Research articles for the 2021-07-15

A Fundamental Connection: Exchange Rates and Macroeconomic Expectations
Stavrakeva, Vania,Tang, Jenny
This paper presents new stylized facts about exchange rates and their relationship with macroeconomic fundamentals. We show that macroeconomic surprises explain a large majority of the variation in nominal exchange rate changes at a quarterly frequency. Using a novel present value decomposition of exchange rate changes that is disciplined with survey forecast data, we show that macroeconomic surprises are also a very important driver of the currency risk premium component and explain about half of its variation. These surprises have even greater explanatory power during economic downturns and periods of financial uncertainty.

A new class of conditional Markov jump processes with regime switching and path dependence: properties and maximum likelihood estimation
Budhi Surya

This paper develops a new class of conditional Markov jump processes with regime switching and paths dependence. The key novel feature of the developed process lies on its ability to switch the transition rate as it moves from one state to another with switching probability depending on the current state and time of the process as well as its past trajectories. As such, the transition from current state to another depends on the holding time of the process in the state. Distributional properties of the process are given explicitly in terms of the speed regimes represented by a finite number of different transition matrices, the probabilities of selecting regime membership within each state, and past realization of the process. In particular, it has distributional equivalent stochastic representation with a general mixture of Markov jump processes introduced in Frydman and Surya (2020). Maximum likelihood estimates (MLE) of the distribution parameters of the process are derived in closed form. The estimation is done iteratively using the EM algorithm. Akaike information criterion is used to assess the goodness-of-fit of the selected model. An explicit observed Fisher information matrix of the MLE is derived for the calculation of standard errors of the MLE. The information matrix takes on a simplified form of the general matrix formula of Louis (1982). Large sample properties of the MLE are presented. In particular, the covariance matrix for the MLE of transition rates is equal to the Cram\'er-Rao lower bound, and is less for the MLE of regime membership. The simulation study confirms these findings and shows that the parameter estimates are accurate, consistent, and have asymptotic normality as the sample size increases.

Aig in Hindsight
McDonald, Robert,Paulson, Anna L.
The near-failure on September 16, 2008, of American International Group (AIG) was an iconic moment in the financial crisis. The decision to rescue AIG was controversial at the time and remains so. Large bets on real estate pushed AIG to the brink of bankruptcy. In one case, AIG used securities lending to transform insurance company assets into residential mortgage-backed securities (RMBS) and collateralized debt obligations (CDOs), ultimately losing at least $21 billion and threatening the solvency of the life insurance companies. AIG also sold insurance on multi-sector CDOs, backed by real estate assets, ultimately losing more than $30 billion. These activities were apparently motivated by a belief that AIG?s real estate bets would not suffer defaults and were ?money-good.? We find that these securities have in fact suffered write-downs and that the stark ?money-good? claim can be rejected.

Article Processing Charges based publications: to which extent the price explains scientific impact?
Abdelghani Maddi,David Sapinho

The present study aims to analyze relationship between Citations Normalized Score (NCS) of scientific publications and Article Processing Charges (APCs) amounts of Gold Open access publications. To do so, we use APCs information provided by OpenAPC database and citations scores of publications in the Web of Science database (WoS). Database covers the period from 2006 to 2019 with 83,752 articles published in 4751 journals belonging to 267 distinct publishers. Results show that contrary to this belief, paying dearly does not necessarily increase the impact of publications. First, large publishers with high impact are not the most expensive. Second, publishers with the highest APCs are not necessarily the best in terms of impact. Correlation between APCs and impact is moderate. Otherwise, in the econometric analysis we have shown that publication quality is strongly determined by journal quality in which it is published. International collaboration also plays an important role in citations score.

