# Research articles for the 2021-07-06

A change of variable formula with applications to multi-dimensional optimal stopping problems
Cheng Cai,Tiziano De Angelis
arXiv

We derive a change of variable formula for $C^1$ functions $U:\mathbb{R}_+\times\mathbb{R}^m\to\mathbb{R}$ whose second order spatial derivatives may explode and not be integrable in the neighbourhood of a surface $b:\mathbb{R}_+\times\mathbb{R}^{m-1}\to \mathbb{R}$ that splits the state space into two sets $\mathcal{C}$ and $\mathcal{D}$. The formula is tailored for applications in problems of optimal stopping where it is generally very hard to control the second derivatives of the value function near the optimal stopping boundary. Differently to other existing papers on similar topics we only require that the surface $b$ be monotonic in each variable and we formally obtain the same expression as the classical It\^o's formula.

A dynamic version of the super-replication theorem under proportional transaction costs
Francesca Biagini,Thomas Reitsam
arXiv

We extend the super-replication theorems of [27] in a dynamic setting, both in the num\'eraire-based as well as in the num\'eraire-free setting. For this purpose, we generalize the notion of admissible strategies. In particular, we obtain a well-defined super-replication price process, which is right-continuous under some regularity assumptions.

Approximations to ultimate ruin probabilities with a Wienner process perturbation
Yacine Koucha,Alfredo D. Egidio dos Reis
arXiv

In this paper, we adapt the classic Cram\'er-Lundberg collective risk theory model to a perturbed model by adding a Wiener process to the compound Poisson process, which can be used to incorporate premium income uncertainty, interest rate fluctuations and changes in the number of policyholders. Our study is part of a Master dissertation, our aim is to make a short overview and present additionally some new approximation methods for the infinite time ruin probabilities for the perturbed risk model. We present four different approximation methods for the perturbed risk model. The first method is based on iterative upper and lower approximations to the maximal aggregate loss distribution. The second method relies on a four-moment exponential De Vylder approximation. The third method is based on the first-order Pad\'e approximation of the Renyi and De Vylder approximations. The last method is the second order Pad\'e-Ramsay approximation. These are generated by fitting one, two, three or four moments of the claim amount distribution, which greatly generalizes the approximations. We test the precision of approximations using a combination of light and heavy tailed distributions for the individual claim amount. We assess the ultimate ruin probability and present numerical results for the exponential, gamma, and mixed exponential claim distributions, demonstrating the high accuracy of these four methods. Analytical and numerical methods are used to highlight the practical implications of our findings.

Are Difference-in-Differences Estimates Blowing Smoke? A Cautionary Tale From an Oft-Used Natural Experiment
Zdrojewski, Anthony,Butler, Alexander W.
SSRN
We illustrate the sensitivity of two-way fixed effects difference-indifferences estimates to innocuous changes in data structure. Using the staggered rollout of state-level bank branching deregulations, three outcome variables are brought to bear on the interventions: personal income growth (a replication), house prices (new to the literature), and per capita cigarette consumption (a falsification test). Estimates are sensitive to panel length, and we document that the data structure creates the false impression of a causal effect of the interventions on all three outcome variables. We contend that any test using this particular natural experiment is at risk of generating spurious results.

Clustering Structure of Microstructure Measures
Liao Zhu,Ningning Sun,Martin T. Wells
arXiv

This paper builds the clustering model of measures of market microstructure features which are popular in predicting the stock returns. In a 10-second time frequency, we study the clustering structure of different measures to find out the best ones for predicting. In this way, we can predict more accurately with a limited number of predictors, which removes the noise and makes the model more interpretable.

