assume that variations in underlying asset volatility are exclusively driven by idiosyncratic volatility. To address that shortcoming, we present a more comprehensive analysis of how variations in underlying asset volatility driven by both systematic and idiosyncratic volatility price the cross-section of such European options. Our main theoretical insight is that variations driven by systematic volatility can be priced with a different sign compared to variations driven by idiosyncratic volatility depending on option moneyness (i.e., the probability with which an option will be exercised). Standard empirical asset pricing tests broadly support our main theoretical conclusions.
On the theoretical front, we consider a two-period continuous-variable stochastic discount factor model in which the second-period log underlying asset payoff and log stochastic discount factor realization are bivariate normal with a negative correlation. We show that, in that model, an underlying asset volatility increase induced through idiosyncratic volatility only affects the expected return of a European option through the option’s elasticity, while an increase induced through systematic volatility also oppositely affects it through the expected underlying asset return, with the relative strengths of the two opposing effects determined by moneyness. Hence, a systematic-volatility-induced increase raises the expected returns of in-the-money (ITM), at-the-money (ATM), and mildly out-of-the-money (OTM) calls but lowers those of deeper out-of-the-money (DOTM) calls. In contrast, an idiosyncratic-volatility-induced increase always lowers the expected returns of calls, with the effect however converging to zero with moneyness increases. The model yields comparable conclusions for puts.
On the empirical front, we show that double-sorted portfolio exercises and Fama-MacBeth (1973) regressions run on “quasi-European” single-stock calls (i.e., American calls written on single stocks not paying out dividends over the time-to-maturity) broadly confirm our model’s main predictions. Sorting our calls into portfolios double-sorted on moneyness and either a systematic or idiosyncratic volatility estimate while controlling for the other volatility estimate, the left panel of the graph below, for example, reveals that the mean returns of our ITM calls significantly rise with the systematic volatility estimate, while those of our OTM and DOTM calls significantly fall with that estimate. Next, the right panel establishes that the mean returns of our calls in all moneyness groups fall with the idiosyncratic volatility estimate, with the effect however becoming weaker with moneyness.
Our conclusions are robust with respect to the factor model used to estimate the volatility components; leaving a zero or one month gap between the volatility estimation and call return window; using standard or weighted least-squares (WLS) Fama-MacBeth regressions; controlling for a comprehensive set of factors known to price options; and adjusting or not adjusting call returns for bid-ask transaction costs.
Authors: Tong Wang
Our research shows that the most fundamental principle in investments fails when it comes to managing bear market risk exposure of your stock portfolio. Investors have long been taught that the reward they earn in the form of expected return is proportional to the amount of risk they are willing to take. If you take on more risk, you can expect to earn a higher return, right?
We find that stocks that bear the most bear market risk, i.e., those that perform particularly poorly during market downturns, also tend to earn the lowest expected returns. By avoiding them, investors can reduce their portfolio risk and improve then portfolio return at the same time!
The main peril of constructing portfolios to hedge bear market risk suggested by previous research lies in the reliance on the historical performance of stocks during bear markets. It was assumed that stocks that performed well during the past bear markets must be good hedges against future bear markets. Our research indicates that the reality is the opposite: Stocks that looked like good hedges in the past tend to perform very poorly during future downturns. Holding such stocks would increase your exposure to the bear market risk and negatively impact your average portfolio return. So, investors should avoid such stocks at all cost.
NOTE: This and previous issues of Review of Finance [ISSN 1572-3097 | EISSN 1573-692X] are freely available to current EFA members as a benefit of annual membership. For information on how to submit a manuscript to Review of Finance, please visit the RF Editorial Office website revfin.org. Follow us on LinkedIn.