Bank Intermediation in times of digitalized corporate customers and competitors? â€" Relationship Lending as safe haven
Scholle, Lorraine,Heinze, Marcel
Within a two-dimensional framework, this article provides an literature-based discussion of how banks' corporate lending business is affected by digitization. On the one hand, technological advances induced by digitization are changing internal processes and business models among the banks' corporate customers. This creates a change in customer requirements and demand for financing of digitization projects. On the other hand, alternative providers of corporate loans are emerging in the form of online marketplace lenders.We first note that there is a funding gap for digitization projects that could hamper progress in technological development. Investments in digital technologies differ from “traditional” investments in their lack of tangible assets and a high degree of uncertainty about the project outcome which could be the main drivers of this funding gap. As digital marketplace lenders experience high growth rates especially in past periods of reduced credit supply by banks, we argue that marketplace lenders could fill this gap. Under this assumption, we discuss whether, marketplace lenders can fulfil essential intermediation functions and conclude that traditional competitive advantages of banks over marketplace lenders are diminishing. We therefore extend our discussion and examine the extent to which the concept of relationship lending provides banks with competitive advantages over marketplace lending. We conclude banks need to focus on the personal approach. Of particular importance is the expertise of the loan officer in evaluating innovation projects, whereas interpersonal trust, customer orientation and service quality form the basis for the continuity of customer loyalty in competition with fintech lenders.

Business analytics meets artificial intelligence: Assessing the demand effects of discounts on Swiss train tickets
Martin Huber,Jonas Meier,Hannes Wallimann

We assess the demand effects of discounts on train tickets issued by the Swiss Federal Railways, the so-called `supersaver tickets', based on machine learning, a subfield of artificial intelligence. Considering a survey-based sample of buyers of supersaver tickets, we investigate which customer- or trip-related characteristics (including the discount rate) predict buying behavior, namely: booking a trip otherwise not realized by train, buying a first- rather than second-class ticket, or rescheduling a trip (e.g.\ away from rush hours) when being offered a supersaver ticket. Predictive machine learning suggests that customer's age, demand-related information for a specific connection (like departure time and utilization), and the discount level permit forecasting buying behavior to a certain extent. Furthermore, we use causal machine learning to assess the impact of the discount rate on rescheduling a trip, which seems relevant in the light of capacity constraints at rush hours. Assuming that (i) the discount rate is quasi-random conditional on our rich set of characteristics and (ii) the buying decision increases weakly monotonically in the discount rate, we identify the discount rate's effect among `always buyers', who would have traveled even without a discount, based on our survey that asks about customer behavior in the absence of discounts. We find that on average, increasing the discount rate by one percentage point increases the share of rescheduled trips by 0.16 percentage points among always buyers. Investigating effect heterogeneity across observables suggests that the effects are higher for leisure travelers and during peak hours when controlling several other characteristics.

Chief Executive Officer Power and Corporate Sexual Orientation Equality
Brodmann, Jennifer,Hossain, Ashrafee T,Masum, Abdullah Al,Singhvi, Meghna
We examine the role of Chief Executive Officer (CEO) power in Corporate Sexual Orientation Equality (CSOE), measured by corporate support for employees with alternate sexual orientations (i.e., Lesbian, Gay, Bisexual, Transgender, and Queer â€" LGBTQ). We find that CEO power is an obstacle to promoting CSOE. Our finding is robust to different model specifications and a battery of endogeneity checks. In the cross-section, we find that the negative association between CEO power and CSOE is more (less) pronounced for firms with weaker (stronger) external monitoring, with a lower (higher) level of transparency, and those located in a more (less) religious county. We also find evidence that the financial market appreciates it when powerful CEOs are less engaged in possibly controversial promotional activities, such as LGBTQ-friendliness.

Computing near-optimal Value-at-Risk portfolios using Integer Programming techniques
Onur Babat,Juan C. Vera,Luis F. Zuluaga

Value-at-Risk (VaR) is one of the main regulatory tools used for risk management purposes. However, it is difficult to compute optimal VaR portfolios; that is, an optimal risk-reward portfolio allocation using VaR as the risk measure. This is due to VaR being non-convex and of combinatorial nature. In particular, it is well known that the VaR portfolio problem can be formulated as a mixed integer linear program (MILP) that is difficult to solve with current MILP solvers for medium to large-scale instances of the problem. Here, we present an algorithm to compute near-optimal VaR portfolios that takes advantage of this MILP formulation and provides a guarantee of the solution's near-optimality. As a byproduct, we obtain an algorithm to compute tight lower bounds on the VaR portfolio problem that outperform related algorithms proposed in the literature for this purpose. The near-optimality guarantee provided by the proposed algorithm is obtained thanks to the relation between minimum risk portfolios satisfying a reward benchmark and the corresponding maximum reward portfolios satisfying a risk benchmark. These alternate formulations of the portfolio allocation problem have been frequently studied in the case of convex risk measures and concave reward functions. Here, this relationship is considered for general risk measures and reward functions. To illustrate the efficiency of the presented algorithm, numerical results are presented using historical asset returns from the US financial market.