Collaborative Insurance Sustainability and Network Structure
Arthur Charpentier,Lariosse Kouakou,Matthias Löwe,Philipp Ratz,Franck Vermet
arXiv

The peer-to-peer (P2P) economy has been growing with the advent of the Internet, with well known brands such as Uber or Airbnb being examples thereof. In the insurance sector the approach is still in its infancy, but some companies have started to explore P2P-based collaborative insurance products (eg. Lemonade in the U.S. or Inspeer in France). The actuarial literature only recently started to consider those risk sharing mechanisms, as in Denuit and Robert (2021) or Feng et al. (2021). In this paper, describe and analyse such a P2P product, with some reciprocal risk sharing contracts. Here, we consider the case where policyholders still have an insurance contract, but the first self-insurance layer, below the deductible, can be shared with friends. We study the impact of the shape of the network (through the distribution of degrees) on the risk reduction. We consider also some optimal setting of the reciprocal commitments, and discuss the introduction of contracts with friends of friends to mitigate some possible drawbacks of having people without enough connections to exchange risks.

Communist Imprints and Corporate Behavior
Schnorpfeil, Philip,Johanning, Lutz
SSRN
Are there long-term effects of communism on corporate behavior? We study firms in formerly communist East Germany using localized variation in West German influence. West German-influenced firms make decisions less consistent with communist norms compared to non-influenced firms: they vary employment more and rely on internal finance less. Supporting a beliefs-based channel, firms in counties where propaganda of these norms was more effective exhibit stronger communist ideology in their decisions. Corporate behavior also discontinuously varies along the former Inner German border, which we again trace to ideological imprints. Our results, which withstand numerous robustness tests, suggest a novel element of the Soviet-communist legacy.

Corporate Governance Reforms and Innovation
Lin, Chen,Wei, Lai,Zhao, Hui
SSRN
In this study, we investigate the effect of corporate governance reforms on corporate innovation by constructing a comprehensive firm-level panel dataset across 58 countries from 2000 to 2015. We find that both the quantity and quality of innovation decrease after the initiation of the reforms. Affected firms also conduct less innovation that explores new knowledge versus that exploits existing knowledge. The effect is more pronounced for firms operating in more competitive industries or with higher operational uncertainty. The results suggest that corporate governance reforms may induce managerial myopia and mitigate long-term investment in risky innovation.

Countering Misinformation on Social Media Through Educational Interventions: Evidence from a Randomized Experiment in Pakistan
Ayesha Ali,Ihsan Ayyub Qazi
arXiv

Fake news is a growing problem in developing countries with potentially far-reaching consequences. We conduct a randomized experiment in urban Pakistan to evaluate the effectiveness of two educational interventions to counter misinformation among low-digital literacy populations. We do not find a significant effect of video-based general educational messages about misinformation. However, when such messages are augmented with personalized feedback based on individuals' past engagement with fake news, we find an improvement of 0.14 standard deviations in identifying fake news. We also find negative but insignificant effects on identifying true news, driven by female respondents. Our results suggest that educational interventions can enable information discernment but their effectiveness critically depends on how well their features and delivery are customized for the population of interest.

Delayed Creative Destruction: How Uncertainty Shapes Corporate Assets
Campello, Murillo,Kankanhalli, Gaurav,Kim, Hyunseob
SSRN
We show how uncertainty shapes the asset allocation, composition, productivity, and value of capital-intensive firms. We do so using detailed, near-universal data on shipping firms' new orders, secondary-market transactions, and demolition of ships. Firms curtail both the acquisition and disposal of vessels in response to heightened uncertainty. The mechanism operates primarily through cuts in new ship orders and demolition of older ships â€" decisions that are costlier to reverse vis-a-vis deals in the used ship market. These dynamics are more pronounced when secondary ship markets are illiquid, as firms face stronger incentives to delay their decisions. The rise of Somali pirate attacks in 2009â€"2011 is used as a shock to well-defined shipping sectors to corroborate our findings. Critically, uncertainty prompts firms to concentrate their fleets into narrower, less productive portfolios, leading to value losses. Our work is novel in showing that uncertainty hampers "creative destruction," slowing both the adoption of innovation embodied in new capital and the disposal of old capital.

Do Banks Overreact to Disaster Risk?
Huang, Qianqian,Jiang, Feng,Xuan, Yuhai,Yuan, Tao
SSRN
We examine how banks respond to large natural disasters when corporate borrowers are located in the neighborhood of the disaster area. We find robust evidence that banks charge significantly higher loan spreads for firms located in the neighborhood of the disaster area than for remote firms. The results are not driven by regional spillovers, limited credit supply, lender rent extraction motive, or rational learning. We also find that banksâ€™ reaction is transitory, and is less pronounced for experienced banks. Overall, our empirical findings indicate that banks are subject to salience bias when assessing their clientsâ€™ natural disaster risk.

