Research articles for the 2020-05-14
arXiv
We investigate the optimal reinsurance problem under the criterion of maximizing the expected utility of terminal wealth when the insurance company has restricted information on the loss process. We propose a risk model with claim arrival intensity and claim sizes distribution affected by an unobservable environmental stochastic factor. By filtering techniques (with marked point process observations), we reduce the original problem to an equivalent stochastic control problem under full information. Since the classical Hamilton-Jacobi-Bellman approach does not apply, due to the infinite dimensionality of the filter, we choose an alternative approach based on Backward Stochastic Differential Equations (BSDEs). Precisely, we characterize the value process and the optimal reinsurance strategy in terms of the unique solution to a BSDE driven by a marked point process.
arXiv
Assume that an agent models a financial asset through a measure Q with the goal to price / hedge some derivative or optimize some expected utility. Even if the model Q is chosen in the most skilful and sophisticated way, she is left with the possibility that Q does not provide an "exact" description of reality. This leads us to the following question: will the hedge still be somewhat meaningful for models in the proximity of Q?
If we measure proximity with the usual Wasserstein distance (say), the answer is NO. Models which are similar w.r.t. Wasserstein distance may provide dramatically different information on which to base a hedging strategy.
Remarkably, this can be overcome by considering a suitable "adapted" version of the Wasserstein distance which takes the temporal structure of pricing models into account. This adapted Wasserstein distance is most closely related to the nested distance as pioneered by Pflug and Pichler \cite{Pf09,PfPi12,PfPi14}. It allows us to establish Lipschitz properties of hedging strategies for semimartingale models in discrete and continuous time. Notably, these abstract results are sharp already for Brownian motion and European call options.
SSRN
This study introduces a novel framework for building company bankruptcy models and a methodology for assessing the vulnerability of industrial economic activities. We consider the identification of bankruptcy as a classification problem and assume that bankruptcy criteria differ across industries. We build highly accurate industry bankruptcy models by constructing separate models for each industry. We also propose a method of analyzing the vulnerability of industrial economic activities in various countries and industries using new indicators we call "expected potential loss," which we obtain using the predicted likelihood of bankruptcy and company information.
SSRN
We find evidence of tax‐driven strategic allocation of debt and asset risk across group entities of European banks. We evaluate the effects that establishing tax neutrality between debt and equity finance has on systemic risk, and show that the degree of coordination in implementing the hypothetical tax reform matters. In particular, a coordinated elimination of the tax advantage of debt would significantly reduce systemic losses in the event of a severe banking crisis. By contrast, uncoordinated tax reforms are not equally beneficial precisely because national tax policies generate spillovers through cross‐border bank activities.
SSRN
By stepping between bilateral counterparties, a central counterparty (CCP) transforms credit exposure. CCPs generally improve financial stability. Nevertheless, large CCPs are by nature concentrated and interconnected with major global banks. Moreover, although they mitigate credit risk, CCPs create liquidity risks, because they rely on participants to provide cash. Such requirements increase with both market volatility and default; consequently, CCP liquidity needs are inherently procyclical. This procyclicality makes it more challenging to assess CCP resilience in the rare event that one or more large financial institutions default. Liquidity-focused macroprudential stress tests could help to assess and manage this systemic liquidity risk.
SSRN
We analyze the transmission of changes in commodity prices to bank lending in a large sample of developing countries. A bank‐level analysis shows that a fall in commodity net export prices is associated with a reduction of bank lending, particularly for commodity exporters and during episodes of terms‐of‐trade decline. We complement this analysis with loan‐level data from a credit register, which allows us to identify the effect of a commodity price shock on the supply of credit, controlling for unobserved factors that could drive borrowers' credit demand. Results show that banks with relatively lower deposits and poor asset quality transmit the changes in commodity prices to lending more aggressively.