Credit scoring using neural networks and SURE posterior probability calibration
Matthieu Garcin,Samuel Stéphan

In this article we compare the performances of a logistic regression and a feed forward neural network for credit scoring purposes. Our results show that the logistic regression gives quite good results on the dataset and the neural network can improve a little the performance. We also consider different sets of features in order to assess their importance in terms of prediction accuracy. We found that temporal features (i.e. repeated measures over time) can be an important source of information resulting in an increase in the overall model accuracy. Finally, we introduce a new technique for the calibration of predicted probabilities based on Stein's unbiased risk estimate (SURE). This calibration technique can be applied to very general calibration functions. In particular, we detail this method for the sigmoid function as well as for the Kumaraswamy function, which includes the identity as a particular case. We show that stacking the SURE calibration technique with the classical Platt method can improve the calibration of predicted probabilities.

Does Revenue-Expense Matching Play a Differential Role in Analysts’ Earnings and Revenue Forecasts?
Kim, Robert,Kim, Sangwan
This paper investigates whether matching has differential implications for the accuracy of analysts’ earnings and revenue forecasts. We construct a novel measure of firm-level matching and document that matching improves analysts’ earnings forecasts to a greater extent than their revenue forecasts. We also document matching’s differential impact on analysts’ earnings and sales forecasts by proposing a new count metric capturing a wedge in the accuracy of earnings and revenue forecasts. In additional tests, we report that the differential impact of matching is less (more) pronounced in a situation where the balance sheet (income statement) orientation likely dominates. We also report that matching’s differential role is weaker (stronger) when firms have high intangible intensity (analysts have appropriate resources or expertise). In short window tests, matching’s role in analysts’ forecast revisions is more pronounced for earnings than sales forecasts. Overall, these results show how analysts benefit from better revenue-expense matching.

Does Sunlight Kill Germs? Stock Market Listing and Workplace Safety
Liang, Claire Y.C.,Qi, Yaxuan,Zhang, Rengong,Zhu, Haoran
We find that, on average, workplace injuries in publicly-listed firms are lower than those in comparable private firms. This finding is robust to multiple tests designed to mitigate endogeneity concerns regarding a firm’s listing status. Further investigation suggests that the benefit of a public listing for workplace safety relates to heightened monitoring of listed firms by the media and regulators. The listing effect is more pronounced when media coverage is high. We further find that public firms located in counties facing reduced media scrutiny, due to local newspaper closures, experience greater increases in injury rates than local private counterparts after the closures. Regulators also impose more stringent monitoring on public firms, evidenced by a higher likelihood of nonroutine inspections and larger penalties on detected violations. Overall, our study highlights the positive impact of a stock market listing on workplace safety.

ESG Disclosure, REIT Debt Financing and Firm Value
Feng, Zifeng,Wu, Zhonghua
Using recently available GRESB ESG public disclosure data for REITs around the world, we examine how ESG disclosure is related to REIT debt financing and firm value. We find that REITs with higher levels of ESG disclosure have lower cost of debt, higher credit ratings, and higher unsecured debt to total debt ratio, controlling for key firm characteristics. These findings suggest that improving ESG disclosure can help REITs to gain better access to the capital markets and enhance corporate financial flexibility, as lenders have paid close attention to a firm’s ESG disclosure and integrated evaluation of ESG factors into their lending decisions. Moreover, firm value of REITs is positively associated with their ESG disclosure level. When using the Covid-19 pandemic as a quasi-experimental setting, we find evidence that REITs with higher ESG disclosure levels before the pandemic exhibit higher firm value during the pandemic. These results indicate that investors do value active ESG disclosure by REITs. Additional analyses show that ESG disclosure level is sensitive to institutional ownership, implying that institutional investors may drive REIT ESG disclosure efforts. Taken together, this paper suggests that effective ESG disclosure can have a positive impact on REIT debt financing and firm value due to the increased corporate transparency, and the ESG reporting framework developed by GRESB appears to be effective to provide transparency and comparability across the global real estate industry.

