AFA PhD Student Poster Session
Poster Session
Saturday, Jan. 7, 2023 7:55 AM - 8:30 PM (CST)
A Network Model of Capital Structure
Abstract
This paper investigates the relationship between firms’ network production structure and key decisions, such as asset size and leverage. We model the production process as a function of input-output linkages between different industries, including random productivity shocks that impact firms’ decisions. We derive the equilibria for the theoretical model and then use Generalized Method of Moments (GMM) to calibrate the parameters to match relevant observed moments of our data. The results confirm that our theoretical model fits most empirical data properly. Particularly, key empirical moments associated with leverage, debt expense-to-gross profit ratio and asset turnover can be closely replicated using our approach. The model also matches observed default rates by industry and can be used to assess network sensitivity and the impact of contagion in production networks.A Nonparametric Tail Risk Analysis of Global Equities
Abstract
Tail risk or ’Black Swan’ events are rare in occurrence and yet play a significant role in asset price movements. Despite continued efforts, researchers and investors alike struggle to match such occurrences with existing models or strategies. To address this issue, we develop an empirical procedure that merges theory with evidence. We modify the traditional Kalman filter by constructing a recursive procedure to predict ’Black Swan’ events. Our model accurately out of sample forecasts such events and yields a substantially higher marginal likelihood compared to the baseline Time-varying regression model. Incorporating tail risk yields a 1.4% higher annual return and 1.12 times higher Sharpe ratio for equity-only portfolios, a significant improvement in investor performance compared to the standard portfolio problem. Our findings suggest generating predictive densities via Kalman-Mixtures prove successful in predicting risk premia, and constructing portfolios for investors and researchers alike. We believe our procedure offers a more accurate and alternative approach in dealing with rare disaster events in the global equity market.A Smooth Shadow-Rate Dynamic Nelson-Siegel Model for Yields at the Zero Lower Bound
Abstract
We propose a smooth shadow-rate version of the dynamic Nelson-Siegel (DNS) model to analyze the term structure of interest rates during the recent zero lower bound (ZLB) period. By relaxing the no-arbitrage restriction, our shadow-rate model becomes highly tractable with a closed-form yield curve expression. The model easily permits the implementation of readily available DNS extensions such as time-varying loadings, integration of macroeconomic variables and time-varying volatility. Using U.S. Treasury data, we provide clear evidence of a smooth transition of the yields entering and leaving the ZLB state. Moreover, we show that the smooth shadow-rate DNS model dominates the baseline DNS model in terms of fitting and forecasting the yield curve, while being competitive with a shadow-rate affine term structure model.Capital Allocation Decisions in Private Equity
Abstract
I study the determinants of across industry fund level portfolio allocation decisions by private equity (PE) firms. I construct a dynamic agency model with an exploration versus exploitation trade off of a PE firm raising capital for subsequent funds. The PE firm can allocate capital to a known market (exploitation) or explore a new market (exploration).The model features moral hazard between the general and limited partners and learning from past investments by the PE firm. I endogenize the portfolio allocation of the PE firm and the capital allocation of the limited partners. Firms with high opportunity cost of exploration do not explore; firms that choose to explore, base their allocation decision on the cost of managing the funds, opportunity cost of exploration, and their skill to learn from past investments. Exploration and subsequent period investments increase in the severity of moral hazard. Using data from Preqin, I find empirical evidence consistent with the model.
Asset Pricing and Re-sale in Networks
Abstract
I study asset pricing when re-trade can take place in co-existing and interconnectedmarkets. In my framework, there is a divisible asset and a finite set of traders. They
are distributed over a trading network. Traders can acquire shares at a common price,
and then they may trade with their connections at possibly different prices. I find that
trading centrality, a novel network metric, is a sufficient statistic for the equilibrium.
Trading centrality processes information about expected re-trade equilibria, and maps
it to traders’ behavior before trade. A trader’s asset acquisition is proportional to his
centrality, and the asset common price is defined by aggregating centrality globally.
For the re-trades in the network, a trader demands the gap between his optimal level
of asset and his centrality; while each price is defined by aggregating centrality locally
in the seller’s network. I investigate what market outcomes and welfare arise at
different trading networks. Implications for asset issuance and interdealer markets are
examined.
Asset Pricing with Complexity
Abstract
Machine learning methods for big data trade off bias for precision in prediction. To understand the implications for financial markets, I formulate a trading model with a prediction technology where investors optimally choose a biased estimator. The model identifies a novel cost of complexity that arises endogenously. This effect makes it optimal to ignore costless signals and introduces in- and out-of-sample return predictability that is not driven by priced risk or behavioral biases. Empirically, the model can explain patterns of vanishing predictability of the equity risk premium. The model calibration is consistent with a technological shift following the rise of private computers and the invention of the internet. When allowing for heterogeneity in information between agents, complexity drives a wedge between the private and social value of data and lowers price informativeness. Estimation errors generate short-term price reversals similar to liquidity demand.Banks as "Anchors": The Role of Banks in Funding Innovation
Abstract
Bank investments in the venture capital (VC) market play an important role, especially outside main entrepreneurial hubs. Banks act as anchors to the companies, serving as a positive signal of their quality and attracting further investors. Due to their abilities in monitoring and higher local expertise, banks are able to select profitable VC investments and exit them successfully. I exploit the implementation of the Volcker Rule as a shock where banks are no longer allowed to sponsor or invest in VC funds. I find that companies in regions dependent on bank VC financing suffer a drop in financing and innovation. A proxy for attention to start-ups serves as another confirmation mechanism of our story. I add to the debate on cross-selling services by financial intermediaries and on the certification role that banks play in markets other than lending.Banks, Fintech Disruptions and Labor Consequences
Abstract
I examine how traditional depository banks respond to increased competition from fintechfirms. My identification strategy exploits the staggered adoption of the regulatory
sandbox legislation in some US states. I first show that the adoption of regulatory
sandboxes leads to 8% increase in the number of fintech startups. This rise in fintech
firms leads banks to increase wages and employment. At the same time, banks close
more branches. Together, my results suggest that banks hire skilled workers and close
costly branches in a bid to be more responsive to the potential disruptions from fintech
firms.
Banks' Role as Liquidity Providers and Opacity in Financial Reporting
Abstract
This study examines the relationship between banks’ role as liquidity providers and opacity in financial reporting, measured with discretionary loan loss provisions. I investigate the 2007 financial crisis, when unexpected credit line drawdowns generated difficulties in liquidity provision for banks with large amounts of pre-crisis unused commitments. I find that such banks increased financial reporting opacity relatively more after the onset of the crisis. The results are consistent with the theoretical literature that highlights the benefit of bank opacity in providing liquidity during distress.Powerful CEOs in Uncertain Times: Survival of the Fittest
Abstract
In contrast to the widespread concern about excessive CEO power, this paper examines whether powerful CEOs are more beneficial and desirable under uncertainty. I document that powerful CEOs have a lower dismissal rate in uncertain times. With better performance but no increased compensation, they are likely retained optimally for their effectiveness under uncertainty rather than by entrenched power. Two mechanisms potentially explain why powerful CEOs are more effective under uncertainty: they are more willing to share information with the board, and more capable of taking swift action. My findings support optimal dismissal theory, highlighting that powerful CEOs' effectiveness increases with uncertainty.Clientele Credit: Theories and Evidence
Abstract
Clientele credit is the firm’s collection of payments from customers based on the firm’s unfulfilled obligations on the future delivery of services or goods. One-third compustat firms carry balance of unfulfilled obligations, and their pre-collected clientele credits account for, on average, 16.8% of non-cash asset. Many theories potentially explain the sizeable usage of this obligation-based credit, but few comprehensive empirical tests were conducted. This paper fills the gap. Using the novel, hand-collected data from the off-balance sheet information in 10-K, I test the financing advantage hypothesis and document the following supportive findings. First, creditworthy firms are offered those credits, and the offering is not conditional on information from the bank. Second, the demand for clientele credit centers on the firms without access to other credit, such as bank line of credit or trade credit. Third, firm with better access to finance and information advantage is more likely to be the credit provider. Using COVID-19 as a natural experiment that causes a sudden increase in demand for liquidity, I find that constrained firm increases clientele credit balance on an asset by 4.07% more than non-constrained firms, controlling for other demand for funding. Empirical results overall support the notion of credit redistribution view and suggest that clientele credit be a viable liquidity alternative.Climate-Induced Labor Risk and Firm Investments in Automation
Abstract
This paper studies whether and how firms adapt to climate-induced labor risks through automation investments. Using textual analysis, I construct a measure of automation investment intensity at the firm-year level based on material news and events. I find that firms whose workforce is more climate-exposed invest more in automation when they face adverse long-term climate conditions and are not financially constrained. The automation news of these firms is associated with positive stock market responses. In addition, I uncover that after automation adoption, climate-exposed firms carry a smaller employment buffer and have lower employee insurance costs; they also enjoy better operating performance under short-term climate shocks. Overall, these results imply that automation investments effectively help firms mitigate climate-induced labor risk and speak to the implications of climate adaptation strategies.Common Ownership in Product Markets: The Role of Supply Chains
Abstract
We investigate the relationship between common institutional ownership of firms in sectors along a supply chain and product market competition. Consistent with industrial organization models, common ownership is associated with lower markups in upstream and intermediate sectors and with higher markups in more downstream sectors. We establish causality by relying on a difference-in-differences approach based on the quasi-natural experiment of financial institution mergers. We conclude that common ownership deserves antitrust attention but eventual restrictions should be designed taking into account the overall portfolio composition of investors and jointly considering horizontal and vertical externalities that firms impose on each other.Competition and the Value of Innovation
Abstract
I investigate how competition affects firms' economic returns from innovation, defined as the present value of incremental expected future cash flow associated with the innovation. I measure innovation economic returns based on the changes in patenting firms' stock market value around patent issuance dates following Kogan et al. (2017). The observed negative correlation between competition and patent value may reflect unobserved, simultaneous determinants of industry competition, firm innovation, and patent value. I propose a novel quasi-natural experiment design to address this issue. I compare the value of patents that were issued immediately before and after competition-altering events. I show that an expected decrease in market competition leads to an increase in patent value and vice versa.Corporate Governance Networks and Financial Performance
Abstract
I investigate the impact of two different corporate governance network connectedness measureson financial performance of firms. I consider both ownership connectedness, defined as the number of connections to other firms through common shareholders, and boardroom connectedness, that is the number of connections to other firms through common directors. In panel regressions, I find that firms with higher shareholder overlap but lower directors overlap with other firms have higher ROA. These relations are statistically significant and economically meaningful: ceteris paribus, 200 additional common institutional shareholders have a +0.7% impact on ROA, while one additional common female director has a -0.6% impact on ROA. Using changes in the Russell 1000 and Russell 2000 indices constituents as a source of exogenous variation in ownership connectedness, I establish that the relation for ownership connectedness is causal: higher institutional shareholder connectedness imply higher ROA. Firms benefit from sharing institutional investors. In fact, given their size and scope, they act like a super entity between the firms they have in their portfolios, facilitating the exchange of best practices among connected firms. On the other hand, I provide evidence that female directors sitting on multiple boards inhibit firm performance.