SSRN
We employ recent Survey of Consumer Finances (SCF) microdata from the US to analyze the impacts of confidence in one’s own financial knowledge, confidence in the economy, and objective financial literacy on investment in risky financial assets (equity and bonds) on both the extensive and intensive margins. Controlling for a rich set of covariates including risk aversion, we find that objective financial literacy is positively related to investment in risky assets as well as debt securities. Moreover, confidence in own financial skills additionally increases the probability of holding risky assets and bonds. While these relationships are rather robust for the extensive margin, they break down with regard to the conditional share of financial wealth in risky assets of those who actually hold them. The relevance of financial literacy as well as confidence varies considerably with the distribution of wealth as well as across several socio-economic dimensions such as age, education and race.
arXiv
In this paper, we propose a new class of optimization problems, which maximize the terminal wealth and accumulated consumption utility subject to a mean variance criterion controlling the final risk of the portfolio. The multiple-objective optimization problem is firstly transformed into a single-objective one by introducing the concept of overall "happiness" of an investor defined as the aggregation of the terminal wealth under the mean-variance criterion and the expected accumulated utility, and then solved under a game theoretic framework. We have managed to maintain analytical tractability; the closed-form solutions found for a set of special utility functions enable us to discuss some interesting optimal investment strategies that have not been revealed before in literature.
arXiv
In this study, we make use of empirically observed occupational stratification patterns, in order to identify the relationship between education and social mobility of individuals - the latter is approximated by the social distance of an individual's occupation from his/her household's traditional niche occupation. Our study draws upon a novel occupational network construction proposed in Lambert et.al (2018), with slight adjustments, to empirically identify social stratification patterns using cross sectional household surveys available in the Indian context. We use IHDS-2 data-set for the purpose of our study.
arXiv
Many online news publishers finance their websites by displaying ads alongside content. Yet, remarkably little is known about how exposure to such ads impacts users' news consumption. We examine this question using 3.1 million anonymized browsing sessions from 79,856 users on a news website and the quasi-random variation created by ad blocker adoption. We find that seeing ads has a robust negative effect on the quantity and variety of news consumption: Users who adopt ad blockers subsequently consume 20% more news articles corresponding to 10% more categories. The effect persists over time and is largely driven by consumption of "hard" news. The effect is primarily attributable to a learning mechanism, wherein users gain positive experience with the ad-free site; a cognitive mechanism, wherein ads impede processing of content, also plays a role. Our findings open an important discussion on the suitability of advertising as a monetization model for valuable digital content.
SSRN
It poses a challenge to understand why nurses working with elderly people living in care homes or being in ambulant care have not yet been tested for the coronavirus, whereas teams in the German top football leagues have been tested before going back to practice again.How can this riddle be solved? For me, there are two possible explanations: Either the German government acts rationally only in certain cases or there are other things in the interest of the German government than just the number of headcount of lives. In this working paper, I argue for the latter and try to prove it.
SSRN
We test for racial discrimination in the prices charged by mortgage lenders. We construct a unique dataset where we observe all three dimensions of a mortgage's price: the interest rate, discount points, and fees. While we find statistically significant gaps by race and ethnicity in interest rates, these gaps are offset by differences in discount points. We trace out point-rate schedules and show that minorities and whites face identical schedules, but sort to different locations on the schedule. Such sorting may reflect systematic differences in liquidity or preferences. Finally, we find no differences in total fees by race or ethnicity.
SSRN
We show that FED policy announcements lead to a significant increase in international comovements in the cross-section of equity and in particular sovereign CDS markets. The relaxation of unconventionary monetary policies is felt strongly by emerging markets, and by countries that are open to the trading of goods and flows, even in the presence of floating exchange rates. It also impacts closed economies whose currencies are pegged to the dollar. This evidence is consistent with recent theories of a global financial cycle and the pricing of a FED’s put. In contrast, ECB announcements hardly affect comovements, even in the Eurozone.
arXiv
This paper proposes and motivates a dynamical model of the Chinese stock market based on a linear regression in a dual state space connected to the original state space of correlations between the volume-at-price buckets by a Fourier transform. We apply our model to the price migration of executed orders by the Chinese brokerages in 2009-2010. Regulatory brokerage tapes were used to conduct a natural experiment assuming that tapes correspond to randomly assigned, informed and uninformed traders. Our analysis demonstrated that customers' orders were tightly correlated--in a highly nonlinear sense of the neural networks--with the Chinese market sentiment index, significantly correlated with the stock returns and exhibited no correlation with the bellwether bond of the Bank of China. We did not notice any spike of illiquidity transmitting from the US Flash Crash in May 2010 to trading in China.
