Research articles for the 2021-02-11
SSRN
This study exploits spatial and temporal variation in natural disasters in the United States via a generalized differences-in-differences approach to identify the impact of natural disasters on householdsâ food-at-home (FAH) spending and quality from 2005 to 2016. We use two datasets: (i) the Storm Events Database to identify U.S. counties that experience severe economic losses as a result of droughts, floods, hurricanes, and tornadoes, and (ii) the Nielsen Consumer Panel Data for grocery data. We find that only floods and hurricanes affect FAH spending. Floods (Hurricanes) have a persistent (immediate) effect on FAH spending. On average, highly damaging floods (hurricanes) decrease 15-day FAH spending by about $2 ($7) in 90 days (30 days) after the events. The FAH quality effect of the four natural disasters is either inconsequential or nonexistent. We provide indirect evidence that the FAH spending effect of natural disasters works through both income and price channels. We also find that hurricanes have an anticipation effect on total grocery spending which starts 15 days before the disaster date. Our results are robust to an alternative specification that controls for county-specific linear trends. We add to the growing body of literature on the effects of natural disasters on household finances and financial decisions. Our findings could be of particular interest to post-disaster relief organizations and their programs.
arXiv
Scoring rules aggregate individual rankings by assigning some points to each position in each ranking such that the total sum of points provides the overall ranking of the alternatives. They are widely used in sports competitions consisting of multiple contests. We study the tradeoff between two risks in this setting: (1) the threat of early clinch when the title has been clinched before the last contest(s) of the competition take place; (2) the danger of winning the competition without finishing first in any contest. In particular, four historical points scoring systems of the Formula One World Championship are compared with the family of geometric scoring rules that have favourable axiomatic properties. The formers are found to be competitive or even better. The current scheme seems to be a reasonable compromise in optimising the above goals. Our results shed more light on the evolution of the Formula One points scoring systems and contribute to the issue of choosing the set of point values.
arXiv
The paper introduces a very simple and fast computation method for high-dimensional integrals to solve high-dimensional Kolmogorov partial differential equations (PDEs). The new machine learning-based method is obtained by solving a stochastic weighted minimization with stochastic gradient descent which is inspired by a high-order weak approximation scheme for stochastic differential equations (SDEs) with Malliavin weights. Then solutions to high-dimensional Kolmogorov PDEs or expectations of functionals of solutions to high-dimensional SDEs are accurately approximated without suffering from the curse of dimensionality. Numerical examples for PDEs and SDEs up to 100 dimensions are shown by using second and third-order discretization schemes in order to demonstrate the effectiveness of our method.
SSRN
Investors are said to "abhor uncertainty", but if there were no uncertainty they could earn only the risk-free rate. A fundamental result in the analytical accounting literature shows that investors buying into a CARA-normal CAPM market pay lower asset prices, earn higher expected returns, and obtain higher expected utility, when the market payoff has higher variance. New investors obtain similar welfare gains from risk under a log/power utility CAPM. These results do not imply that investors "abhor information". To realize investors' ex ante expectations, the subjective probability distributions representing market expectations must be accurate. Greater payoff risk can add to investors' expected utility, but higher ex post (realized) utility comes from better information and more accurate ex ante expectations. An important implication for accounting is that greater disclosure can have the simultaneous effects of (i) exposing more accurately firms' payoff uncertainty and thereby increasing new investors' expected utility, and (ii) improving market estimates of firms' payoff parameters (means, variances, covariances), thereby giving investors a better chance of realizing their expectations. Paradoxically, better information can be valuable to new investors by exposing more accurately the uncertainty in firms' business operations and results. New investors maximizing expected utility typically want both more uncertainty and better information.
SSRN
We test for the causal impact of analyst coverage on corporate risk-taking in the property and casualty insurance sector, using the exogenous change in analyst coverage introduced by broker closures and mergers. We find that a decrease in analyst coverage promotes an increase in insurersâ risk-taking, which is mainly driven by insurers with smaller initial analyst coverage and those operating in an environment of lower product market competition. We also show that the decrease in analyst coverage causes more risky investment behaviors, more risky underwriting, and less conservative reserving practice.