How does Student Debt affect Early-Career Retirement Saving?
Rutledge, Matthew,Sanzenbacher, Geoffrey,Vitagliano, Francis
This paper examines the relationship between student loans and retirement saving by 30-year-old workers. Total outstanding student loan debt in the United States has quintupled since 2004. Rising student debt levels mean that young workers must reduce either their consumption or their saving. To what extent do these workers cut back on retirement saving? Existing studies have lacked adequate data or controls for studying this issue, especially for younger workers. This study uses the National Longitudinal Survey of Youth 1997 Cohort, and thus includes a large sample of young workers, and includes detailed controls including school quality, parental background, and the underlying ability of the college attendee. While the estimated relationship between student debt and participation in a retirement plan is small, bachelor's degree-holders who have student loans do have significantly lower retirement assets at age 30 than those without loans. Interestingly, the actual size of the student loan does not seem to matter – those with student loans have lower retirement savings, but retirement wealth accumulation is similar for those with small loans and large loans.

Internal Capital Markets, Corporate Investment, and the COVID-19 Pandemic: Evidence from Korean Business Groups
Lee, Sangwon
This paper examines whether the investment of Korean business group (“chaebol”) affiliated firms behaved differently from that of non-chaebol firms in response the COVID-19 outbreak. I show that chaebol firms cut back investment less than similar non-chaebol firms. Chaebol firms with higher-than-industry-median market-to-book ratios invested more and experienced less declines in their stock prices, while I fail to find such relationships for non-chaebol firms. This paper provides evidence that chaebol internal capital markets helped mitigate the negative effects of the COVID-19 pandemic on firm investment and values.

International Asset Pricing with Strategic Business Groups
Massa, Massimo,O'Donovan, James,Zhang, Hong
Firms in global markets often belong to business groups. We argue that this feature can have a profound influence on international asset pricing. In bad times, business groups may strategically reallocate risk across affiliated firms to protect core “central firms.” This strategic behavior induces co-movement among central firms, creating a new intertemporal risk factor. Based on a novel dataset of worldwide ownership for 2002-2012, we find that central firms are better protected in bad times and that they earn relatively lower expected returns. Moreover, a centrality factor augments traditional models in explaining the cross-section of international stock returns.

International Trade and Letters of Credit: A Double-edged Sword in Times of Crises
Crozet, Matthieu,Demir, Banu,Javorcik, Beata S.
This study argues that the ability to mitigate risks associated with international trade is particularly important at times of heightened uncertainty, such as the economic crisis caused by the Covid-19 pandemic. Risk mitigation can be achieved through letters of credit (LCs), trade finance instruments providing guarantees to trading partners. As their use varies across products, exports of some products are more resilient than others during times of increased uncertainty. This situation reverses in times of financial crises when distressed banks may limit the supply of LCs. Our analysis using data on US and EU-15 exports during the Covid crisis and the Global Financial Crisis provides empirical support for these hypotheses.

Market risk factors analysis for an international mining company. Multi-dimensional, heavy-tailed-based modelling
Łukasz Bielak,Aleksandra Grzesiek,Joanna Janczura,Agnieszka Wyłomańska