SSRN
Spanish abstract: La valoración de los bienes raÃces con fines de garantÃa hipotecaria es un elemento clave para la estabilidad financiera, como se puso de manifiesto a raÃz de la crisis de 2008. En este contexto, el presente documento se centra en la descripción del sistema de tasación español de bienes inmuebles para garantÃa hipotecaria y en su comparación con los sistemas empleados en otros paÃses de nuestro entorno económico. Cabe señalar que la variedad de modelos de valoración es amplia y depende, entre otros aspectos, de la importancia relativa del sector inmobiliario en cada paÃs. AsÃ, en unos paÃses hay mecanismos de autorregulación del sector, ya que la profesión no está regulada y no existen prescripciones de uso de una metodologÃa concreta, ni estandarización de los modelos de informe, ni certificación de los tasadores. Por el contrario, en otros paÃses (entre los que se encuentra España) se han establecido normas que recogen los aspectos metodológicos, de modelo de informe y de homologación de sociedades de tasación, y existe una autoridad nacional supervisora.English abstract: The 2008 crisis evidenced that real-estate appraisal for mortgage lending is key to financial stability. This paper focuses on describing the Spanish mortgage-lending appraisal system and comparing it with those used in other advanced economies. A wide range of appraisal models is used. The model used depends, inter alia, on the relative importance of the real-estate sector in each country. For instance, there are countries in which the appraisal profession is unregulated and there are no rules on the use of a specific methodology, the model reports are not standardised, the appraisers are not certified and the sector is self-regulated. Others, by contrast, Spain included, have drawn up standards establishing the valuation methodology, the model appraisal report, and the requirements for incorporation and certification of appraisal companies. These countries also have a national supervisory authority.Note: Downloadable document is in Spanish.
SSRN
We study the impact of emotions on real‐world decisions made by loan officers by analyzing the loan conditions of loans granted immediately after a bank branch robbery. We find significant differences between the conditions of loans granted after a robbery and changes in loan conditions that occur contemporaneously at unaffected branches. In general, loan officers seem to adopt so‐called avoidance behavior. In accordance with the literature on posttraumatic stress, their avoidance behavior is halved within 2 weeks following the robbery and the effect further varies depending on the presence, or absence, of a firearm during the robbery.
SSRN
In this paper, we compare and contrast financial data science with econometrics and conclude that the former is inevitably interdisciplinary due to the numerous skill-sets needed within a competitive research team. The latter, in contrast, is firmly rooted in economics. Both areas are highly complementary, as they share an equivalent process with the former’s intellectual point of departure being statistical inference and the latter’s being the data sets themselves. Two challenges arise, however, from the age of big data. First, the ever increasing computational power allows researchers to experiment with an extremely large number of generated test subjects and leads to the challenge of p-hacking. Second, the extremely large number of observations available in big data sets provide levels of statistical power at which common statistical significance levels are barely a challenge. We argue that the former challenge can be mitigated through adjustments for multiple hypothesis testing where appropriate. However, it can only truly be addressed via a strong focus on the integrity of the research process and the researchers themselves, with pre-registration and actual out-of-sample periods being the best technical though in themselves potentially insufficient tools. The latter challenge can be addressed in two ways. First, researchers can simply use more stringent statistical significance levels such as 0.1%, 0.5% and 1% instead of 1%, 5% and 10%, respectively. Second, and more importantly, researchers can use additional criteria such as economic significance, economic relevance and statistical relevance to assess the robustness of statistically significant coefficients. Especially statistical relevance seems crucial in the age of big data, as it appears not impossible for an individual coefficient to be considered statistically significant when its actual statistical relevance (i.e. incremental explanatory power) is extremely small.