Efficiency of communities and financial markets during the 2020 pandemic
Nick James,Max Menzies
arXiv

This paper investigates the relationship between the spread of the COVID-19 pandemic, the state of community activity, and the financial index performance across 20 countries. First, we analyze which countries behaved similarly in 2020 with respect to one of three multivariate time series: daily COVID-19 cases, Apple mobility data and national equity index price. Next, we study the trajectories of all three of these attributes in conjunction to determine which exhibited greater similarity. Finally, we investigate whether country financial indices or mobility data responded quicker to surges in COVID-19 cases. Our results indicate that mobility data and national financial indices exhibited the most similarity in their trajectories, with financial indices responding quicker. This suggests that financial market participants may have interpreted and responded to COVID-19 data more efficiently than governments. Further, results imply that efforts to study community mobility data as a leading indicator for financial market performance during the pandemic were misguided.

Face masks, vaccination rates and low crowding drive the demand for the London Underground during the COVID-19 pandemic
Prateek Bansal,Roselinde Kessels,Rico Krueger,Daniel J Graham
arXiv

The COVID-19 pandemic has drastically impacted people's travel behaviour and out-of-home activity participation. While countermeasures are being eased with increasing vaccination rates, the demand for public transport remains uncertain. To investigate user preferences to travel by London Underground during the pandemic, we conducted a stated choice experiment among its pre-pandemic users (N=961). We analysed the collected data using multinomial and mixed logit models. Our analysis provides insights into the sensitivity of the demand for the London Underground with respect to travel attributes (crowding density and travel time), the epidemic situation (confirmed new COVID-19 cases), and interventions (vaccination rates and mandatory face masks). Mandatory face masks and higher vaccination rates are the top two drivers of travel demand for the London Underground during COVID-19. The positive impact of vaccination rates on the Underground demand increases with crowding density, and the positive effect of mandatory face masks decreases with travel time. Mixed logit reveals substantial preference heterogeneity. For instance, while the average effect of mandatory face masks is positive, preferences of around 20% of the pre-pandemic users to travel by the Underground are negatively affected. The estimated demand sensitivities are relevant for supply-demand management in transit systems and the calibration of advanced epidemiological models.

Financial Policymaking after Crises: Public vs. Private Interests
Saka, Orkun,Ji, Yuemei,De Grauwe, Paul
SSRN
We first present a simple model of post-crisis policymaking driven by both public and private interests. Using a novel dataset covering 94 countries between 1973 and 2015, we then establish that financial crises can lead to government interventions in financial markets. Consistent with a public interest channel, we find post-crisis interventions occur only in democratic countries. However, by using a plausibly exogenous setting -i.e., term limits- muting political accountability, we show that democratic leaders who do not have re-election concerns are substantially more likely to intervene in financial markets after crises, in ways that may promote (obstruct) private (public) interests.

Financial policymaking after crises: Public vs. private interests
Saka, Orkun,Ji, Yuemei,De Grauwe, Paul
RePEC
We first present a simple model of post-crisis policymaking driven by both public and private interests. Using a novel dataset covering 94 countries between 1973 and 2015, we then establish that financial crises can lead to government interventions in financial markets. Consistent with a public interest channel, we find post-crisis interventions occur only in democratic countries. However, by using a plausibly exogenous setting -i.e., term limits- muting political accountability, we show that democratic leaders who do not have re-election concerns are substantially more likely to intervene in financial markets after crises, in ways that may promote (obstruct) private (public) interests.

Generative Adversarial Networks in finance: an overview
Florian Eckerli,Joerg Osterrieder
arXiv

Modelling in finance is a challenging task: the data often has complex statistical properties and its inner workings are largely unknown. Deep learning algorithms are making progress in the field of data-driven modelling, but the lack of sufficient data to train these models is currently holding back several new applications. Generative Adversarial Networks (GANs) are a neural network architecture family that has achieved good results in image generation and is being successfully applied to generate time series and other types of financial data. The purpose of this study is to present an overview of how these GANs work, their capabilities and limitations in the current state of research with financial data, and present some practical applications in the industry. As a proof of concept, three known GAN architectures were tested on financial time series, and the generated data was evaluated on its statistical properties, yielding solid results. Finally, it was shown that GANs have made considerable progress in their finance applications and can be a solid additional tool for data scientists in this field.