SSRN
In this paper we explore some of the benefits of using the finite-state Markov chain approximation (MCA) method of Kushner and Dupuis (2001) to solve continuous-time optimal control problems. We first show that the implicit finite-difference scheme of Achdou et al. (2017) amounts to a limiting form of the MCA method for a certain choice of approximating chains and policy function iteration for the resulting system of equations. We then illustrate the benefits of departing from policy function iteration by showing that using variations of modified policy function iteration to solve income fluctuation problems in two and three dimensions can lead to an increase in the speed of convergence of more than an order of magnitude. We then show that the MCA method is also well-suited to solving portfolio problems with highly correlated state variables, a setting that commonly occurs within general equilibrium models with financial frictions and for which it is difficult to construct monotone (and hence convergent) finite-difference schemes.
arXiv
I analyze Osaka factory worker households in the early 1920s, whether idiosyncratic income shocks were shared efficiently, and which consumption categories were robust to shocks. While the null hypothesis of full risk-sharing of total expenditures was rejected, factory workers maintained their households, in that they paid for essential expenditures (rent, utilities, and commutation) during economic hardship. Additionally, children's education expenditures were possibly robust to idiosyncratic income shocks. The results suggest that temporary income is statistically significantly increased if disposable income drops due to idiosyncratic shocks. Historical documents suggest microfinancial lending and saving institutions helped mitigate risk-based vulnerabilities.
arXiv
We investigate the allegation that legacy U.S. airlines communicated via earnings calls to coordinate with other legacy airlines in offering fewer seats on competitive routes. To this end, we first use text analytics to build a novel dataset on communication among airlines about their capacity choices. Estimates from our preferred specification show that the number of offered seats is 2% lower when all legacy airlines in a market discuss the concept of "capacity discipline." We verify that this reduction materializes only when legacy airlines communicate concurrently, and that it cannot be explained by other possibilities, including that airlines are simply announcing to investors their unilateral plans to reduce capacity, and then following through on those announcements.
SSRN
We propose an averaging rule that combines established minimum-variance strategies to minimize the expected out-of-sample variance. Our rule overcomes the problem of selecting the âbestâ strategy ex-ante and diversifies remaining estimation errors of the single strategies included in the averaging. Extensive simulations show that the contributions of estimation errors to the out-of-sample variances are uncorrelated between the considered strategies. This implies that averaging over multiple strategies oËers sizable diversification benefits. Our rule leverages these benefits and compares favorably to eleven strategies in terms of out-of-sample variance on both simulated and empirical data sets. The Sharpe ratio is across all data sets at least 25% higher than for the 1/N portfolio.
SSRN
Anti-tax loss trafficking rules disallow the use of loss carryforwards after a change in ownership or activity (such as significant changes in turnover, employment, or the product portfolio). This restriction could threaten accumulated loss carryforwards of start-ups. Accounting for the in-creased risk and reduced return on their investment, VC investors could reduce their funding. I analyze whether the venture capital (VC) funding of start-ups in Europe is affected by these regulations. I base my empirical analysis on several case studies and a panel analysis covering VC-funded companies in the EU28 Member States from 1999 to 2014. My findings suggest that strict anti-tax loss trafficking rules indeed impair VC funding. Especially more mature companies and companies in high-tech industries are affected.
SSRN
Cognitive biases are pervasive, and are known to negatively impact individuals' investment behavior and financial outcomes. However, it is an open question whether cognitive biases are attenuated or amplified when teams, rather than individuals, manage investment decisions. To address this question, we use the mutual fund industry as a laboratory. We focus on how return extrapolation, a cognitive bias that has received considerable attention in recent literature, influences the trading behavior of a team-managed fund compared to the behavior of the individual team members when they manage a fund alone. Using an IV methodology, we show that teams heavily attenuate the influence of return extrapolation on funds' trading and investment performance. Our results shed new light on the role of teams for bias correction, and highlight a potential benefit of team-based asset management.