The Stock Market Valuation of Corporate Social Responsibility Programs
Abstract
This paper examines how the market evaluates corporate social responsibility (CSR) programs. The level of public concern about a social issue, measured as the number of newspaper articles covering the social issue, positively affects the market reaction to the news on CSR programs addressing the issue. Also, stock prices increase when CSR programs are difficult for individuals to replicate. I further find a positive effect of past profitability on the market reaction, while the effect turns weaker if a CSR program addresses issues of more serious public concern. Companies tend to increase CSR efforts to address the social problems discussed more often, and larger companies are more likely to take CSR initiatives that are harder for individuals to replicate. Overall, this paper sheds light on how stock prices impound the value of CSR programs.Ants that Move the Log: Crashes, Distorted Beliefs, and Social Transmission
Abstract
Have retail investors become the ants that move the log? Social media has proved instrumental for effective coordination that might lead to extreme returns. To study this effect, I construct a novel crash risk measure by estimating ex-ante crash probabilities via logit and machine learning techniques. Stocks with high ex-ante crash risk tend to have lower returns, especially when lagged sentiment is high. Robinhood traders tend to over-buy high crash-risk stocks, consistent with the optimal expectations theory (Brunnermeier et al., 2007). By exploiting the staggered first appearances of ticker names on ``Wallstreetbets'', I document a causal effect of social transmission on crash risk. This effect is significantly more substantial for smaller stocks. To further bolster the finding, I exploit the entire history of Reddit to construct a novel instrument. I show that social transmission is likely to cause elevated crash risk on a daily basis.Credit Constraints and the Distributional Effects of the Refinancing Channel
Abstract
This paper investigates the distributional impact of credit constraints on the transmission of monetary policy in the U.S. through mortgage refinancing, by developing a model that identifies household-level application and approval probabilities separately. On average, households with a high loan amount, low income, as well as Black, Hispanic and Female households are most affected by credit constraints. The model is used to determine the impact of credit constraints after a monetary policy shock and a credit tightening event, finding that households with high loan amounts, low incomes, Black, Hispanic and Female households face the largest credit constraints.Crypto-CAPM: The Role of Speculative and Fundamental Demand in Cryptocurrency Pricing
Abstract
We offer a CAPM-like equilibrium pricing model for cryptocurrencies in an environment where investors have dispersed beliefs and can endogenously control the utility gain from transactional benefits. We identify three priced components: i) Systematic exposure to the crypto market portfolio, ii) Belief heterogeneity and iii) Transactional benefits. Theoretically: (1) we derive an "optimism coefficient", that captures the magnitude of belief heterogeneity in each crypto asset. (2) we find a bilateral relationship between belief dispersion and transactional benefits. (3) we demonstrate that in boom episodes, over-optimism de-stabilizes crypto market and might lead to crash. We provide several empirical supports for our theory.Distrust Spillover on Banks: The Impact of Financial Advisory Misconduct
Abstract
Using a novel data set of operational affiliation links between U.S. investment advisory companies and commercial banks, I find that distrust shocks from misconduct committed by investment advisors spillover to their affiliated banks by exploiting the geographic dispersion of branches of both advisers and banks. I examine within-branch variation relative to other branches who operates under the same bank and not in the same local community as the fraudulent affiliated advisor. Local communities where fraudulent advisor locates subsequently withdraw deposits from affiliated bank. Additionally, only banks sharing the common brand name with fraudulent advisors explain the negative relation, breaking the link between distress risk and deposit withdrawal. This evidence identifies an important source of operational risk in banking sector.Do Industries' Political Profiles Affect their Portfolio Return Performance?
Abstract
The political profiles of an industry influence its performance. I form eight comprehensive political profile portfolios after double sorting on industry-level: (1) political geography proxied by political alignment, (2) corporate political strategies, proxied by donations to political action committees & lobbying expenditures, (3) and government interference, proxied by dependence on procurement contracts & federal regulations, and exhibit that an industries’ political profiles impact its returns. Industries with high political alignment, concentrated corporate political strategies, and low government interference, earn an annualized alpha of 11.79%, significantly out-performing the market. The results hold in a cross-sectional setting, as industries with high political alignment, concentrated corporate political strategies, and low government interference, earn a 12.95% higher return than that of all other industries.Do Mutual Fund Investors Really (Not) Learn? A Model-Free Learning Approach
Abstract
We show that mutual fund investors with limited financial literacy still attempt to learn the value of a fund via the model-free learning approach. The model-free learning algorithm, which roots in the fields of neuroscience and psychology, requires little knowledge about the environment. Moreover, during the model-free learning process, investors evaluate the reward of a fund as the higher of the excess return over the risk-free rate and the market-adjusted return to support their decision of holding the fund. We propose a model-free learning expectation measure and show it helps explain both the fund flows and the flow-performance convexity puzzle. The Morningstar ratings and behavioral bias measures cannot explain the results. Thus, our study sheds light on the debate about investor sophistication.Product Market Decisions and Subprime Lending by Captive Finance Companies
Abstract
I study whether companies strategically utilize captive financing, a form of providing funding to consumers, to manage product demand. Using detailed data on auto loans, I show that captive lenders alter the financing terms and lending standards throughout the product life cycle. They reduce interest rates, allow longer maturity, charge lower down payments, and relax loan standards (1) when the underlying car models become outdated; (2) when competitors release new models; and (3) when they experience exogenous shocks such as recalls. While the lower interest rates offered by captive lenders reduce the likelihood of consumer default in the short term, the average default rate eventually increases in the long horizon because captive lenders’ willingness to dispense higher-risk loans allows more subprime borrowers to access credit. For consumers who cannot find a loan from non-captive lenders, borrowing from captive lenders help them in purchasing a car, but they could potentially be approved for a loan they cannot afford. These findings collectively suggest that captive financing is a tool manufacturers use to boost car sales throughout the product life cycle, while this tool could induce overleveraging by consumers.Environmental Risks and Loan Contract Terms
Abstract
This paper investigates whether and how firm-level environmental risks are reflected in banks’ credit policies, in absence of intense regulatory scrutiny. I find that following an adverse en- vironmental incident, banks start to take into account weak environmental performance as a fundamental risk to firms, by requiring higher loan interest rates and more restrictive covenants on firms with environmental concerns. However, this shift in lending practices is driven by banks with green expertise, that is, an information advantage accumulated through prior relationships with environmentally friendly firms. Other banks that do not possess such green expertise tend to issue loans with shorter maturities and more collateral to mitigate environmental risks. I further illustrate that banks’ green awareness get transmitted to the real economy, leading to improvements in firm-level emission reduction and green innovation.ESG Investing: A Tale of Two Preferences
Abstract
What motivates ESG integration? I find both non-pecuniary and risk-mitigating preferences explain its prominence. Using widely endorsed ESG ratings, I show each preference induces sizable ESG equity premium identified through option-implied expected returns. Due to unexpectedly persistent demand growth for ESG-conscious assets, realized returns mask true ESG pricing effects, especially those attributable to non-pecuniary preference. Consequently, this paper lends support to recent theoretical frameworks on ESG investing with non-pecuniary preference and reconciles mixed evidence in the empirical literature. In addition, I am able to identify the impact of investors' hedging motives against negative non-pecuniary externalities via option-implied risk-neutral moments.Expected Growth and Stock Returns: A Machine Learning Approach
Abstract
Expected growth is an important firm fundamental variable but is unobservableand difficult to estimate. In this study, I apply machine learning (ML) to forecast
growth at the firm level. Compared with the conventional linear regression, ML models
produce more accurate forecasts out of sample. Among the ML models, non-linear
models perform the best. In particular, the gradient boosting regression reduces the
mean and median forecast errors by 9.52% and 20.95%, respectively, relative to linear
regression. Moreover, the ML-based growth measure exhibits sensible properties at
the firm level, in subsamples, and at the aggregate level. Finally, I use the firm-level
growth forecasts to predict cross-sectional stock returns. Consistent with theory,
expected growth positively predicts future returns. Controlling for past growth, firms
in the top expected growth decile beat those in the bottom decile by an average of
0.56% per month (t = 4.49), which cannot be explained by most benchmark models.