Higher Education: Can Debt Beat Savings?
Stackpole, David
SSRN
This paper investigates the possible opportunity cost of using standard college savings plans against the advantages of using debt to pay for college. In addition, it presents a practical argument for using debt in place of college savings plans in certain instances.By doing so, investors may not only be able to mitigate the difficulty of saving, but also realize greater financial benefit in the long run.

Macroeconomic Fundamentals and the Pricing of Anomaly Portfolios
Tharyan, Rajesh
SSRN
The consensus is that asset pricing models with macroeconomic factors perform poorly, relative to firm-characteristic-based factor models, in explaining the cross-section of stock and bond returns. This is a disconcerting result if the â€œcentral task of asset pricingâ€ is to demonstrate the link between macro risk factors and asset returns. I propose a model with a set of factors that mimic underlying fundamental sources of risk in the economy. These factors are extracted using a novel stock-level sort that preserves the relation between stocks and a large set of macroeconomic variables. This model performs at least as well as standard characteristic-based factor models in explaining the cross-section of common benchmark and anomaly portfolio spreads. Taken together, the evidence shows that macroeconomic factors are useful in explaining the cross-section of stock and bond returns.

Managerial Short-Termism and ESG
Lin, Chen,Wei, Lai,Yang, Nan,Zhang, Yupu
SSRN
While practitioners call for long-term managerial compensation to promote firmsâ€™ commitment in environmental, social and governance (ESG) issues, little direct evidence exists on the role managerial incentive horizon plays in firmsâ€™ ESG performance. Exploiting two alternative identification strategies, we find consistent evidence that firm ESG performance declines when CEO short-term incentive becomes stronger. We find similar results using other ESG measures including worker injuries and pollution. Together, the evidence suggests that CEO compensation that promotes long-termism is critical for ESG.

Optimal Insurance to Maximize RDEU Under a Distortion-Deviation Premium Principle
Xiaoqing Liang,Ruodu Wang,Virginia Young
arXiv

In this paper, we study an optimal insurance problem for a risk-averse individual who seeks to maximize the rank-dependent expected utility (RDEU) of her terminal wealth, and insurance is priced via a general distortion-deviation premium principle. We prove necessary and sufficient conditions satisfied by the optimal solution and consider three ambiguity orders to further determine the optimal indemnity. Finally, we analyze examples under three distortion-deviation premium principles to explore the specific conditions under which no insurance or deductible insurance is optimal.

Penny-Wise and Pound-Foolish: Does Striving to Meet Earnings Expectations by Manipulating Real Activities Undermine Product Quality?
Chen, Yangyang,Ma, Lijun,Pittman, Jeffrey,Yang, Xin
SSRN
We examine whether managersâ€™ activities in striving to reach earnings targets affect their firmsâ€™ product quality. We find that firms suspected of manipulating real activities in trying to meet earnings benchmarks exhibit a higher likelihood and frequency of product recalls. Other evidence implies that high earnings pressure induces managers to manipulate real activities, resulting in more product quality failures. In cross-sectional results consistent with expectations, we find that the impact of exploiting real activities to attain earnings benchmarks on product recalls intensifies for firms whose managers have stronger incentives to manage earnings and subsides for firms subject to greater customer power. Additional tests show that suspected benchmark targeting also raises the severity of product recalls and that investors react less strongly to small positive earnings surprises for firms with a history of product recalls.