SSRN
Chordia and Miao (2020) provide evidence that low-latency trading (LLT) improves the long-term informational efficiency of stock prices. This discussion raises two primary concerns with their analysis. First, the mechanism through which LLT enhances long-term efficiency is unclear. Second, CM's measure of LLT trading activity is correlated with non-LLT trading activity, which may in turn cause the documented improvements in efficiency. We close by proposing an alternative explanationâ"changes in market microstructure have had a bifurcated impact on liquidity, enhancing efficiency for large and liquid stocks, but not for small and illiquid stocks.
SSRN
We study the dynamics of cash-and-carry arbitrage using the U.S. crude oil market. Sizable arbitrage-related inventory movements occur at the NYMEX futures contract delivery point but not at other storage locations where, instead, operational factors explain most inventory changes. We add to the Theory of Storage literature by introducing two new features. First, due to arbitrageurs contracting ahead, inventories respond to not only contemporaneous but also lagged futures spreads. Second, storage capacity limits can impede cash-and-carry arbitrage, leading to the persistence of unexploited arbitrage opportunities. Our findings suggest that arbitrage-induced inventory movements are, on average, price stabilizing.
arXiv
The COVID-19 pandemic has affected travel behaviors and transportation system operations, and cities are grappling with what policies can be effective for a phased reopening shaped by social distancing. A baseline model was previously developed and calibrated for pre-COVID conditions as MATSim-NYC. A new COVID model is calibrated that represents travel behavior during the COVID-19 pandemic by recalibrating the population agendas to include work-from-home and re-estimating the mode choice model for MATSim-NYC to fit observed traffic and transit ridership data. Assuming the change in behavior exhibits inertia during reopening, we analyze the increase in car traffic due to the phased reopen plan guided by the state government of New York. Four reopening phases and two reopening scenarios (with and without transit capacity restrictions) are analyzed. A Phase 4 reopening with 100% transit capacity may only see as much as 73% of pre-COVID ridership and an increase in the number of car trips by as much as 142% of pre-pandemic levels. Limiting transit capacity to 50% would decrease transit ridership further from 73% to 64% while increasing car trips to as much as 143% of pre-pandemic levels. While the increase appears small, the impact on consumer surplus is disproportionately large due to already increased traffic congestion. Many of the trips also get shifted to other modes like micromobility. The findings imply that a transit capacity restriction policy during reopening needs to be accompanied by (1) support for micromobility modes, particularly in non-Manhattan boroughs, and (2) congestion alleviation policies that focus on reducing traffic in Manhattan, such as cordon-based pricing.
arXiv
The paper investigates the effects of the credit market development on the labor mobility between the informal and formal labor sectors. In the case of Russia, due to the absence of a credit score system, a formal lender may set a credit limit based on the verified amount of income. To get a loan, an informal worker must first formalize his or her income (switch to a formal job), and then apply for a loan. To show this mechanism, the RLMS data was utilized, and the empirical method is the dynamic multinomial logit model of employment. The empirical results show that a relaxation of credit constraints increases the probability of transition from an informal to a formal job, and improved CMA (by one standard deviation) increases the chances of informal sector workers to formalize by 5.4 ppt. These results are robust in different specifications of the model. Policy simulations show strong support for a reduction in informal employment in response to better CMA in credit-constrained communities.
SSRN
In response to unemployment shocks, older workers deplete their 401(k)s, particularly after the waiving of the early withdrawal penalty on unemployment-motivated withdrawals at age 55. This paper shows that Unemployment Insurance (UI) keeps older workers from depleting their 401(k) assets following job losses. UI also incentivizes older unemployed workers to delay claiming their Social Security (SS) benefits beyond the earliest age of eligibility, 62. Overall, UI enhances the retirement income of the individuals having a history of late-career layoffs by helping them preserve their 401(k) assets, the return on these assets and opt for a higher stream of SS benefits.
SSRN
How does an idiosyncratic shock to the liquidity of a stock affect the liquidity and prices of its related stocks? Utilizing the unique features of two-step spinoffs, we document strong evidence that the increased liquidity of spun-off firms spills over to their industry peers after the spinoffs. The liquidity spillovers across firms lead to value spillovers as well. The improved liquidity also induces larger institutional holdings in those stocks. The results provide support for the notion that the prices of spun-off firms provide additional public information about the related firms, thereby ameliorating information asymmetry in those firms.