Mining companies to properly manage their operations and be ready to make business decisions, are required to analyze potential scenarios for main market risk factors. The most important risk factors for KGHM, one of the biggest companies active in the metals and mining industry, are the price of copper (Cu), traded in US dollars, and the Polish zloty (PLN) exchange rate (USDPLN). The main scope of the paper is to understand the mid- and long-term dynamics of these two risk factors. For a mining company it might help to properly evaluate potential downside market risk and optimise hedging instruments. From the market risk management perspective, it is also important to analyze the dynamics of these two factors combined with the price of copper in Polish zloty (Cu in PLN), which jointly drive the revenues, cash flows, and financial results of the company. Based on the relation between analyzed risk factors and distribution analysis, we propose to use two-dimensional vector autoregressive (VAR) model with the $\alpha-$stable distribution. The non-homogeneity of the data is reflected in two identified regimes: first - corresponding to the 2008 crisis and second - to the stable market situation. As a natural implication of the model fitted to market assets, we derive the dynamics of the copper price in PLN, which is not a traded asset but is crucial for the KGHM company risk exposure. A comparative study is performed to demonstrate the effect of including dependencies of the assets and the implications of the regime change. Since for various international companies, risk factors are given rather in the national than the market currency, the approach is universal and can be used in different market contexts, like mining or oil companies, but also other commodities involved in the global trading system.

Mind the App: Information Design and Consumer Behavior
Levi, Yaron
In a randomized field experiment, I test if the way in which information is presented influences consumer behavior. Users of an online account aggregation app received a personalized index representing their net worth as a lifetime monthly cash flow. The presentation of the index varied in the framing used to describe the index and in the salience of the comparison between the index and the user's historical spending. Consumers that received a consumption frame (promoting a mental reflection about the affordability of future consumption) and a salient comparison with historical spending decreased their discretionary spending by 15% relative to other treatments throughout the eight months of the experiment. The effect persisted for an additional eight months after the removal of the experiment content from the app. The sensitivity of consumers' spending to information design presents opportunities for policies aimed at influencing saving rates.

Modelling Sovereign Credit Ratings: Evaluating the Accuracy and Driving Factors using Machine Learning Techniques
Bart H.L. Overes,Michel van der Wel

Sovereign credit ratings summarize the creditworthiness of countries. These ratings have a large influence on the economy and the yields at which governments can issue new debt. This paper investigates the use of a Multilayer Perceptron (MLP), Classification and Regression Trees (CART), Support Vector Machines (SVM), Na\"ive Bayes (NB), and an Ordered Logit (OL) model for the prediction of sovereign credit ratings. We show that MLP is best suited for predicting sovereign credit ratings, with a random cross-validated accuracy of 68%, followed by CART (59%), SVM (41%), NB (38%), and OL (33%). Investigation of the determining factors shows that there is some heterogeneity in the important variables across the models. However, the two models with the highest out-of-sample predictive accuracy, MLP and CART, show a lot of similarities in the influential variables, with regulatory quality, and GDP per capita as common important variables. Consistent with economic theory, a higher regulatory quality and/or GDP per capita are associated with a higher credit rating.

Oligopoly Banking, Risky Investment, and Monetary Policy
Altermatt, Lukas,Wang, Zijian
Oligopolistic competition in the banking sector and risk in the real economy are important characteristics of developed economies, but so far they have mostly been abstracted from monetary models. We build a dynamic general equilibrium model of monetary policy transmission that incorporates both of these features. We document that including them leads to important insights in our understanding of the transmission mechanism. Various equilibrium cases can occur, and policies have differing effects in these cases. We also calibrate the model to the U.S. economy during 2016-2019. We find that doubling banking competition would have increased welfare by 1.02%, but at the cost of increasing the probability of bank default from 0.02% to 0.44%. We show that bank profits are increasing in the policy rate, in particular when interest rates are low. Finally, we find that monetary policy pass-through is incomplete under imperfect competition in the banking sector.

One semester, two languages: How to teach R and Python to business school students?
Yan, Yuxing
It is crazy to teach business students both R and Python at the same time! It was my thought when asked to teach such a course in 2020. However, after one-semester’s heavy struggle together with my students, I found that such a course is not only possible, but also desirable. In this paper, my teaching experiences are summarized into several areas: 1) write my own lecture notes; 2) use concepts and formulae suitable for business students; 3) tons of in-class exercises; 4) use the same formulae, data sets or even the same exercises several times; 5) recording my own video for each chapter even for a face-to-face lecture; 6) over 1,000 small programs; 7) many useful utility functions, and 8) teach R first, then compare Python with R constantly.