Predicting Exporters with Machine Learning
Francesca Micocci,Armando Rungi
arXiv

In this contribution, we exploit machine learning techniques to predict out-of-sample firms' ability to export based on the financial accounts of both exporters and non-exporters. Therefore, we show how forecasts can be used as exporting scores, i.e., to measure the distance of non-exporters from export status. For our purpose, we train and test various algorithms on the financial reports of 57,021 manufacturing firms in France in 2010-2018. We find that a Bayesian Additive Regression Tree with Missingness In Attributes (BART-MIA) performs better than other techniques with a prediction accuracy of up to $0.90$. Predictions are robust to changes in definitions of exporters and in the presence of discontinuous exporters. Eventually, we argue that exporting scores can be helpful for trade promotion, trade credit, and to assess firms' competitiveness. For example, back-of-the-envelope estimates show that a representative firm with just below-average exporting scores needs up to $44\%$ more cash resources and up to $2.5$ times more capital expenses to reach full export status.

Stopping spikes, continuation bays and other features of optimal stopping with finite-time horizon
Tiziano De Angelis
arXiv

We consider optimal stopping problems with finite-time horizon and state-dependent discounting. The underlying process is a one-dimensional linear diffusion and the gain function is time-homogeneous and difference of two convex functions. Under mild technical assumptions with local nature we prove fine regularity properties of the optimal stopping boundary including its continuity and strict monotonicity. The latter was never proven with probabilistic arguments. We also show that atoms in the signed measure associated with the second order spatial derivative of the gain function induce geometric properties of the continuation/stopping set that cannot be observed with smoother gain functions (we call them \emph{continuation bays} and \emph{stopping spikes}). The value function is continuously differentiable in time without any requirement on the smoothness of the gain function.

Tafsir-Maarif al-Quran of Mufti Muhammad Shafi An Approach
Wani, Dr. Bilal
SSRN
Mufti Muhammad Shafi is counted amongst the leading â€˜Ulama of Indo-Pak subcontinent who carried the banner of the pure religion in these lands and spent their lives and their strength in elevating it so that the caravan of Islam continues to proceed. Allah enabled him to serve Islam and the Muslims with every limb of his body, until his life became dependent on religion and its people. Mufti Muhammad Shafi has many beneficial works whose number surpasses one hundred, and according to Mufti Muhammad Rafi â€˜Uthmani, the exact number of his books is 162, most of them in the Urdu language, on the sciences of Quranic exegesis, Hadith, Jurisprudence, Spirituality, Literature, Theology, social etiquettes and other topics. One of the greatest contributions of Mufti Muhammad Shafi is considered the writing of a very popular Tafsir known as Maâ€˜arif al-Quran. The present paper is an attempt to highlight the distinctive features of this important Tafsir which makes it different from other Tafasir.

The Impact of COVID-19 Economic Crisis on the Speed of Adjustment toward Target Leverage Ratio: An International Analysis
Vo, Thi Thuy Anh,Mazur, Mieszko,Thai, Thi Hong An
SSRN
This paper investigates changes in the speed of adjustment toward target leverage ratio under the impact of COVID-19 economic crisis. Using an international sample of publicly listed firms, we find that, on average, firms tend to adjust their capital structure more rapidly in the period following the breakout of COVID-19. Furthermore, we find that firms domiciled in countries in which COVID-19 causes more severe damage, adjust their target leverage quicker than firms domiciled in less severely affected countries. Overall, our study aims at developing a better un- derstanding of the impact of COVID-19 on corporate financing decisions.

The Information Advantage of Institutional Common Owners: Evidence from Stock Price Crash Risk
Li, Qingyuan,Ni, Xiaoran,Yeung, P. Eric,Yin, David
SSRN
In contrast with the evidence that institutional ownership increases firm-level stock price crash risk, this study finds that institutional common ownership reduces crash risk. The negative effect of institutional common ownership manifests itself through non-dedicated common owners and is more pronounced among firms whose information is more ambiguous (i.e., whether industry-wide or firm-specific). Our findings support the stabilizing role of institutional common owners in the market due to their information advantage, allowing them to better differentiate between the firm-specific and industry-wide nature of bad news, thus avoid selling on false signals.