SSRN
Tsionas has offered a more revisionist approach to the empirics of the nexus between financial development and economic growth following our paper entitled 'Financial development and economic growth nexus: A revisionist approach'. In the current note, we engage Tsionas' approach in tandem with our original finance–growth nexus review. We concur with Tsionas' approach and reiterate that the debate on the relationship between financial development and economic growth remains a complex terrain both on the theoretical and empirical fronts.
SSRN
We quantify financial returns to backers in reward-based crowdfunding projects on Kick-starter and show that such investments provide profitable opportunities. The average unconditional annualized return is 11.5% and the average return on successful projects is 30%.Hence, backing money near the end of a campaign is a profitable strategy. The most attractive is the Design category, where successful projects yield 73%, on average. Short-term projects are more profitable than long-term ones. Therefore, financial return is an important type of extrinsic motivation in crowdfunding, which has generally been neglected in academic literature.
SSRN
We examine various factors that influence the effects of government‐subsidized research and development (R&D) programs on firm productivity. Based on a panel dataset of Chinese firms, we find the effects of the Innovation Fund for Small and Medium Technology Based Firms (Innofund) are dynamic over time and are heterogeneous depending on funding forms and the level of marketization and economic development across regions. In general, Innfound has significant and positive effects on firm productivity in both the short and long run. However, the short‐term effects of Innofund are stronger than the long‐term ones. Additionally, the positive effects of Innofund are stronger for firms backed by interest‐free bank loans than those supported by appropriation. Meanwhile, Innofund has stronger positive effects in provinces that are less market‐oriented or less developed economically. Finally, the short‐term effects of Innofund stay stronger than the long‐term ones even after we control the funding forms and the market conditions across regions. Identification and selection concerns are addressed through the propensity score matching approach and two‐stage estimation.
SSRN
Purpose â€" This study investigates the impact of corporate governance mechanisms on financial risk reporting in the UK. Design/methodology/approach â€" The study uses a panel data of 50 non-financial firms belonging to ten industrial sectors listed on the London Stock Exchange in the period 2011-2015. Multivariate regression techniques are used to examine the relationships. Additionally, to alleviate the concern of potential endogeneity, we use two-stage least squares and fixed effect estimators. Findings â€" The findings of this study reveal that corporate governance has a significant influence on financial risk disclosure. Specifically, we find that block ownership and board gender diversity have a positive effect on the level of corporate financial risk disclosure. While, there is no significant relationship between board size and corporate financial risk disclosure. Originality/value â€" This study adds to the emerging body of literature on corporate governanceâ€"risk disclosure relationship in UK context using content analysis. The study also highlights that gender diversity enhances financial risk disclosure.
SSRN
We study neural networks as nonparametric estimation tools for the hedging of options. To this end, we design a network, named HedgeNet, that directly outputs a hedging strategy. This network is trained to minimise the hedging error instead of the pricing error. Applied to end-of-day and tick prices of S&P 500 and Euro Stoxx 50 options, the network is able to reduce the mean squared hedging error of the Black-Scholes benchmark significantly. We illustrate, however, that a similar benefit arises by simple linear regressions that incorporate the leverage effect. Finally, we show how a faulty training/test data split, possibly along with an additional ‘tagging’ of data, leads to a significant overestimation of the outperformance of neural networks.