SSRN
Scholars argue that the agency theory has some limitations as the sustaining theory of governance. It is its inability to distinguish the wider stakeholder influencing forces effecting on organizations. This paper delivers a concise picture incorporating other management-based theories to supplement agency theory in distinguishing the wider stakeholder influencing forces as well as the consequential extended governance standard it creates. Yet, for developing the theory-building approach it has reviewed and critically examined the existing literature. Furthermore, a circumstance is built to assimilate four existing theories that supplement each other to distinguish the wider stakeholder influencing forces. Finally, further studies have been recommended to certify the approach with wide-ranging real-life institutional settings.
arXiv
We examine probabilistic forecasts for battleground states in the 2020 US presidential election, using daily data from two sources over seven months: a model published by The Economist, and prices from the PredictIt exchange. We find systematic differences in accuracy over time, with markets performing better several months before the election, and the model performing better as the election approached. A simple average of the two forecasts performs better than either one of them overall, even though no average can outperform both component forecasts for any given state-date pair. This effect arises because the model and the market make different kinds of errors in different states: the model was confidently wrong in some cases, while the market was excessively uncertain in others. We conclude that there is value in using hybrid forecasting methods, and propose a market design that incorporates model forecasts via a trading bot to generate synthetic predictions. We also propose and conduct a profitability test that can be used as a novel criterion for the evaluation of forecasting performance.
arXiv
Some studies have shown that third-party punishment (TPP) substantially exists in a controlled laboratory setting. However, only a few studies investigate the robustness of TPP. This study experimentally investigates to what extent TPP can be robust by offering an additional but unattractive risky investment option to a third party. We find that when both the punishment and investment options are available, the demand for punishment decreases whereas the demand for investment increases. These findings support our hypothesis that the seemingly unrelated and dominated investment option may work as a compromise and suggest the fragility of TPP.
SSRN
We consider Heston's (1993) stochastic volatility model for valuation of European options to which (semi) closed form solutions are available and are given in terms of characteristic functions. We prove that the class of scale-parameter distributions with mean being the forward spot price satisfies Heston's solution. Thus, we show that any member of this class could be used for the direct risk-neutral valuation of the option price under Heston's SV model. In fact, we also show that any RND with mean being the forward spot price that satisfies Hestons' option valuation solution, must be a member of a scale-family of distributions in that mean. As particular examples, we show that one-parameter versions of the {\it Log-Normal, Inverse-Gaussian, Gamma, Weibull} and the {\it Inverse-Weibull} distributions are all members of this class and thus provide explicit risk-neutral densities (RND) for Heston's pricing model. We demonstrate, via exact calculations and Monte-Carlo simulations, the applicability and suitability of these explicit RNDs using already published Index data with a calibrated Heston model (S&P500, Bakshi, Cao and Chen (1997), and ODAX, Mrázek and PospÃÅ¡il (2017)), as well as current option market data (AMD).
arXiv
We consider an investment process that includes a number of features, each of which can be active or inactive. Our goal is to attribute or decompose an achieved performance to each of these features, plus a baseline value. There are many ways to do this, which lead to potentially different attributions in any specific case. We argue that a specific attribution method due to Shapley is the preferred method, and discuss methods that can be used to compute this attribution exactly, or when that is not practical, approximately.
arXiv
We develop a model of inter-temporal and intra-temporal price discrimination by monopoly airlines to study the ability of different discriminatory pricing mechanisms to increase efficiency and the associated distributional implications. To estimate the model, we use unique data from international airline markets with flight-level variation in prices across time, cabins, and markets, as well as information on passengers' reasons for travel and time of purchase. We find that the ability to screen passengers across cabins every period increases total surplus by 35% relative to choosing only one price per period, with both the airline and passengers benefiting. However, further discrimination based on passenger's reason to traveling improve airline surplus at the expense of total efficiency. We also find that the current pricing practice yields approximately 89% of the first-best welfare. The source of this inefficiency arises mostly from dynamic uncertainty about demand, not private information about passenger valuations.