The Role of Banks' Technology Adoption in Credit Markets during the Pandemic
Branzoli, Nicola,Rainone, Edoardo,Supino, Ilaria
SSRN
This paper shows that higher information technology (IT) adoption by banks led to a larger increase in corporate lending in the months following the COVID-19 outbreak in Italy. Examining banks with heterogeneous degrees of IT adoption, we investigate the dynamics of credit and its allocation across firms using a new database with detailed information on bank IT expenditures and propensity to innovate matched with bank-firm level data on credit growth before and during the pandemic. Using a difference-in-differences identification strategy, we find that banks with higher intensity of IT adoption increased their credit more than others during the pandemic. The increase was concentrated in term loans extended to smaller and financially sounder companies; the effect was stronger in the initial phase of tighter restrictions to firm activity and individual mobility, and more significant for undertakings active in the sectors most affected by the shock. We provide evidence that these results are driven by both bank's ability to offer credit entirely on-line and bank's use of digital technologies for creditworthiness assessment. We find that physical proximity between borrowers and lenders remained important for credit provision during the pandemic, but only when combined with high level of IT adoption.

The global migration network of sex-workers
Luis E C Rocha,Petter Holme,Claudio D G Linhares
arXiv

Differences in the social and economic environment across countries encourage humans to migrate in search of better living conditions, including job opportunities, higher salaries, security and welfare. Quantifying global migration is, however, challenging because of poor recording, privacy issues and residence status. This is particularly critical for some classes of migrants involved in stigmatised, unregulated or illegal activities. Escorting services or high-end prostitution are well-paid activities that attract workers all around the world. In this paper, we study international migration patterns of sex-workers by using network methods. Using an extensive international online advertisement directory of escorting services and information about individual escorts, we reconstruct a migrant flow network where nodes represent either origin or destination countries. The links represent the direct routes between two countries. The migration network of sex-workers shows different structural patterns than the migration of the general population. The network contains a strong core where mutual migration is often observed between a group of high-income European countries, yet Europe is split into different network communities with specific ties to non-European countries. We find non-reciprocal relations between countries, with some of them mostly offering while others attract workers. The GDP per capita is a good indicator of country attractiveness for incoming workers and service rates but is unrelated to the probability of emigration. The median financial gain of migrating, in comparison to working at the home country, is 15.9%. Only sex-workers coming from 77% of the countries have financial gains with migration and average gains decrease with the GDPc of the country of origin. Our results shows that high-end sex-worker migration is regulated by economic, geographic and cultural aspects.

The unbearable lightness of equilibria in a low interest rate environment
Guido Ascari,Sophocles Mavroeidis
arXiv

Structural models with no solution are incoherent, and those with multiple solutions are incomplete. We show that models with occasionally binding constraints are not generically coherent. Coherency requires restrictions on the parameters or on the support of the distribution of the shocks. These restrictions are rarely explicitly acknowledged or imposed in the literature. Models whose coherency is based on support restrictions are generically incomplete, admitting a very large number of minimum state variable solutions. These are distinct from the solutions due to indeterminacy in models without an effective lower bound constraint.

Two Stochastic Control Problems In Capital Structure and Portfolio Choice
Shan Huang
arXiv

This thesis mainly focuses on two problems in capital structure and individual's life-cycle portfolio choice. In the first problem, we derive a stochastic control model to optimize banks' dividend and recapitalization policies and calibrate that to a sample of U.S. banks in the situation where we model banks' true accounting asset values as partially observed variables due to the opaqueness in banks' assets. By the calibrated model, the noise in reported accounting asset values hides about one-third of the true asset return volatility and raises the banks' market equity value by 7.8\% because the noise hides the banks' solvency risk from banking regulators. Particularly, those banks with a high level of loan loss provisions, nonperforming assets, and real estate loans, and with a low volatility of reported total assets have noisy accounting asset values. Because of the substantial shock on the true asset values, the banks' assets were more opaque during the recent financial crisis. In the second problem, we present an optimal portfolio selection model with voluntary retirement option in an economic situation, where an investor is facing borrowing and short sale constraints, as well as the cointegration between the stock and labor markets. Our model reinterprets the non-participation puzzle in stock investment and early retirement in market booms. Investor's willingness to retire earlier becomes stronger as risk aversion increases or as wages decline in the long term. Consistent with the empirical evidence, we find that retirement flexibility makes the optimal portfolio invest less in the stock market. We also find that our model-generated portfolio share rises in wealth.