What can we learn about the equity premium from professional forecasts?
Abstract
Using macroeconomic forecasts by professional economists, we construct a comprehensive macro condition index that summarizes subjective expectations of output, inflation, labor and housing market conditions. The index varies strongly over business cycles and significantly predicts stock returns both in and out of sample. Through the comparison with realized macroeconomic variables, we demonstrate that our index primarily reflects the true yet unobserved macroeconomic condition that matters for the equity premium. Further analysis shows that the predictability is not driven by survey forecast biases and is mainly from a discount rate channel. Consequently, the predictive power of the index comes from investor’s rational response to the changing macroeconomic condition. Overall, our findings portray a tight relation between the equity premium and broad aspects of the macroeconomy, suggesting that multiple state variables, especially those related to labor and housing market conditions, are at work empirically.Factor Extrapolation (Contrarianism): Evidence based on Mutual Fund Holdings
Abstract
In financial economics, one key ingredient in driving asset prices is investors' belief formation process. Deviating from the rational paradigm, recent studies examined behavioral biases that may affect information, such as limited attention, overconfidence, anchoring bias, and return extrapolation. In this paper, I offer a new reveal-expectation approach to identify belief formation and link it to investor characteristics.My approach can be described as follows. When returns of well-known style strategies are realized in the market, investors may react to these returns by altering their portfolio composition. By observing the dynamic response of portfolio formation to return realizations, one can infer behavioral biases investors may possess when attempting to form expectations of future strategy returns. While extrapolators chase after high returns by increasing their exposure to a style strategy, a contrarian investor should do the opposite, essentially betting against past returns.
Assuming that investors' expectations are consistent with their investment decisions, my approach tries to infer beliefs from actions, and is therefore an application of revealed preference theory. Compared to alternative methods proposed by the literature, it presents several advantages. First, although the availability of survey data allows researchers to empirically test investors' belief formation, survey data has its limitations. One drawback of using survey data is that investors' responses in the survey are not necessarily consistent with their actual subsequent trading behaviors. In other words, the extent to which the survey truthfully reflects investor behavior bias is limited. To overcome the challenge from using survey data, my reveal-expectation approach infers fund manager expectations from their asset allocations directly by observing mutual fund holding data. Second, the U.S. mutual fund industry provides an economically meaningful setting to test belief distortions because: 1. Timely holdings data are released publicly, providing quantifiable information to measure expectations and biases therein; 2. Style investment strategies are ubiquitous among mutual fund managers, which are ideal targets for measuring belief formation; and 3. The rich cross-section provides statistical power to link behavioral biases to personal traits, allowing one to dive deeper into the driver of behavioral propensities.
By relating stock holdings in a fund's portfolio to past factor returns (Fama French three factors and Carhart momentum factor), I systematically test mutual fund managers' belief formation from their trading behavior and document the importance of contrarianism in contrast to extrapolation and other popular prominent biases in belief formation.
First, I study fund managers' investment behavior by observing change in equity holding in the fund portfolio in reaction to change in factor returns and then infer their revealed expectation. To do so, I first measure the extent of exposure on a factor for each fund by computing fund betas for that factor in two steps following Jiang, Yao, and Yu (2007). I then measure the degree of extrapolation (contrarianism) for each fund with respect to each of the FFC4 factors as the coefficient estimate by regressing change in fund betas on past one-year factor returns. Therefore, a positive (negative) measure of factor extrapolation (contrarianism) refers to a fund manager with extrapolative (contrarian) trading activities. To make inference on whether extrapolators or contrarian managers exist in the entire cross section, I utilize a bootstrapping approach proposed by Fama and French (2010) and compute cross-sectional statistics across all funds, together with their bootstrapped p-values. According to the results from four cross-sectional distributions of extrapolation (contrarianism) measures with respect to each FFC4 factor, I show that rather than belief extrapolation, a substantial fraction of mutual fund managers act as contrarian investors in the sense that they trade against the popular factor returns, which are value, momentum, and market excess returns.
Second, I relate the degree of contrarianism to mutual fund performance by using portfolio sorting analyses and find evidence of superior performance generated by contrarian funds. I first construct a measure of aggregated factor extrapolation (contrarianism) across the four factors to identify extrapolators and contrarian funds. I define XScore1 at each quarter end as the sum of four standardized coefficient estimates by separately regressing change in fund beta on past one-year returns of each factor with a rolling window using all data prior to current quarter end. Therefore, a fund with a positive XScore1 refers to an extrapolative funds who chase after factor returns while a fund with a negative XScore1 refers to a contrarian funds who bet against factor returns. To implement the sorting procedure, I sort all funds into deciles on their XScore1 at each quarter end and calculate next-one-month portfolio alphas, adjusted by the FFC4 factor model. Overall, I find significantly larger alphas generated by contrarian funds. Contrarian funds significantly outperform extrapolators who extrapolate from past factor returns by 2.76% (2.71%) gross (net) annualized FFC4 factor model adjusted alphas. Furthermore, I find that the better performance of contrarian fund managers comes from the fund managers' factor timing abilities, especially their timing ability of the value premium. By examining strategies which involve 5-by-5 double independent, I further show that Xscore1 is a solid and independent fund performance predictor. To conclude, the results from portfolio sorting analysis provide evidence that Xscore1 contains information to predict fund performance and contrarian funds on average significantly outperform extrapolative funds.
Lastly, I relate contrarian investing to fund traits through a Fama-MacBeth regression (hereafter FM regression) of XScore1 on a variety of lagged fund-level characteristics. In this paper, explanatory variables of fund-level characteristics include expense ratios, total net assets (TNA), turnover ratios, fund age, fund flow, 3-month fund volatility, manager experience in a fund, number of managers in a fund, and a dummy variable which equals to one if there is either a new manager added or an existing manager removed from the fund and otherwise zero. The results from FM regression with Newey-West adjusted t-statistic show that contrarian funds with a positive XScore1 are associated with higher expense ratios, lower turnover ratios, and more experienced management teams. This result supports the claim that contrarian fund managers are sophisticated investors by betting against factor returns to exploit mispricing correction due to factor mean reversion.
Firm Investment, Costly Reversibility, and Stock Returns
Abstract
I study the asset pricing implications of investment and disinvestment options with a production-based model featuring costly reversibility. Investment options are contingent claims on assets in place so that they are riskier and earn higher expected returns. Disinvestment options with costly reversibility reduce exposure to aggregate risks amid deteriorating business conditions and lower expected returns on a firm. The inextricable link between investment options and disinvestment options explains the coexistence of the profitability premium and the value premium while retains a positive relation between profitability and market valuation ratios. My model also generates a procyclical profitability premium and a countercyclical value premium.Foreign Investors' Industry Expertise and Firm Value
Abstract
This paper identifies the industry expertise of foreign institutional investors using the industry structure of their domestic stock market as an indicator. Foreign investors are labeled as advantaged if the firm’s industry is one of their home country’s Top 3 industries in terms of market capitalization. Using firm-level data across 70 non-U.S. countries between 2000 and 2017, I show that foreign advantaged ownership has a positive and long-term effect on firm value while remaining foreign ownership has an insignificant or negative effect. I further identify two economic mechanisms through which the industry expertise of advantaged foreign investors may increase firm value: advantaged foreign investors are better monitors and bring greater knowledge spillovers. Finally, the positive effects of advantaged foreign investors on firm value are primarily due to operating improvements rather than changes in payout policy.From In-Person to Online: The New Shape of the VC Industry
Abstract
Geographical clustering is an essential feature of the venture capital (VC) industry as proximity helps VCs to acquire soft information about early-stage companies. VCs rely on their network and interactions with founders to reduce the information asymmetry of private markets. Known as active investors, they also need this proximity for their post-investment activities. By creating an unexpected interruption in face-to-face interactions, Covid-19 stressed the traditional venture capital investment model. The replacement of in-person with online meetings reduced the gap between collecting soft information from proximate and distant startups and raised questions about the importance of in-person events. We document that VCs respond to this change by breaking their traditional norm: they invest in more distant startups. We find that this evolution goes along with selection criteria and syndication process changes despite some persisting behaviors. Hence, our results support that, even VCs, who put a lot of emphasis on in-person interactions, revisit their investment model. Our findings contribute to questioning the future of the VC industry and shed light on the value of soft information for VCs.Global Corporate Default Risk Factors: Frailty and Spillover Effects
Abstract
We study the drivers of corporate default clustering from a global perspective. Across different regions worldwide, we confirm that firm-specific and systematic variables are inadequate in accounting for clustering of default events. To mitigate this issue, we propose a time varying latent factor (frailty) that can more adequately account for global corporate default clustering. Our frailty factor is constructed using the Generalized Autoregressive Score (GAS) paradigm. In contrast with existing literature on corporate default clustering with frailty factor, our approach is more computational efficient, which can be flexibly applied in a big data setting that concurrently incorporates both a long time series of firm-level data and comprehensive coverage of explanatory variables. Based on our frailty factors, we uncover two novel risk insights. First, we identify significant evidence of international default contagion. Second, we identify evidence for a “Global Corporate Default Latent Factor”, a single common factor that explains comovement in global corporate default risk, beyond information contained in explanatory variables. Finally, based on our frailty factor, we construct a stress test model that can provide a more realistic prediction of corporate default risk under adverse macroeconomic environment.Global Portfolio Network and Currency Risk Premia
Abstract
I show how foreign equity and debt investments explain cross-sectional variation in currency excess returns. Using bilateral asset holdings of 26 countries from 2001 to 2021, I construct a network centrality measure where a country is more central if it is integrated with core countries which account for a large share in global portfolios. I find that currency excess returns and interest rates decrease in network centrality. The network centralities are persistent over time and offer a country-specific economic source of risk which drives differences in currency excess returns. A long-short investment strategy with currency portfolios sorted on network centrality yields an annualized Sharpe ratio of 0.54. In an asset pricing model, I show that the derived risk factor is priced in a cross section of currency portfolios. Further, global risk aversion shocks cause currencies of central countries to appreciate, while currencies of peripheral countries depreciate; hence investors demand a premium. This is consistent with the idea that currency excess returns compensate for time-varying risk. I rationalize the findings in a partial equilibrium model of exchange rate determination where the sensitivity of investor country's global portfolio to valuation effects induced by asset price changes depends on the issuer country's market capitalization that affects marginal utility growth.Guns and Kidneys: How Transplant Tourism Finances Global Conflict