SSRN
This paper studies the flows of equity mutual funds. We find that investors base their mutual fund purchase decisions in a way described by prospect theory. The prospect theory value predicts fund flows for horizons up ten months and contains incremental information compared to historical performance measures already discovered in the fund flow literature. Especially the concavity and convexity feature of the prospect theory value is responsible for the superior fund flow predictions. The results are robust to various specifications.
SSRN
Many disclosure and internal governance regulations for U.S. public firms trigger when a firm's public float exceeds a threshold. Consistent with firms seeking to avoid costly regulation, we document significant bunching around multiple regulatory thresholds introduced from 1992 to 2012. We present a revealed preference estimation strategy that uses this behavior to quantify regulatory costs. Our estimates show that various disclosure and internal governance rules leads to a total compliance cost of 4.3% of the market capitalization for a median U.S. public firm. We apply the estimated costs to firms' public-private choice and show that regulatory costs significantly impact private firms' decisions to go public, while have limited effects on public firms' decisions to go private.
arXiv
The global production (as a system of creating values) is eventually forming a vast web of value chains that explains the transitional structures of global trade and development of the world economy. It is truly a new wave of globalisation, and we can term it as the global value chains (GVCs), creating the nexus among firms, workers and consumers around the globe. The emergence of this new scenario is asking how an economy's businesses, producers and employees are connecting to the global economy and capturing the gains out of it regarding different dimensions of economic development. Indeed, this GVC approach is very crucial for understanding the organisation of the global industries (including firms) through analysing the statics and dynamics of different economic players involved in this complex global production network. Its widespread notion deals with various global issues (including regional value chains also) from the top down to the bottom up, founding a scope for policy analysis.
arXiv
We study issues of robustness in the context of Quantitative Risk Management and Optimization. We develop a general methodology for determining whether a given risk measurement related optimization problem is robust, which we call "robustness against optimization". The new notion is studied for various classes of risk measures and expected utility and loss functions. Motivated by practical issues from financial regulation, special attention is given to the two most widely used risk measures in the industry, Value-at-Risk (VaR) and Expected Shortfall (ES). We establish that for a class of general optimization problems, VaR leads to non-robust optimizers whereas convex risk measures generally lead to robust ones. Our results offer extra insight on the ongoing discussion about the comparative advantages of VaR and ES in banking and insurance regulation. Our notion of robustness is conceptually different from the field of robust optimization, to which some interesting links are derived.
SSRN
We investigate asset manager characteristics that influence ESG voting patterns using a decade of voting data with more than 20 million observations. Asset managers predominantly vote against social and environmental proposals. Especially, large and passive asset managers vote the least in favor of these proposals and despite the increased attention to sustainability integration, they hardly vote more in favor of these proposals than a decade ago. Moreover, signatories of the PRI do not vote more often in favor of environmental and social issues. Our results have important implications for investors striving for direct impact on the sustainability agenda of corporates.
SSRN
This paper frames a normative theory of stewardship engagement by large institutional investors and asset managers in terms of their theory of investment management â" âModern Portfolio Theoryâ -- which describes investors as attentive to both systematic risk as well as expected returns. Because investors want to maximize risk-adjusted returns, it will serve their interests for asset managers to support and sometimes advance shareholder initiatives that will reduce systematic risk. âSystematic Stewardshipâ provides an approach to âESGâ matters that serves both investor welfare and social welfare and fits the business model of large diversified funds, especially index funds. The analysis also shows why it is generally unwise for such funds to pursue stewardship that consists of firm-specific performance-focused engagement: Gains (if any) will be âidiosyncratic,â precisely the kind of risks that diversification minimizes. Instead asset managers should seek to mitigate systematic risk, which most notably would include climate change risk, financial stability risk, and social stability risk. This portfolio approach follows the already established pattern of assets managersâ pursuit of corporate governance measures that may increase returns across the portfolio if even not maximizing for particular firms. Systematic Stewardship does not raise the concerns of the âcommon ownershipâ critique, because the channel by which systematic risk reduction improves risk-adjusted portfolio returns is to avoid harm across the entire economy that would damage the interests of employees and consumers as well as shareholders.