arXiv
COVID-19 has put a severe dent on the global economy and Indian Economy. International Monetary Fund has projected 1.9 percent for India. However, we believe that due to extended lockdown, the output in the first quarter is almost wiped out. The situation may improve in the second quarter onwards. Nevertheless, due to demand and supply constraints, input constraints and disruption in the supply chain, except agriculture, no other sector would be able to achieve full capacity of production in 2020-21. The signals from power consumption, GST collection, contraction in the core sectors hint towards a slump in the total output production in 2020-21. We derive the quarterly GVA for 2020-21 by using certain assumptions on the capacity utilisation in different sectors and using the quarterly data of 2019-20. We provide quarterly estimates of Gross Value Addition for 2020-21 under two scenarios. We have also estimated the fourth quarter output for 2019-20 under certain assumptions. We estimate
SSRN
Indian gold derivatives market has a Century old history with the inception of the famous Bombay Bullion Association (BBA) in 1919 though subjected to ban subsequently similar to other commodities. Following their revival in the early 2000s, gold futures volumes have witnessed a healthy growth of about 115% on average during the first decade from 2003 to 2012 reaching an average daily turnover of more than Rs.12 thousand crore but fell steeply to about Rs. 4.6 thousand crore in 2014 with the levy of Commodity Transaction Tax (CTT) in July 2013 causing a sharp increase in impact cost of futures trading. Although gold futures volumes have recovered notably to around Rs. 5.7 thousand crore during 2019, they remained well below the pre-CTT era. Indian futures market is characterized by relatively high delivery ratio to volumes at about 0.35% on average during 2011 to 2019. The aggregate deliveries of gold on MCX accredited warehouses stood at 114 tonnes till December 2019 with a record delivery of about 5.16 tonnes of gold in the month of August 2019. In view of these significant deliveries in gold futures, an attempt is made to understand trading trends with particular reference to pattern of gold stocks as well as deliveries in futures market.
arXiv
India like many other developing countries is characterized by huge proportion of informal labour in its total workforce. The percentage of Informal Workforce is close to 92% of total as computed from NSSO 68th round on Employment and Unemployment, 2011-12. There are many traditional and geographical factors which might have been responsible for this staggering proportion of Informality in our country. As a part of this study, we focus mainly on finding out how Informality varies with Region, Sector, Gender, Social Group, and Working Age Groups. Further we look at how Total Inequality is contributed by Formal and Informal Labour, and how much do occupations/industries contribute to inequality within each of formal and informal labour groups separately. For the purposes of our study we use NSSO rounds 61 (2004-05) and 68 (2011-12) on employment and unemployment. The study intends to look at an overall picture of Informality, and based on the data highlight any inferences which are visible from the data.
SSRN
With the onset of the financial crisis, disentangling the effects of loan demand and supply in contemporary banking research has become vital for a proper assessment of supply‐related banking shocks. These shocks may negatively affect the real economy through many channels, such as the lending channel of monetary policy transmission, the bank risk‐taking channel or the evaluation of macroprudential policy efficiency. All these rely on separating the two lending components. Empirical identification has largely relied on the use of demand‐related fixed effects, which has also been applied in several analyses within this symposium.
SSRN
Using the data of 20 major Organization for Economic Co‐operation and Development countries over time, this article documents new evidence on real equity and real currency prices: higher real returns in the home equity market relative to its foreign counterparts are generally associated with real home currency depreciation at monthly frequency, but this negative correlation breaks down or even reverses during times of relatively higher aggregate economic uncertainty or volatility. This article also argues that a long‐run risks‐type model with time‐varying liquidity risk in stock markets can provide one plausible explanation for the time‐varying correlation structure.
SSRN
Using credit-registry data for Spain and Peru, we document that four main types of commercial creditâ€"asset-based loans, cash-flow loans, trade finance and leasingâ€"are easily identifiable and represent the bulk of corporate credit. We show that credit dynamics and bank lending channels vary across these loan types. Moreover, aggregate credit supply shocks previously identified in the literature appear to be driven by individual loan types. The effects of monetary policy and the effects of the financial crisis propagating through banks’ balance sheets are primarily driven by cash-flow loans, whereas asset-based credit is mostly insensitive to these types of effects.
SSRN
We investigate the use of machine learning (ML) and other robust-estimation techniques in event studies conducted on single securities for the purpose of securities litigation. Single-firm event studies are widely used in civil litigation, with billions of dollars in settlements hinging on the outcome of the exercise. We find that regularization (equivalently, penalized estimation) can yield noticeable improvements in both the variance of event-date abnormal returns and significance-test power. Thus we believe that there is a role for ML methods in event studies used in securities litigation. At the same time, we find that ML-induced performance improvements are smaller than those based on other good practices. Most important are (i) the use of a peer index based on returns for firms in similar industries (how this is computed appears to be less important than that some version be included), and (ii) for significance testing, using the SQ test proposed in Gelbach, Helland, and Klick (2013), because it is robust to the considerable non-normality present in abnormal returns.