Abstract
This paper investigates the impact of organ trafficking on local conflict using georeferenced data on conflict events and hand-collected data on local transplant infrastructure in eight countries known for illegal transplanting. I exploit exogenous variation in kidney demand measured by the number of U.S. waiting list patients, their payment capacity, and their physical condition. Higher kidney demand increases conflict in localities with a transplanting center. Specifically, a one-standard deviation increase in the U.S. waiting list for kidneys leads to a 17% increase in the probability of conflict and a 1% increase in the number of conflict events compared to localities without transplant infrastructure. Consistent with the hypothesis that armed groups use organ trafficking to finance violent attacks, I find that non-state armed groups with transplanting capacities in their home region perform more attacks when kidney demand is higher. These attacks happen both in their home region and in other regions, spreading violence over space. My results further show that higher kidney demand is associated with an increase in suspicious payments from and to countries known for illegal organ trafficking. This corroborates the hypothesis that non-state armed groups finance their attacks by organ trade.Heterogeneous Investor Consideration, Mutual Fund Competition, and Fund Fees
Abstract
We present a novel approach to measuring competition among mutual funds by examining the sets of funds investors consider when making investment allocations. We focus on the individual consideration sets revealed by prospectus views on the SEC's EDGAR website, and document limited and heterogeneous patterns of consideration, consistent with choice behaviour studied elsewhere. We formulate a micro-theory model in which investors' heterogeneous and overlapping consideration of investment alternatives grants funds differing degrees of (local) market power. We calibrate the model and show it can successfully predict the observed cross-sectional structure of mutual fund fees. We go on to study the composition of consideration sets to identify the fund characteristics driving investors' perceptions of similarity. Our approach reveals the importance of investor consideration in understanding fund competition and offers insights for future research on fund differentiation.Heterogeneous Macro and Financial Effects of ECB Asset Purchase Programs
Abstract
Central banks resorted to asset purchase programs to replace conventional policy measures, which became ineffective after interest rates approached the effective lower bound. We investigate their effects on financial markets and focus on heterogeneous transmission using a Bayesian structural vector autoregression analysis. Since financial markets react directly to policy announcements, we base our identification scheme on market surprises at the announcement time. We find evidence of a stimulating effect on the economy, declining government bond yields, increasing stock prices, increasing value-growth spread and a reduction in stress in corporate and sovereign debt markets after an asset purchase shock. We disentangle the effect among industry sectors and EMU countries and find that the effect is heterogeneous, with financial stocks and the economy of Southern Euro area countries being the most positively affected.How and Why Do Operating Firms Participate in Swap Markets?
Abstract
We study operating firms’ participation to the swap markets using their open IRS, FX, CDS/CDX, Commodity, and Equity swap positions reported to the DTCC, between 2018 and 2021. Results from regression discontinuity design analyses around discrete financial and credit risk thresholds show larger and more levered firms, with large foreign profits are more likely to use swaps. Focusing on the boundary of investment grade credit ratings, firms with larger capital expenditures and lower tangible assets are more likely to hedge, whereas firms at the boundary of the negative-to-positive Debt/EBITDA threshold and firms with high R&D expenses are less likely to hedge. These results are consistent with the view that risk management plays a role in firms’ investment decisions and their ease of access to capital markets. This is the first study establishing these stylized facts across multiple hedging instruments on the most complete sample of public U.S. firms in a panel data setting.How do Managers' Expectations Affect Share Repurchases?
Abstract
Companies repurchased a record amount of shares in the 21st century despite high valuations. An important motive for repurchases is likely to be the desire of firms to reacquire stocks that are undervalued. This paper evaluates the extent to which undervaluation is a motive for share repurchases using the difference between management earnings forecasts and consensus analyst forecasts as a measure of management's perception of firm value. The results imply that companies increase share repurchases when they expect higher cash flows in the future than the market does. In addition, I analyze whether firms are truly undervalued in the market or misvalued by managers when they repurchase shares. I find that the higher management earnings forecasts preceding share repurchases are associated with relatively stronger post-repurchase performance in terms of incomes and stock returns. A measure of managerial overoptimism does not explain the relationship between repurchases and earnings expectations. These results imply that managers' repurchase decisions are more motivated by insider information or the market's misvaluation of firm values.How Robust are Empirical Factor Models to the Choice of Breakpoints?
Abstract
We comprehensively investigate the robustness of well-known factor models to altered factor-formation breakpoints. Deviating from the standard 30th and 70th percentile selection, weuse an extensive set of anomaly test portfolios to uncover two main findings: First, there
is a trade-off between specification versus diversification. More centered breakpoints tend
to result in less (idiosyncratic) risk. More extreme sorts create stronger exposures to the
underlying anomalies and, thus, higher average returns. Second, the models are robust to
different degrees. The Hou, Xue, and Zhang (2015) model is much more sensitive to changes
in breakpoints than the Fama–French models
Imperfect Banking Competition and the Propagation of Risk Shocks
Abstract
This paper studies how the intensity of competition in the banking sector affects the propagation of risk shocks. Analyzing a panel dataset of 44 country, I show that an increase in uncertainty has a stronger negative impact on output growth when banking competition is lower. In order to explain this fact, I build a dynamic stochastic general equilibrium model with imperfect banking competition and financial frictions. In the model, entrepreneurs and imperfectly competitive banks engage in a loan contract and entrepreneurs receive idiosyncratic returns from renting capital. When banking competition is lower, banks charge higher loan rates to their borrowers making borrowers more fragile. Because of higher borrower fragility, second moment shocks to entrepreneur return have stronger negative effects on credit supply, investment and output when banking competition is lower.The Firm Balance Sheet Channel of Uncertainty Shocks
Abstract
Spikes in aggregate uncertainty are followed by large investment and output drops. This paper highlights the role of pre-existing debt on corporate balance sheets — a missing piece in the literature — in transmitting uncertainty shocks. Empirically, following uncertainty shocks, average firm-level physical capital drops while liquid assets holding grows. Importantly, this shift in corporate portfolio choice is much more pronounced among ex-ante more indebted firms. I develop and estimate a quantitative heterogeneous-firm model with financial frictions to account for the novel empirical patterns. The calibrated model captures cross-sectional heterogeneity in corporate balance sheets, generates empirically-consistent corporate investment and financing behavior, and successfully reproduces the observed average and heterogeneous responses to uncertainty shocks. In the model, in response to uncertainty shocks, more indebted firms increase liquid assets more in an effort to avoid liquidity shortfalls for future debt repayments, thereby leading to larger cuts in capital investment. I then use the model to study the aggregate implications of this novel transmission mechanism. I show quantitatively that the aggregate impact of uncertainty shocks depends on the stock of outstanding debt accumulated ex-ante. I find that credit market interventions mitigate both the depth and persistence of output drop following uncertainty shocks, which sheds new light on stabilization policies during periods of high uncertainty.Inflation Expectations and Households Portfolio Choice
Abstract
Do household inflation expectations affect portfolio choice? This paper exploits inflationexperience as an instrumental variable for inflation expectations, and links it to household portfolios. I document that households with higher inflation expectations are more likely to invest in equity markets, shifting from safe assets to risky ones. Households can also achieve substantial financial returns and optimize their portfolio. I also document that households’ heterogeneous characteristics also contribute to the portfolio re-balance. In addition. I attribute the above findings to the income expectations and nominal rigidity of the deposit rate. These results imply households’ portfolio rebalancing behavior in response to increased inflation expectations
Information Asymmetry, Liquidity, and the Choice between Private and Public Bond Issuance
Abstract
This paper uses the effects of a regulatory change to provide new evidence on the choice between issuing debt securities in the private and public markets. With a more streamlined public issuance process, firms are more likely to seek financing in the public market. This effect is more pronounced for firms characterized by higher information asymmetry and whose debt offerings are characterized by lower expected liquidity. Furthermore, the regulatory intervention also produces real effects on firms’ operations. More specifically, firms increase investments and operating performance but keep leverage and cash holdings unchanged. The findings in this paper speak of unexpected consequences of the regulatory change and have implications for policy making.Investor Sentiment and Sell-side Research Quality
Abstract
We investigate whether investor sentiment affects the research quality of sell-side analysts. As institutional investors regard industry knowledge as the most important element of sell-side service, we use it to proxy for sell-side research quality. Using textual analysis to measure the industry knowledge in Chinese A-share healthcare reports, we find that more in-depth analysis that focuses on the healthcare industry is associated with higher accuracy and value to investors. After controlling for confounding factors, we find that when investor sentiment is higher, analysts’ research quality is lower. Further analysis shows that institutional investors reduce their demand for fundamental analysis during bubble periods, and analysts cater to their clients’ time-varying demand by strategically adjusting their efforts.Managerial Taxes, Co-ownership, and Risk-Taking Decisions
Abstract
We investigate the effect of personal taxation on the risk-taking decision of mutual fund managers, conditional on whether they hold shares of the funds they manage. Since capital losses can be offset against capital gains tax liabilities, higher taxation thus reduces the downside of risk-taking, motivating a risk-averse fund manager with co-ownership to take more risk. Exploiting the enactment of the American Taxpayer Relief Act 2012 as an exogenous shock that led to a significant tax increase in the US, we find that fund managers with high co-ownership increase their portfolio risk by 0.45 percentage points, equivalent to a 19%-standard-deviation increase in risk-taking. Such a relationship is stronger for funds with higher rates of return and for managers with lower risk aversion. Moreover, we find a negative impact of personal taxation on fund performance, particularly for funds with a more severe agency problem. Our findings provide evidence that the shocks of personal taxation can go beyond the scope of individuals and spill over to investment companies and, consequently, to the broader investing public.Market Fragmentation and Price Impact
Abstract
We investigate the effects of market fragmentation on price impact. Using a newlylaunched exchange as a quasi-natural experiment, we find that an exogenous increase in
market fragmentation leads to a higher price impact of equity trading in the primary
U.S. equity exchanges. Our IV estimates suggest a one-standard-deviation increase in
market fragmentation of a stock will induce approximately 26.5 bps increases in NBBO
price impact and much more significant increases in each exchange-based price impact for
trading that stock. In addition, we also find the market depth at each existing lit exchange
is negatively associated with the total order volume submitted to the new exchange. Our
results are providing supportive evidence to the recent theories such as Chen and Duffie
(2021) that market fragmentation decreases market depth at each exchange level, increases
the aggressiveness of order submissions, and makes the order book slope more inelastic thus
leading to increases in price impact under a multi-market setting.