SSRN
While existing studies find mixed results on the effect of hidden liquidity, this study uses the Tick Size Pilot (âthe Pilotâ) as an instrument to study how hidden liquidity, both on and off-exchange, affect the informativeness of quotations. We document that an increase in tick size results in a reduction in pre-trade transparency, but with opposing effects on on- and off-exchange hidden liquidity. We find that an increase in either hidden liquidity reduces price efficiency, the contribution of quotes to price discovery, and the ability to manage the order execution risk and cost of exchange order submission. In addition, an increase in either hidden liquidity reduces the ability to manage transaction costs off-exchange. These results hold for both on- and off-exchange hidden liquidity. However, several results differ when pre-trade transparency is measured using trade-based measures of hidden liquidity rather than order-based measures.
SSRN
That investors should diversify their portfolios is a core principle of modern finance. Yet there are some periods where diversification is undesirable. When the portfolioâs main growth engine performs well, investors prefer the opposite of diversification. An ideal complement to the growth engine would provide diversification when it performs poorly and unification when it performs well. Numerous studies have presented evidence of asymmetric correlations between assets. Unfortunately, this asymmetry is often of the undesirable variety: it is characterized by downside unification and upside diversification. In other words, diversification often disappears when it is most needed. In this article we highlight a fundamental flaw in the way that some prior studies have measured correlation asymmetry. Because they estimate downside correlations from subsamples where both assets perform poorly, they ignore instances of âsuccessfulâ diversification; that is, periods where one assetâs gains offset the otherâs losses. We propose instead that investors measure what matters: the degree to which a given asset diversifies the main growth engine when it underperforms. This approach yields starkly different conclusions, particularly for asset pairs with low full sample correlation. In this paper we review correlation mathematics, highlight the flaw in prior studies, motivate the correct approach, and present an empirical analysis of correlation asymmetry across major asset classes.
SSRN
We model the new quantitative aspects of market risk management for banks that Basel established in 2016 and came into effect in January 2019. Market risk is measured by Conditional Value at Risk (CVaR) or Expected Shortfall at a confidence level of 97.5%. The regulatory backtest remains largely based on 99% VaR. As additional statistical procedures, in line with the Basel recommendations, supplementary VaR and CVaR backtests must be performed at different confidence levels. We apply these tests to various parametric distributions and use non-parametric measures of CVaR, including CVaR- and CVaR+ to supplement the modelling validation. Our data relate to a period of extreme market turbulence. After testing eight parametric distributions with these data, we find that the information obtained on their empirical performance is closely tied to the backtesting conclusions regarding the competing models.
SSRN
Among the many problems caused by the coronomic crisis is the quick and substantial growth of the public debts of states. This problem is pressing for Georgia as well. In order to overcome the problems caused by the COVID-19 pandemic, the Government of Georgia managed to attract external debt with the amount of USD 3 billion in spring 2020, half of which will be taken by the government itself and the other half by the private sector. The government was forced to take this step in order to at least partially alleviate the social and economic problems in the country.
SSRN
A local credit shock, induced by hurricane Katrina, propagated banks' internal networks to produce real and credit markets' effects in distant regions. Driven by abnormal mortgage and housing demand in Katrina-it areas, financially constrained multi-market banks re-allocated resources toward the damaged areas leading to a credit tightening in the undamaged local markets. Depending on their housing supply elasticity, local housing markets in the undamaged regions responded to this credit disruption with a mix of housing prices and housing supply declines. These spillovers depended on undamaged markets' financial linkages to disaster areas. In the undamaged regions, community banks, being local and unexposed to disaster areas, partially insulated their markets from these spillovers.
SSRN
In this paper, I review hedge fund risk using various commonly used measures including market betas, correlations, and porfolio drawdowns. We see a picture emerge that shows hedge funds have historically hedged a fair degree of systematic market risk, especially in the early years, offering meaningful diverisification benefits to traditional stock/bond portfolios. However, the diversification benefits for investors in hedge funds have since seemingly lessened, even if not altogether eliminated. Most recently, modest benefits bore out for hedge fund investors during the 2020 pandemic, although again much less so than in the earlier years.