Parameterised-Response Zero-Intelligence Traders
Dave Cliff

I introduce PRZI (Parameterised-Response Zero Intelligence), a new form of zero-intelligence trader intended for use in simulation studies of auction markets. Like Gode & Sunder's classic Zero-Intelligence Constrained (ZIC) trader, PRZI generates quote-prices from a random distribution over some specified domain of discretely-valued allowable quote-prices. Unlike ZIC, which uses a uniform distribution to generate prices, the probability distribution in a PRZI trader is parameterised in such a way that its probability mass function (PMF) is determined by a real-valued control variable s in the range [-1.0, +1.0] that determines the strategy for that trader. When s is zero, a PRZI trader behaves identically to the ZIC strategy, with a flat/rectangular PMF; but when s is close to plus or minus one the PRZI trader's PMF becomes asymptotically maximally skewed to one extreme or the other of the price-range, thereby enabling the PRZI trader to act in the same way as the "Shaver" strategy (SHVR) or the "Giveaway" strategy (GVWY), both of which have recently been demonstrated to be surprisingly dominant over more sophisticated, and supposedly more profitable, trader-strategies that incorporate adaptive mechanisms and machine learning. Depending on the value of s, a PRZI trader will behave either as a ZIC, or as a SHVR, or as a GVWY, or as some hybrid strategy part-way between two of these three previously-reported strategies. The novel smoothly-varying strategy in PRZI has value in giving trader-agents plausibly useful "market impact" responses to imbalances in an auction-market's limit-order-book, and also allows for the study of co-adaptive dynamics in continuous strategy-spaces rather than the discrete spaces that have traditionally been studied in the literature.

Power-law Portfolios
Jan Rosenzweig

Portfolio optimization methods suffer from a catalogue of known problems, mainly due to the facts that pair correlations of asset returns are unstable, and that extremal risk measures such as maximum drawdown are difficult to predict due to the non-Gaussianity of portfolio returns. \\ In order to look at optimal portfolios for arbitrary risk penalty functions, we construct portfolio shapes where the penalty is proportional to a moment of the returns of arbitrary order $p>2$. \\ The resulting component weight in the portfolio scales sub-linearly with its return, with the power-law $w \propto \mu^{1/(p-1)}$. This leads to significantly improved diversification when compared to Kelly portfolios, due to the dilution of the winner-takes-all effect.\\ In the limit of penalty order $p\rightarrow\infty$, we recover the simple trading heuristic whereby assets are allocated a fixed positive weight when their return exceeds the hurdle rate, and zero otherwise. Infinite order power-law portfolios thus fall into the class of perfectly diversified portfolios.

Private Retirement Systems and Sustainability: Insights from Australia, the UK, and the US
Working Papers, PRC,Fabian, Nathan,Homanen, Mikael,Pedersen, Nikolaj,Slebos, Morgan
Retirement system sustainability is defined as the ability of plan boards and managers to be responsible investors, active stewards, and allocators of capital to economic activities with desirable social and environmental outcomes. In this paper, we examine the policy frameworks and important structural variables pertinent to private retirement systems in Australia, the UK, and the US. By analyzing various reports, interviewing experts, and using data from the Principles of Responsible Investment as well as national pension and retirement authorities, we identify key structural challenges within national retirement systems. These include market fragmentation, principal-agent conflicts in personal pensions, and the role of service providers. Our results provide insight into how, or whether, retirement systems can facilitate desirable economic, social, and environmental outcomes.

Re-Examining Board Reforms and Firm Value: Response to “How Much Should We Trust Staggered Differences-in-Differences Estimates?” by Baker, Larcker, and Wang (2021)
Fauver, Larry,Hung, Mingyi,Li, Xi,Taboada, Alvaro G.
Using board reforms in 41 countries and staggered difference-in-differences (DiD) estimates, Fauver, Hung, Li, and Taboada (2017, FHLT) find that firm value increases following the reforms. In a study that reviews the recent econometric theory on staggered DiD estimations, Baker, Larcker, and Wang (2021, BLW) contest the robustness of FHLT’s results. They conclude that FHLT’s results become mostly insignificant using alternative approaches that address the biases suggested by this recent theory. However, we find that the insignificant findings in BLW’s analysis are largely due to selective modifications that BLW made to FHLT’s data and model specifications, which resulted in low power tests. Importantly, these changes, which were not transparently disclosed in BLW, largely explain the insignificant results reported in BLW, even before implementing the new econometric approaches. Thus, in this study, we perform a battery of tests that apply alternative approaches that address the biases suggested in this recent literature. In contrast to the conclusions in BLW, we find that FHLT’s results remain significant. Our findings reinforce the conclusion of FHLT that board reforms increase firm value and highlight the importance of fair data representation when applying modified staggered DiD methods.