Market-Based Policy Promoting Diversity and Equity: Evidence from the Housing Market
Abstract
The increased awareness of the importance of diversity, equity, and inclusion (DEI) in recent years has prompted organizations to embrace this social movement. One such organization is GreatSchools (GS), which provides nationwide school-quality ratings disseminated across the largest PropTech brokerage platforms in the US. At the end of 2017, GS changed its rating system away from focusing exclusively on test scores (TS) by incorporating a DEI measure. I exploit this discrete one-time change and deconstruct the rating into TS-based and DEI-based components to evaluate the effect of GS rating’s DEI integration on households’ financial decisions via home prices. Overall, the change ultimately makes GS rating less relevant, as home prices become much less responsive to the new rating index than to the previous one. Similar homes in the same zip code are then carefully matched to draw a meaningful comparison between transactions assigned to schools that experience GS rating changes and those in schools that see no changes. The results show significantly positive price premiums for properties in schools with negative GS rating change, in comparison to their control counterparts. To investigate the channel through which such results manifest, I conduct heterogeneity analyses that exploit cases when GS rating and TS move in opposite directions and show that price premiums are explained by the increased portion of GS rating that is attributable to the TS-based component. However, not all households prefer TS to GS rating as a signal of school quality, as preferences depend on homebuyer locality. House prices in markets that are heavily comprised of nonlocal homebuyers move in the same direction as GS rating changes, while those in markets with predominantly local homebuyers exhibit strong positive responses to TS changes regardless of any shifts in the third-party school rating. This evidence supports the notion that readily available heuristics are likely most valuable to informationally disadvantaged homebuyers, in accordance with the local network information channels and long-standing school reputational mechanisms.Network Factors for Idiosyncratic Volatility Spillover
Abstract
This paper studies the network structure change of idiosyncratic volatility spillover among sectors. Changes in the network structure are captured by two asset pricing factors: Concentration factor and Magnitude factor. The two factors determine the node size distribution and linkage thickness distribution respectively in an idiosyncratic volatility spillover network and they contain distinct sources of systematic risk. Concentration factor measures the degree to which the contamination capacity is dominated by a few large sectors and Magnitude factor measures the average possibility of idiosyncratic volatility spillover. Concentration factor earns a positive price of risk while Magnitude factor earns a negative price of risk. Cross-sectional tests show that stocks more exposed to Concentration factor are riskier (with an annual return spread of +5%) and stocks more exposed to Magnitude factor are hedges (with an annual return spread of -4%). These return gaps cannot be explained by standard asset pricing models such as three/four/five-factor model. These second-order ("volatility level") network factors contain extra systematic risk than the corresponding first-order ("return level") network factors, which sheds light on the intuition that idiosyncratic volatility spillover covers more underlying interconnection mechanisms other than the ordinary input-output chain. Lastly, I give a multisector model to link the idiosyncratic structure change to the aggregate volatility. Conditionally, a higher Concentration factor and a lower Magnitude factor can increase the cross-sectional decay rate (“diversification speed”) of aggregate volatility when sector number n goes to infinity. This further validates that a higher Concentration is good news since there are fewer potential sources to contaminate the whole economy and that a higher Magnitude is bad news since the contamination is more likely to happen.Networks in the Board of Directors: A Choice Set Consideration Approach
Abstract
1. INTRODUCTIONRecruitment in the board of directors involves many factors, which are hard to disentangle. It is in the firm’s interest to have skilled directors and a board devoid of deadlock, and share- holders may want to appoint directors who are able to both advise and monitor the CEO. On the other hand, it might be in the interest of the CEO to pack the board with friends to ensure his continuation as a CEO, and he may prefer board members that vindicate his decisions and support him in front of the shareholders.
The problem is well known, and numerous pieces of legislation have been passed to ensure the alignment of shareholder and director interests. Among them are regulations on a minimum share of independent directors, which are directors that are not supposed to have any meaningful financial relationships with the supervised firm and its corporate officers outside of sitting fees.
It is worth noting that the above-described issues are not antithetic. A CEO may want skilled advisors who can provide advice when necessary, but vindicate his decisions. And a board that is cooperative and friendly towards the CEO will often be devoid of deadlock. There can be a gain in efficiency in appointing like-minded individuals to the board, and having a gridlocked board can reinforce the CEO’s position as shown in Donaldson et al. (2020).
When thinking about the importance of preexisting relationships in the board’s recruitment process, we accordingly end up with several intuitions. First, there is the aforementioned co- ordination concern, as it may be optimal to recruit like-minded individuals. Then, there is the screening concern: because of incomplete information, preexisting relationships may help with inference about the type of a director. That is, it may be easier for the board to reliably recruit skilled, fitting candidates through its network. Finally, there is the possibility of cronyism or nepotism. Bringing friends and cronies to the board may make governance easier while de- creasing the supervision faced by the CEO and the board.
In this paper, I use insights and methods from the product market literature to produce reliable estimates of the role of networks in the appointment process. By aggregating the potential candidates into profiles based on observables, I can produce novel joint estimates of the importance of networks in the recruitment process relative to other candidate characteristics. Moreover, I can meaningfully interact firm characteristics and director characteristics, which allows me to disentangle the various intuitions outlined above. For example, if the coordination concern is paramount, I would expect larger multi-industry firms to recruit directors connected to the board. If recruitment through networks is mostly about CEO power, I would expect firms with longer CEO tenure to be more likely to recruit directors through the CEO’s network.
My main contribution is twofold. First, I propose a rich and flexible specification inspired by the consideration set literature that allows me to jointly estimate the determinants of director choice and the composition of the choice set. This allows me to isolate the bias on parameters due to the composition of the choice set and recover the true parameter estimates. Secondly, I can exploit the vast dataset over 35 years and the structure of the model to get robust estimates on the relative importance of different observables in the recruitment process. This in turn al- lows me to shed light on which type of firm prefers to hire a given type of director and helps unravel the processes behind director appointment.
2. THE DATASET
The dataset is based on BoardEx data for the directors and network component, augmented with CRSP-Compustat data for firms and market variables.
BoardEx is a business-oriented dataset focused on network data on business executives, is by far the most complete dataset on firm board composition and maintains an impressive array of director and executive profiles. The dataset inventories 1.4 million individual executive profiles, linked to over more than 300 000 identified firms and a million other various organizations. From these profiles’ career and extra-professional history, it maps over 10 billion interpersonal relationships, with detailed information such as length of overlap, hierarchical positions, or the type of connection (educational, professional, social network, etc).
3. THE MODEL
In a consideration set model, we jointly estimate the probability of one option to be present in the choice set and the probability for this option to be chosen. Such a consideration set model allows for the endogenous determination of the choice set for each and every firm according to a set of parameters. I allow the choice set to be a function of the director’s experience, the director’s network and the director’s preexisting relationship with the board, and the size of the board’s network. Because of the computational complexity of this model, it must be estimated via simulation, as described in Goeree (2008) and Abaluck and Adams-Prassl (2021)
4. RESULTS
I find that most of the evidence pointing towards nepotistic behaviour disappears when properly accounting for choice set selection. Notably, firms that hire connected individuals are bigger, span less industries and have CEOs that are more recently appointed. Overall, the impact of personal connections on board nomination is very small. On the other hand, the size of the network of a candidate matters a lot, which suggests that networks are most likely used as a screening device: boards will gauge potential appointees through their networks. I confirm these results by estimating the nomination process in board committees. Since the choice set (i.e. the board) is known, the core difficulty of our study is entirely alleviated. Board members with pre-existing connections to the board or the CEO at the time of their recruitment are not more likely to be appointed to prominent and impactful committees (audit/compensation), whereas board members with a large network are. This points to spurious estimates in the previous literature: The size the network of a potential appointees matters, not their personal connexions to members of the board.
Non-dilutive CoCo Bonds: A Necessary Evil?