SSRN
Economic theory establishes that greater transparency about an agent's action increases the agent's career concerns and short-termism. We use a difference-in-differences design around a regulatory change that increased the transparency of mutual fund portfolio strategies, and we examine the effect of mutual funds' short-termism on corporate share repurchases. We find that firms with greater ownership by affected mutual funds increase share repurchases following the regulatory change. Consistent with theory, this effect is greater when mutual fund managers face high career concerns. Furthermore, we implement a new simulation model to account for multiple hypotheses testing when reusing natural experiments. Overall, we document one important driver of share repurchases: the short-termism of actively managed mutual funds.
SSRN
Using data from a university, we analyze a policy designed to increase employer‐sponsored life insurance. The university increased basic life insurance holdings, which nudged employees with supplemental coverage to have more life insurance. In large part due to inertia, the nudge increased life insurance holdings one‐for‐one for those who could have undone it. Additionally, we find that expanding coverage options significantly increased total life insurance holdings for new hires who were not subject to inertia. These policy changes reduced uninsured vulnerabilities for two‐thirds of employees. Our findings have important policy implications for addressing widespread disparities in life insurance coverage.
SSRN
We examine how the numeracy level of employees influences their on‐the‐job performance. Based on an administrative dataset of a retail bank we relate the performance of loan officers in a standardized math test to the accuracy of their credit assessments of small business borrowers. We find that loan officers with a high level of numeracy are more accurate in assessing the credit risk of borrowers. The effect is most pronounced during the precrisis credit boom period when it is arguably more difficult to pick out risky borrowers.
arXiv
Social mobility captures the extent to which socio-economic status of children, is independent of status of their respective parents. In order to measure social mobility, most widely used indicators of socio-economic status are income, education and occupation. While social mobility measurement based on income is less contested, data availability in Indian context limits us to observing mobility patterns along the dimensions of either education or occupation. In this study we observe social mobility patterns for different social groups along these two main dimensions, and find that while upward and downward mobility prospects in education for SCs/STs is somewhat improving in the recent times, occupational mobility patterns are rather worrisome. These results motivate the need for reconciling disparate trends along education and occupation, in order to get a more comprehensive picture of social mobility in the country.
SSRN
This technical note describes the Forward-Looking Analysis of Risk Events (FLARE) model, which is a top-down model that helps assess how well the banking system is positioned to weather exogenous macroeconomic shocks. FLARE estimates banking system capital under varying macroeconomic scenarios, time horizons, and other systemic shocks.
arXiv
We measure the public concern during the outbreak of COVID-19 disease using three data sources from Google Trends (YouTube, Google News, and Google Search). Our findings are three-fold. First, the public concern in Italy is found to be a driver of the concerns in other countries. Second, we document that Google Trends data for Italy better explains the stock index returns of France, Germany, Great Britain, the United States, and Spain with respect to their country-based indicators. Finally, we perform a time-varying analysis and identify that the most severe impacts in the financial markets occur at each step of the Italian lock-down process.
arXiv
In the last years, cryptocurrencies are increasingly popular. Even people who are not experts have started to invest in these securities and nowadays cryptocurrency exchanges process transactions for over 100 billion US dollars per month. However, many cryptocurrencies have low liquidity and therefore they are highly prone to market manipulation schemes. In this paper, we perform an in-depth analysis of pump and dump schemes organized by communities over the Internet. We observe how these communities are organized and how they carry out the fraud. Then, we report on two case studies related to pump and dump groups. Lastly, we introduce an approach to detect the fraud in real time that outperforms the current state of the art, so to help investors stay out of the market when a pump and dump scheme is in action.