Risk-managed Collective Pension Schemes with Intergenerational Benefit Smoothing
Berninger, Christoph,Mittnik, Stefan
In view of the repeated severe market downturns since the turn of the century, the interest in risk-based investment strategies has grown in recent years. However, such strategies have not yet made major inroads into the design of pension programs. In this paper, we fill this gap by combining a risk-managed investment strategy with a pension scheme where benefits are smoothed across generations by establishing a collective reserve. We demonstrate that combining the two helps to improve the performance of the pension investments and decreases the risk of a negative reserve in times of a market crisis. We furthermore investigate the implications of imposing varying degrees of diversification across assets in such a scheme.

Shadow Bank and Fintech Mortgage Securitization
An, Yu,Li, Lei,Song, Zhaogang
Agency MBS issuers can choose among three securitization venues: individual securitization where an issuer uses her own loans to create an MBS, collective securitization where different issuers deliver loans into a common MBS, and cash window where issuers receive immediate cash payment by selling loans to Fannie Mae or Freddie Mac, who then conduct securitization. We find that issuers with greater immediate liquidity needs (e.g., smaller issuers and shadow banks) have a larger fraction of their loans securitized through cash window. The uniform pricing feature of collective securitization results in cross-subsidy from traditional banks, who have relatively high-value loans, to shadow banks, especially fintech issuers, who have relatively low-value loans; hence, shadow banks and traditional banks prefer collective and individual securitization, respectively. We further show that securitization venues affect the quality and quantity of loans that issuers securitize, using Fannie Mae's policy shock on collective securitization and the COVID-19 shock on cash window.

Sowing the Seeds of Financial Crises: Endogenous Asset Creation and Adverse Selection
Caramp, Nicolas
What sows the seeds of financial crises, and what policies can help avoid them? I model the interaction between the ex-ante production of assets and ex-post adverse selection in financial markets. Positive shocks that increase market prices exacerbate the production of low-quality assets and can increase the likelihood of a financial market collapse. The interest rate and the liquidity premium are endogenous and depend on the functioning of financial markets as well as the total supply of assets (private and public). Optimal policy balances the economy's liq- uidity needs ex-post with the production incentives ex-ante, and it can be implemented with three instruments: government bonds, asset purchase programs, and transaction taxes. Pub- lic liquidity improves incentives but implies a higher deadweight loss than private market interventions. Optimal policy does not rule out private market collapses but mitigates the fluctuations in the total liquidity.

The Effects of COVID-19 and Continuous Auditing on Employees' Compliance with the Internal Control System: The Moderating Role of Conscientiousness
Eulerich, Marc,Lopez-Kasper, Vanessa,S. Sofla, Amin
The trend towards continuous auditing of business operations is growing. In economically demanding times, organizations aim to improve compliance with internal controls. Our study investigates whether continuous auditing and a (COVID19) crisis situation interact with the personality trait conscientiousness among auditees to influence compliance with internal controls. We conducted a between-subjects experiment manipulating audit frequency (continuous vs. traditional audit) and the current business situation (business as usual vs. crisis) and received 125 complete responses from sales professionals. We found that the effect of a crisis situation on the likelihood to engage in non-compliance with internal controls is conditional on conscientiousness, while continuous auditing does not seem to interact with the trait of conscientiousness. Specifically, we observe that less conscientious individuals who are operating under a crisis condition and continuously audited are likelier to engage in non-compliance with internal controls. In contrast, individuals with a high level of conscientiousness were more likely to comply with internal controls when continuously audited in the context of a crisis.