Abstract
We empirically document and theoretically investigate why non-dilutive CoCos are prevalent, even though advocates of CoCos suggest such securities should be dilutive to reduce bank risk-taking. In an agency model with two subsequent moral hazards, we show that while dilutive CoCos deter ex-ante risk-taking and prevent a bank from being undercapitalized, penalizing existing shareholders with dilution when the bank is already undercapitalized leads to risk shifting. CoCos' designs and risk implications depend on banks' equity capitalization, with non-dilutive CoCos particularly attractive to capital-constrained banks, because such securities can maximize the banks' financing capacity by tackling only the ex-post risk shifting.Non-Native Players in the Domestic League: Foreign Penetration and Domestic Banking Sector in an Emerging Market
Abstract
This paper explores how foreign bank penetration impacts the Vietnamese banking sector. By utilizing the comprehensive dataset of the Vietnamese banking system during the period 2005 to 2020, this study provides robust evidence on the impacts of foreign bank penetration on competition and efficiency of Vietnamese local banks. From the empirical results of Panzar – Rosse and Lerner approach, our findings support the hypothesis that the presence of foreign banks is associated with a more competitive market in Vietnam. This study also provides empirical evidence that domestic banks experience lower profits and take more risks when more foreign banks join the local market. Our findings remain robust under different econometric approaches and alternative proxies of profitability and risk-taking. We also find distinct impacts of bank-specific factors that more mature and bigger banks are better in maintaining performance compared to their younger and smaller counterparts. The differential effects of the foreign bank penetration on well- and under-diversified local banks. We also find that foreign banks exert more noticeable effects on local peers when they join the host market via greenfield investments, as opposite to M&A. Our findings propose several practical implications to policymakers, commercial banks, and stakeholders in the globalizing banking system.One-Sided Market Pressure and Interest Rate Differences: An Explanation for Covered Interest Rate Parity Deviations
Abstract
The financial crisis introduced a new era, one where covered interest rate parity deviations in combination with the USD are the new normal despite calm times (Du et al. 2018 and Cerutti et al. 2021).We present a model using a two component argumentation to explain the observed phenomenon - the deviations. The first part of the explanation is the introduction of regulatory costs due to one-sided market pressure and the implied accumulation of positions on the providers balance sheet. The second part accounts for small interest earnings arising through differences in the borrowing,
the Libor and the risk-free investment rate.
The model is empirically tested for the USD/Yen deviations. In addition the results are confirmed on a broad basis by adding the first difference in the interest earnings as an explanatory variable to the multi-currency regression run by Avdjiev et al. (AER 2019).
Option Liquidity and Gamma Imbalances
Abstract
We study the relationship between the market makers’ inventory and liquidity for S&P 500 options. Option spreads are higher when the aggregate gamma inventory is negative, i.e., when market makers act as momentum traders to keep their portfolio delta neutral. Aggregate gamma inventory can explain up to 1/3 of the daily variation in spreads. We show that market makers have balanced gamma inventory whenever markets are illiquid, volatile, and financial intermediaries are constraint. Our results indicate that market makers actively adjust option expensiveness to balance their inventory in the desired direction. Standard option valuation models and market microstructure theories contradict our findings.Private Interaction with Management: Evidence from Textual Analysis of Analyst Reports
Abstract
I identify private interaction between sell-side analysts and firm management based on 373,869 analyst reports for 2,958 U.S. firms by 2,238 analysts who work with eight large banks during 1997-2019. I find that earnings forecast accuracy increases after an analyst privately interacts with management, especially when the information asymmetry and forecast difficulty of the underlying firms are higher. Private interaction with management helps analysts reduce bias, produce more detailed and soft information such as operational and strategic information, and achieve better career outcome. My findings provide direct evidence that private interaction with management benefits analyst performance.Public Information Impact on Cryptocurrency Trading Activity: Evidence from News Media
Abstract
This paper examines the impact of news sentiment on the daily returns, volatility, and liquidity in the cryptocurrency market. We build a novel sentiment indicator from news headlines using the Natural language processing (NLP) technique. The sentiments are classified into positive and negative news sentiments to understand their differential impact. The most dominant cryptocurrency, Bitcoin, experiences a “negativity effect,” i.e., the impact of negative news on returns is higher than the positive news. The returns, volatility, and liquidity of small and young cryptocurrencies increase with positive news as uninformed investors herd and buy these cryptocurrencies with the fear of missing out during the higher crypto valuations. There exists an asymmetric volatility effect on altcoins. The “fear of missing out” phenomenon explains the increase in volatility with the positive news. However, Bitcoin’s volatility and liquidity are immune to the news sentiment.Real Effects of Financial Innovation: How Corporate Bond ETFs Spur Research and Development
Abstract
Corporate bond exchange traded funds (ETFs) have become a stable source of capital for US firms. Conditional on bond ownership today, the probability ETF ownership for the next nine years is 69.98%. This stability in the supply of debt capital, and the lower cost of debt afforded by ETF ownership, enables firms to increase expenditures on R&D projects, especially those with higher monetary values. Using two exogenous ETF inclusion rule changes, we propose a causal link between bond ETF ownership and firm R&D investment. Finally, a theoretical model of debt choice and investment explores firms' endogenous decision to issue debt that is ETF-eligible.Reputation and Asset Prices: Evidence from Trump Real Estate
Abstract
We analyze the effect of reputation on asset prices by exploiting Donald Trump's vast presence in the U.S. residential real estate market. Making use of the unprecedented sequence of controversies following his candidacy for U.S. president in 2015 that fueled the bipartisanship in U.S. politics, we contrast price effects in Manhattan, New York, a state in which the Democrats won the 2016 general election, with Miami, Florida, a state in which the Republicans won. Using Difference-in-Differences regressions, we find a discount of 16% to Trump-branded units in Manhattan for the period from mid 2015 to the end of 2017. For Miami, we document a price increase of 15% for the election year 2016, but no overall effect. Our results thus document the importance of spatial variation for reputation effects and that the partisan divide can spill over to asset prices.Resurrecting the Value Factor from its Redundancy
Abstract
The value factor is redundant in the Fama-French (2015) five-factor model and its explanatory power is primarily subsumed by the investment factor. We show that the value and investment factors' strong relation arises because book-to-market and investment are driven by common economic forces: cash flow shocks and discount rate shocks. We identify those stocks whose variation in book-to-market and investment is due to discount rate shocks and document that only they earn the value and investment premia. These stocks' value and investment premia are roughly 50% larger than the usual value and investment premia. We show that adjusted value and investment factors that use only stocks whose book-to-market and investment are driven by discount rate shocks cannot subsume each other. Thus, the value factor is not redundant if it is built only from stocks for which book-to-market is a good indicator of expected returns and which therefore actually reflect pricing information.Risk Factors for Corporate Bond Returns in the Euro Area
Abstract
I examine the cross-sectional drivers of corporate bond returns in the euro area using data from January 2002 to October 2020. With rising levels of bond financing in the currency bloc, I provide out-of-sample evidence for recently introduced characteristics of bond risk such as downside, credit, and liquidity risk. I find that many of these characteristics are associated with cross-sectional variation in returns and that downside risk exposure yields premiums in excess of established factors. I introduce a new risk characteristic to capture bonds' sensitivity to monetary policy intervention and find evidence that it explains variation in expected returns at the bond and portfolio level.Selling Private Equity Fees
Abstract
We examine private equity (PE) firms’ minority stake sales and the impact of these sales on agency frictions with fund investors. PE firms that have sold minority stakes – primarily to other PE firms – oversee 27% of PE Assets Under Management in 2020. PE firms with strong fundraising and investment records tend to sell stakes. Sellers subsequently experience substantial increases in capital raised (41%) and income (55%). We find no evidence of deteriorating fund performance. Sellers invest more capital in their funds, increase employment, and make investor-friendly distributions. Our results suggest that the reduced “skin-in-the-game” from stake sales does not exacerbate agency frictions between sellers and their fund investors.Silent Activism
Abstract
A portion of hedge funds’ engagement can be observed through their votes and regulatory filings. However, much of their communication occurs through direct interaction with management, which is not formally recorded. I use SEC EDGAR log file data to proxy for such engagements. This proxy indeed captures hedge fund interest: one hedge fund click more than doubles the probability of an activism event. Moreover, consistent with hedge fund clicks proxying for behind-the-scenes engagement, these clicks predict corporate governance changes, for example CEO and director turnover, even in the absence of a formal activist filing. This finding provides evidence that hedge fund activism is farther reaching and more effective than previous literature has shown.Smooth Ambiguity, Wealth Dynamics and Asset Prices with Heterogeneous Beliefs
Abstract
We study a class of endowment economies with long-run risks in which agents have generalized recursive smooth ambiguity preferences and heterogeneous beliefs. The expected growth rate of aggregate consumption consists of a persistent component. Agents cannot observe the component but learn about it via Bayes’ rule. Meanwhile, agents hold different beliefs about persistence of the long-run component. By examining a two-agent model, we find that: 1) the consumption share of the agent with the correct belief dominates in the long run, even when both agents have recursive preferences without smooth ambiguity, 2) smooth ambiguity, in conjunction with state uncertainty, generates uncertainty sharing motive that leads to long-run survival of both agents, 3) the time-varying weights of agents and posterior beliefs help explain the time variation of price-dividend ratios in the data, and 4) in a model with an ambiguity-averse agent and an ambiguity-loving agent, both agents survive in the long run if they hold differentbeliefs.