SSRN
This study seeks to answer whether it is possible to design an early warning system framework that can signal the risk of fiscal stress in the near future, and what shape such a system should take. To do so, multiple models based on econometric logit and the random forest models are designed and compared. Using a dataset of 20 annual frequency variables pertaining to 43 advanced and emerging countries during 1992-2018, the results confirm the possibility of obtaining an effective model, which correctly predicts 70-80% of fiscal stress events and tranquil periods. The random forest-based early warning model outperforms logit models. While the random forest model is commonly understood to provide lower interpretability than logit models do, this study employs tools that can be used to provide useful information for understanding what is behind the black-box. These tools can provide information on the most important explanatory variables and on the shape of the relationship between these variables and the outcome classification. Thus, the study contributes to the discussion on the usefulness of machine learning methods in economics.
SSRN
We propose a simple model of borrower optimism in competitive lending markets with asymmetric information. Borrowers in our model engage in self-deception to arrive at a belief that optimally trades off the anticipatory utility bene�ts and material costs of optimism. Lenders’ contract design shapes these bene�ts and costs. The model yields three key results. First, the borrower’s motivated cognition increases her material welfare, regardless of whether or not she ends up being optimistic in equilibrium. Our model thus helps explain why wishful thinking is not driven out of markets. Second, in line with empirical evidence, a low cost of lending and a booming economy lead to optimism and the widespread collateralization of loans. Third, equilibrium collateral requirements may be inefficiently high.
SSRN
Previous research using attendance‐based proxies for sentiment bias in sports betting markets confirmed the presence of investor sentiment in these markets. We use data from social media (Facebook "") to proxy for sentiment bias and analyze variation in bookmakers' prices investor sentiment. Based on betting data from seven professional sports leagues in Europe and North America, we find evidence that bookmakers increase prices for bets on teams with relatively more Facebook "," indicating the presence of price‐insensitive investors with sentiment bias. These price changes do not affect informational efficiency in this market.
arXiv
We study various decision problems regarding short-term investments in risky assets whose returns evolve continuously in time. We show that in each problem, all risk-averse decision makers have the same (problem-dependent) ranking over short-term risky assets. Moreover, in each problem, the ranking is represented by the same risk index as in the case of CARA utility agents and normally distributed risky assets.
SSRN
Target-date funds feature asset allocations that become increasingly conservative as investors approach retirement. An important shortcoming of this strategy is that it is suboptimal in terms of capital accumulation, which begs the question of why these funds are so popular. A possible answer is that investors become more risk averse as they age, gradually favoring more downside protection as they approach retirement. The main issue explored in this article is how much more risk averse would investors need to become during their working years to select asset allocations similar to those in target-date funds; the evidence here shows that investors would have to roughly double their risk aversion during the last 25 years of their working period. An intuitive interpretation of this result, based on how much an individual would pay to avoid a gamble, is also discussed.
SSRN
We document the effect on Chinese firms of the Shanghai (Shenzhen)-Hong Kong Stock Connect. The Connect was an important capital account liberalization introduced in the mid-2010s. It created a channel for cross-border equity investments into a selected set of Chinese stocks while China's overall capital controls policy remained in place. Using a difference-in-difference approach, and with careful attention to sample selection issues, we find that mainland Chinese firm-level investment is negatively affected by contractionary U.S. monetary policy shocks and that firms in the Connect are more adversely affected than those outside of it. These effects are economically large, robust, and stronger for firms whose stock return has a higher covariance with the world market return. We also find that firms in the Connect enjoy lower financing costs, invest more, and have higher profitability than unconnected firms. We discuss the implications of our results for the debate on capital controls and independence of Chinese monetary policy.
SSRN
We investigate the impact of peer-to-peer lending on the small business loans originated by US depository institutions that are subject to the Community Reinvestment Act. We present a model where a borrower can choose between a traditional bank and a crowdlending platform and show that the entry of crowdlending can induce a switching effect as well as a credit expansion effect. Using the staggered entry of LendingClub across states between 2009 and 2017, we find that the platform entry reduced the small business loans originated by banks, in particular, in the low- or moderate-income tracts as well as in the distressed middle-income tracts with a high poverty rate. A conservative estimate suggests that the crowdlending entry may have reduced the aggregate lending volume to small businesses.