Social Contagion and Asset Prices: Reddit's Self-Organised Bull Runs
Abstract
This paper develops an empirical and theoretical case for how 'hype' among retail investors can drive large asset price fluctuations. We use text data from discussions on WallStreetBets (WSB), an online investor forum with over eleven million followers as of February 2022, as a case study to demonstrate how retail investors influence each other, and how social behaviours impact financial markets. We document that WSB users adopt price predictions about assets (bullish or bearish) in part due to the sentiments expressed by their peers. Peer influence is estimated in two ways using random, temporal variation in peers and an interaction network approach for different identification strategies. We model the impact of social dynamics among retail investors on asset price stability, and hypothesise that the interplay between 'trend following' and `consensus formation' determines the stability of price returns. Our results show that more socially-driven investing causes oscillations and cycles in asset prices. We apply the framework to identify components of asset demand stemming from social dynamics, measured using WSB data. Our predictions are statistically significant in explaining stock market activity. These findings emphasise the role that social dynamics play in financial markets, amplified by online social media.Sovereign Risk Premium, Bond Liquidity and Foreign Reserve Accumulation
Abstract
This paper analyses how foreign reserve accumulation affects sovereign credit risk.By using sovereign credit default swap (CDS) spread as risk measurement, I use
credit rating method to decompose CDS spread into default premium component,
which represents the possibility to default, and risk premium component,
which represents the price paid to the investors for bearing the default risk. Using
panel regression analysis, I find foreign reserve accumulation can effectively
reduce the CDS spread, mainly through risk premium component while it has no
significant effect on default premium component. By analyzing bond level data,
foreign reserve accumulation can effectively reduce spillover effect of global financial
volatility to the sovereign credit risk, also holding more foreign reserve can
improve liquidity condition of the sovereign bonds a country issued. I propose
that exchange rate intervention and sovereign repurchase are potential reasons.
Strategic Firm Behavior Preceding S&P 500 Reconstitutions
Abstract
The standards used by the S&P 500 to determine index participants can largely be divided into three categories: size, liquidity and financial viability. I identify firms that have a large ex-ante probability of being added or removed from the index, and argue that they have large incentives to influence the above criteria. I find that firms with a higher likelihood of addition issue approximately 50% more shares than the average firm. However, 30% to 70% of the effect can be explained by a marked increase in the announcement of stock splits. This group of firms also pays 15% fewer cash dividends and sharply increases discretionary accruals. Each of these corporate finance variables has a direct effect on the methodology used by S&P. This evidence supports the hypothesis that firms attempt to maximize their chance of joining the index by strategically changing corporate policies. All of the extant literature has, so far, been focused on the ex-post implications of index additions. However, I argue, that firms internalize the probability of entering the S&P 500 and behave accordingly. This study demonstrates the ex-ante implications of index additions, which have clear repercussions on the interpretation of studies focusing on financial outcomes following additions.Structure Changes in Autoregressive Conditional Skewness: Evidence from Digital Currency
Abstract
In this paper, we propose a model to estimate autoregressive conditional skewness for different hidden states based on returns of digital currency or text-based analysis of investor sentiment. Our models allow us to change the structure of digital currency markets, including the mean and variance of returns. We empirically utilize this model to investigate the price of multiple digital currencies. The evidence shows the highly persistent conditional skewness occurs when investors’ sentiment was fear and despondent while impersistent one occurs when investors were thrilled about the upward market.Superstar firms and market power: The role of common ownership and corporate spillovers
Abstract
This paper examines if the surge of common ownership contributes to the rise of superstar firms and market power. I show that passive common owners help superstar firms to internalize technological and managerial knowledge spillover resulting in higher profits and markups. On the other side, they harm firms in the lower percentiles of the profit distribution. These findings suggest that common ownership does not reduce competition among superstar firms but bolstering their star status may increase market concentration.The Debt Payment Puzzle: An Experimental Investigation
Abstract
This paper studies the sources of suboptimal allocations observed in credit card repayments using a diagnostic laboratory experiment. We find that optimization ability and limited attention are jointly insufficient to explain the puzzle. Moving beyond existing results, we find that the inherent negative frame of the debt payment problem interferes with subjects' ability to optimize and hinders learning. We show that subjects predominantly rely on the irrelevant balance information while forming their decisions, regardless of how vividly the balance information is displayed. Using additional treatments, we find that the debt frame increases subjects' focus on the irrelevant balance information.The Economics of ETF Redemptions
Abstract
This paper provides novel evidence of redemptions in corporate bond exchange-traded funds (ETFs). I first investigate economic incentives for choosing redemption baskets in the primary market. ETFs dispose of bonds with high price pressure exposures, and authorized participants (APs) select assets negatively co-move with liquidity in AP portfolios. Regarding the economic impacts, redemptions decrease ETF returns, liquidity, and efficiency in the less elastic secondary market. APs profit from redemptions by correcting arbitrage between ETFs and underlying assets. Lastly, new policies in the COVID-19 pandemic consistently impact ETFs in both primary and secondary markets.The Impossibility of Saving by Spending
Abstract
I study the effect of enrollment in a round-up savings program on consumer spending behavior and financial outcomes. I find that upon enrollment in a round-up savings program, households increase their total spending. This effect mostly stems from discretionary spending and is driven by both spending frequency and average purchase amount. This increase in spending, with income fixed, leads to a gradual increase in the propensity of liquidity shortfalls.I use a difference-in-differences estimator to measure causal effects of round-up savings on consumer spending. I find that consumers increase their spending by around $300 per month upon enrollment in round-up savings over a two-month post-enrollment period. Compared to a saving amount of approximately $4.50 per week after enrollment, these results suggest a short-run detrimental effect of round-up savings on household finances.
The Expected Returns of ESG Excluded Stocks. Shocks to Firms Costs of Capital? Evidence from the Worlds' Largest Fund
Abstract
We investigate the consequences of widespread ESG-based portfolio exclusionson the expected returns of firms subject to exclusion. We use the exclusions
of Norway’s “Oil Fund” as a sample of low quality ESG stocks. The fund is
the world’s largest SWF, whose ESG decisions are viewed as a model for many institutional
investors. We construct portfolios representing their exclusions and
find that these portfolios have significantly superior performance (alpha). The
sheer magnitude of these excess returns (more than 5% in annual terms) leads
us to conclude that low-quality ESG stock has a return premium, as predicted
by e.g. Pastor et.al-(2021). We also show evidence of the mechanism. Excluded
firms face a higher cost of capital. If the exclusion is revoked, their capital costs
fall. Companies with low ESG at the time of exclusion (more scope for improvement),
and higher revenue growth (investment needs) are more likely to
get their exclusion revoked, which we interpret as evidence of dynamics: Firms
improve their ESG to revoke exclusions and achieve lower required returns. In
fact, firms that get off the exclusion list do not have superior performance going
forward
The Human Capital Reallocation of M&A: Inventor-level Evidence
Abstract
Mergers and acquisitions (M&A) of innovative firms lead to a significant restructuring of the inventor labor force driven by abnormally high turnover for target firm inventors. Following the merger, inventors in the combined entity (primarily acquiring-firm and newly-hired inventors) file more citation-weighted patents. Departing inventors also increase patenting productivity significantly, and the non-merging firms hiring these inventors improve patenting performance. Overall, these findings indicate that mergers have an economically important impact on the restructuring and productivity of the labor force and provide novel evidence of positive spillover effects of M&A on non-merging firms through post-merger labor restructuring.The Impact of Financial Regulation on Bank Risk and Performance: The Basel III Spillover Experiment
Abstract
This paper aims at studying the causal effects of financial regulation on bank riskand performance. Identification of the causal effects of financial regulations on
banks has been a challenge as such regulations normally are enforced through all
banks in the same country/region at the same time, and decisions regarding the
type and the time of regulation adoption might be endogenous. By exploiting
two features of the Basel III regulation, (i) the sequential adoption of the Basel
III regulation in the different countries, and (ii) the ultimate parent rule, which
establishes that the subsidiary banks from early adopters of Basel III have to comply
with the latest Basel regulation even though they are operating in a country which
has not adopted Basel III; we identify two groups of banks that are under different
financial regulations in a same country: the subsidiary banks from countries which
early adopted Basel III (i.e., treated banks) in countries which have not adopted
Basel III, and the domestic banks of those countries (i.e., untreated banks). Relying
on a difference-in-difference estimation approach, we empirically identify the effects
of Basel III on banks by comparing the overtime variation of risk and performance of
treated banks with the same outcomes of untreated banks in non-adopters countries
of Basel III before and after Basel III implementation in 2015. Our results suggest
that treated banks increase their profitability (ROA and ROE) and liquidity ratio,
while reduce their risks as a result of a decrease in non-performing loans (NPL) to
loan ratio.
The Information Value of M&A Press Releases
Abstract
How do managers comment on merger transactions? By analyzing initial public announcements of Mergers and Acquisitions (M&As) between 1995-2020 and extracting the linguistic sentiment from statements made by managers of acquirer and target firms, we provide new evidence on the informational value of M&A disclosures. We find that positive target sentiment results in positive returns for the target, while sentiment disagreement with the acquirer is associated with lower target returns. Further, the positive target sentiment increases the likelihood of a merger completion and tends to shorten the time to deal completion. We decompose acquirer sentiment into manipulative and fundamental components and demonstrate that acquirer CEOs with low confidence and large ownership holdings in the acquirer firm produce M&A statements that are more manipulative. This suggests that sentiment in M&A disclosures not only contains information on fundamentals and managerial attitudes but that it may be manipulated to protect the personal interest of managers.The Litigation Sensitivity Channel of Shareholder Rights
Abstract
We develop a novel firm-level measure of class-action litigation exposure using textual analysis of risk factor disclosures in corporate filings. Ex-ante litigation exposure predicts future litigation events and commands a risk premium. We document a new litigation sensitivity channel of shareholder rights by exploiting our measure and the variation in U.S. circuit court ideology. For a wide range of outcomes, litigation-sensitive firms respond more sharply to shifts toward more liberal courts. Strengthened shareholder litigation rights foster valuable corporate innovation and improve firm prospects. Our results emphasize the importance of firm heterogeneity in assessing the impact of the litigation system.The Post-ECB Announcement Drift
Abstract
This paper documents a drift in equity prices in the days following monetary policy announcements of the European Central Bank (ECB). Using high-frequency data for European equities and government bond yields between 2002 and 2020, I construct monetary policy shocks and analyze the long-run response of European equities to these shocks. I find a prolonged drift in equity prices for up to 20 days. This drift is particularly strong in response to central bank news about the real economy - so-called information shocks - amounting to 139 (-116) basis points for positive (negative) shocks. To rationalize the drift, I investigate the role of investor disagreement on ECB announcement days. As measures of investor disagreement, I consider trading volume, textual data from the ECB press conference, and forecast dispersion among participants of the ECB Survey of Professional Forecasters. My findings suggest that higher levels of disagreement are associated with a stronger price drift in the days following the monetary policy event.Private Equity Buyouts and Productivity: A Narrative from Italy
Abstract
This paper assesses the real economic impact of Private Equity (PE) buyouts on firm productivity. As a case study, we examine the Italian economy, which presents a puzzling institutional setting of slow economic growth mostly caused by stagnating productivity. To this aim, we construct a dataset combining firm-level information with buyout deal data from 1998 to 2020. We analyze 692 buyout target firms before and after the deal, comparing them to a group of matched control firms. To address our research question, we conduct an event study by running a series of non-parametric comparisons. We then estimate a two-way fixed effects regression with staggered treatment adoption allowing for treatment effect heterogeneity. We find that in the years following a buyout, firm-level productivity significantly decreases, both in terms of labor productivity and total factor productivity. In explaining firm productivity drivers, we show that the negative effects seem to derive from growing inputs combined with stable output. Our findings suggest that while PE investors are increasing input factors, they do not manage to use them more efficiently to generate significantly higher output in the short run.The Scope of OTC Relationships
Abstract
We document that customers concentrate their OTC trading partners across asset classes. We also find that traders employed by a large European investment bank internalizes customers’ relationships with other departments within the bank. In terms of the economic rational, we show that repeat customers obtain a type of liquidity insurance. In goods times they pay wider spreads than new customers, while in bad times they receive tighter spreads. Finally, we shed light on the role of salespeople in investment banks. We show that customers who are matched with powerful salespeople obtain even tighter spreads in bad times and pay a relatively smaller liquidity insurance premium in good times.The Social Welfare of Marketplace Lending: Evidence from Natural Disasters
Abstract
Using natural disasters as exogenous shocks to the peer-to-peer (P2P) loan market, we document a local increase in loan demand post-disaster. Interest rates and delinquencies from loans approved during this demand shock are similar to pre-event levels. Loans allocated prior to a disaster are more likely to suffer delinquency over the life of the loan, but loans granted a hardship accommodation delay of payment reduce the likelihood of future delinquency providing relief to borrowers and reduced delinquency costs to investors. Contrary to regulatory concerns that P2P lending is predatory, our results suggest they provide positive social welfare benefits.The Undrawn Credit Line Premium
Abstract
Public firms in the United States intensively use bank credit lines for liquidity management,with undrawn credit lines representing around 13% of total assets. We study the
relationship between corporate undrawn credit line holding and expected returns in the
cross-section. Intriguingly, we find that, firms that hold more undrawn credit lines earn
on average 3.88% ? 5.74% higher returns than firms with less undrawn credit lines. We
propose a novel risk-based explanation that centers around the endogenous nature of undrawn
credit line holding and credit line revocations: given holding undrawn credit lines
is costly, firms with stronger liquidity needs tend to hold more, but they are also more
venerable to credit line revocations, through which more undrawn credit line holding increases
their exposure to aggregate shocks and makes their dividend streams and returns
co-vary more with aggregate states. We explicitly model the key features of credit line
contracts in the production-based asset pricing framework to quantify the novel mechanism.
The role of Credit Lines in funding takeovers
Abstract
It is well-known that bidders fund mergers and acquisitions (M&A) with a combination of cash and stock, and that the method of payment is systematically related to merger-induced abnormal returns and takeover premia. Despite this, relatively little is known about how firms procure the cash used as payment in takeovers. Possible sources of this cash component include the drawdown of internal funds (retained earnings), sales of financial instruments (bond and/or equity offerings), and other debt financing. In this paper, I provide novel evidence on the role of credit lines in providing the cash component.Studying whether (and how) credit lines are used to fund M&A transactions is challenging since verifying the actual sources of cash in M&A compensation packages is often difficult. To overcome this obstacle, I construct a comprehensive database of 1,393 all-cash and hybrid takeover bids with information on the intensity of different sources of the cash component and details on credit line loan contracts from 1994 through 2020. I identify such sources by hand-collecting data from bidders' Securities Exchange Commission (SEC) filings, press releases, and business news. These deal-level data enable me to examine the decision to use credit lines and the link between financing and investment decisions.
My main findings are summarized as follows. The conventional view in the literature on corporate funding is that credit lines are used primarily to fund short-term liquidity needs. A surprising finding of this paper is the extensive use of credit lines to fund the cash component in takeover bids. As I also find that firms refund the credit lines shortly after the takeover, the credit lines effectively serve as bridge loans. I argue that this ability of bridge loans implies that the potential acquirer can move quickly on a surprising takeover opportunity. Consistent with this argument, I find that the market reaction to the takeover bid is higher when funded with credit lines, but only in the subsample where the firm simultaneously has negotiated credit lines with the bank. In addition, the expected quality of the takeover opportunity (measured by total synergy gains) is higher in those ”certified” transactions.
Toxic Emissions and Corporate Green Innovation
Abstract
This paper examines the relationship between firms’ toxic emissions and green innovation. Consistent with our main hypothesis, which hinges upon regulatory burden and environmental awareness, we show that high-emission companies produce more green patents of higher quality and value than low-emission firms. High-pollution firms appear to bring meaningful change in their green credentials by generating more environmental related green patents using explorative innovation strategies. We exploit the BP Deepwater Horizon oil spill and the election of President Trump as sources of quasi-exogenous variation to alleviate endogeneity concerns. We also find that environmental related green patents mitigate future toxic air releases.Turbulent Business Cycles
Abstract
Recessions are associated with sharp increases in turbulence that reshuffle firms' productivity rankings. To study the business cycle implications of turbulence shocks, we use Compustat data to construct a measure of turbulence based on the (inverse of) Spearman correlations of firms' productivity rankings between adjacent years. We document evidence that turbulence rises in recessions, reallocating labor and capital from high- to low-productivity firms and reducing aggregate TFP and the stock market value of firms. A real business cycle model with heterogeneous firms and financial frictions can generate the observed macroeconomic and reallocation effects of turbulence. In the model, increased turbulence makes high-productivity firms less likely to remain productive, reducing their expected equity values and tightening their borrowing constraints relative to low-productivity firms. Thus, labor and capital are reallocated to low-productivity firms, reducing aggregate TFP and generating a recession with synchronized declines in aggregate output, consumption, investment, and labor hours, in line with empirical evidence.Uncovering the Hidden Profit: How the Fintech Platform Optimizes its Profit by Strategic Information Releasing?
Abstract
In this paper, we illustrate a phenomenon in which Prosper displays roughly 40% of all loans during the first minute of each releasing hour and charges much higher fees than loans in other minutes after controlling for loan characteristics and numerous fixed effects. Our three identification tests produce a consistent argument that Prosper intentionally lists loans with higher fees in the first minute to maximize its profit. Moreover, the results are more significant for loans with higher funding probability, such as those with small amounts, short terms, and high credit scores. Finally, we examine the consequence of this deliberate loan listing action and find that borrowers with loans in the first minute are less willing to request another loan through the platform.What Drives Beliefs about Climate Risks? Evidence from Financial Analysts
Abstract
This paper aims to understand how beliefs about climate physical risks (risks of weather events) are formed and how these beliefs affect financial forecasts. I start by developing the first conceptual framework of belief formation about climate risks along the lines of the Experience-Based Learning model of Malmendier and Nagel, 2011. To micro-fund the drivers of climate beliefs, I construct a novel dataset with geolocalized salient natural disasters and equity analysts in 29 different US states covering 6,846 firms from 1999 to 2020. Using a staggered differences-in-difference methodology, I study variations in analysts’ earnings forecasts after experiencing an exogenous weather shock. In line with previous studies, my finding suggests that analysts, after experiencing a salient weather shock, have lower forecast bias and error. I find that analysts with high ex-ante performance update their forecasts only for firms with high climate physical risks. Contrarily, low-performance analysts become more pessimistic about all firms, disregarding firms' climate exposure. The results suggest that high-performance analysts acquire new information from experiencing salient weather events, while low-performance analysts are affected by availability heuristics.What Drives Stock Prices along Business Cycles?
Abstract
This paper applies a Bayesian break method to studying the empirical time-varying relation between stock price ratios and subjective expectations across the market and 30 industry portfolios monthly from 1976 to 2020. Cash flow expectations unconditionally explain 80% of price variations since 2000 but their role is concentrated during recessions, especially among the hardest-hit industries such as Telecommunications during the Dot-com Bubble, Financials during the Great Recession, and Healthcare during the Covid-19 pandemic. Concurrently, discount rates explain the remaining 20% yet their portion rises above 50% during the expansionary 2010s. Further tests show that cash flow expectations matter more under financial uncertainty. Inflation expectations, while accounting for 60% of price fluctuations in the high inflationary environment before 2000, play a negligible role thereafter.JEL Classifications
- G0 - General