SSRN
We analyze the demographics of zombie firms and durations of zombie spells as well as their determinants, including an application on public subsidies using firm level population panel data from Finland. Firm-level analysis of firm demographics reveals that zombie-firms, as commonly defined in the literature, are often not truly distressed firms but rather companies with temporarily low revenues relative to interest payments. More importantly, we find that roughly a third of these firms are in fact growing companies and two thirds recover from the zombie status to become healthy firms. We also show that the increase of zombie firms over the past 15 years has mainly been driven by cyclical factors, as opposed to a secular trend. In our policy application on government subsidies to firms, estimation results strongly suggest that subsidy-receiving firms are less likely to die, regardless of the type of subsidy. However, with regard to recovery there is heterogeneity in the effects depending on the type of firm and the type of subsidy received. Thus, we do not find a robust positive association of subsidies with zombie recovery.
SSRN
We apply textual analysis tools to the narratives that accompany Federal Reserve Board economic forecasts to measure the degree of optimism versus pessimism expressed in those narratives. Text sentiment is strongly correlated with the accompanying economic point forecasts, positively for GDP forecasts and negatively for unemployment and inflation forecasts. Moreover, our sentiment measure predicts errors in FRB and private forecasts for GDP growth and unemployment up to four quarters out. Furthermore, stronger sentiment predicts tighter than expected monetary policy and higher future stock returns. Quantile regressions indicate that most of sentiment’s forecasting power arises from signaling downside risks to the economy and stock prices.
SSRN
Based on M&A deals by companies from the biotechnology and pharmaceutical industry, I analyze the role of different types of prior ties between companies. I distinguish related alliances into direct and indirect alliances. Related alliances provide access to more information and can reduce transaction costs. The reduction of such costs can lead to a more successful target selection and a more efficient transaction process of the M&A deal because the time from announcement to completion can be reduced. This effect can be explained by trust-building, better access to private information, and certification through related alliances. However, in contrast to other studies, I do not find statistically significant evidence that supports the hypothesis that alliances increase the post-M&A performance and that alliances are associated with higher announcement returns.
SSRN
We examine the impact of the existence on an explicit deposit insurance (DI) scheme and its design features on bilateral cross‐border deposits (CBD) in a gravity model setting. We find that both the absolute quality of a country's DI and its relative quality vis‐à‐vis other countries' DI generally affect depositor behavior. However, during systemic banking crises, cross‐border depositors primarily seek countries with the best DI schemes. Similarly, during the 2008–2009 great financial crisis, the emergency actions taken by the governments, which supply and maintain these safe havens, have led to substantial relocations of CBD.
SSRN
Treasury securities normally possess unparalleled safety and liquidity and, consequently, carry a money premium. We use recent debt limit impasses, which temporarily increased the riskiness of Treasuries, to investigate the relationship between the money premium, safety, and liquidity. Our results shed light on Treasury market dynamics specifically, and debt more generally. We first establish that a decline in the perceived safety of Treasuries erodes the money premium at all times. Meanwhile, changes in liquidity only affected the money premium during the impasses. Next, we show that Treasury safety and liquidity dynamics are generally consistent with the theory of the information sensitivity of debt.
arXiv
We provide the first nationally representative estimates of sexual minority representation in STEM fields by studying 142,641 men and women in same-sex couples from the 2009-2018 American Community Surveys. These data indicate that men in same-sex couples are 12 percentage points less likely to have completed a bachelor's degree in a STEM field compared to men in different-sex couples; there is no gap observed for women in same-sex couples compared to women in different-sex couples. The STEM gap between men in same-sex and different-sex couples is larger than the STEM gap between white and black men but is smaller than the gender STEM gap. We also document a gap in STEM occupations between men in same-sex and different-sex couples, and we replicate this finding using independently drawn data from the 2013-2018 National Health Interview Surveys. These differences persist after controlling for demographic characteristics, location, and fertility. Our findings further the call for interventions designed at increasing representation of sexual minorities in STEM.
