# Research articles for the 2020-12-09

A Stabilization Fund for Countries Facing Market Turmoil
Walker, Mark,Canavan, Chris
SSRN
A state-contingent financing facility would be an effective way to help mediate the economic and financial shocks resulting from the COVID-19 pandemic. An SSB could mobilize large amounts of financial resources from the international capital markets and provide cash flow relief to sovereign debtors without market access on attractive terms that reflect both a countryâ€™s liquidity requirements and its ability to service its obligations without adding to financial stress. A synthetic stabilization fund (SSB) sponsored by a credible official sector institution could provide state-contingent financing much like traditional stabilization funds. Thus, the amount and timing of funds available to a country, as well as the amount and timing of repayment should be linked to the performance of a proxy for a countryâ€™s financial position, such as commodity prices or export revenues. Unlike a traditional stabilization fund, the initial capital of an SSB would be raised in the private markets with credit support from official and bilateral sources to assure long-term funding at reasonable cost.

A q Theory of Internal Capital Markets
Dai, Min,Giroud, Xavier,Jiang, Wei,Wang, Neng
SSRN
We propose a tractable model of dynamic investment, division sales (spinoffs), financing, and risk management for a multi-division firm that faces costly external finance. The model highlights the importance of considering the intertwined nature of the different policies. Our main results are as follows: (1) risk management considerations prescribe the allocation of resources based not only on the divisions' productivity â€" as in standard models of ''winner picking'' â€" but also their risk; (2) firms may choose to voluntarily spin off productive divisions to increase liquidity; (3) diversification can reduce firm value especially in low liquidity states, as it increases the cost of a spinoff and hampers liquidity management; (4) with corporate socialism, liquidity is less valuable since it is less costly to replenish the firm's liquidity through a spinoff; and (5) division-level investment is set such that the ratio between marginal q and the marginal cost of investing in each division equals the marginal value of cash.

An SPV for Countries Lacking Normal Market Access
Walker, Mark,Canavan, Chris
SSRN
Many emerging market countries are facing urgent liquidity needs in light of economic and financial shocks resulting from the COVID-19 pandemic. Official resources by themselves have been insufficient to meet needs and should be complemented by private resources at reasonable cost. To overcome credit concerns that restrict availability of private capital and are reflected in costly, and for many sovereign borrowers, unaffordable market pricing, it would be useful to establish a vehicle that can mobilize large amounts of financial resources from the international capital markets and provide cash flow relief on favorable terms and on relatively short notice to countries lacking normal market access. An SPV sponsored by a credible official sector institution, funded by private creditors and backed by credit enhancement from official and bilateral creditors serve an important need.

An unsupervised deep learning approach in solving partial-integro differential equations
Ali Hirsa,Weilong Fu
arXiv

We investigate solving partial integro-differential equations (PIDEs) using unsupervised deep learning in this paper. To price options, assuming underlying processes follow \levy processes, we require to solve PIDEs. In supervised deep learning, pre-calculated labels are used to train neural networks to fit the solution of the PIDE. In an unsupervised deep learning, neural networks are employed as the solution, and the derivatives and the integrals in the PIDE are calculated based on the neural network. By matching the PIDE and its boundary conditions, the neural network gives an accurate solution of the PIDE. Once trained, it would be fast for calculating options values as well as option \texttt{Greeks}.

Asset Pricing in the Middle Eastâ€™s Equity Markets
Hearn, Bruce Allen,Li, Jing,Mykhayliv, Dariya,Waqas, Muhammad
SSRN
This paper undertakes a comparison between five multifactor variants of the capital asset pricing model, where this is augmented by size, book to market value, momentum, liquidity and a new investor protection metric based on the product of institutional quality in a country and the proportion of free float shares, which captures the impact of controlling block holders. Using monthly returns of 909 blue chip firms from 16 Middle East & North African equity markets for 16 years, we show that a two factor CAPM augmented with a factor mimicking portfolio based on the investor protection metric yields the highest explanatory power. Analysis of Kalman filter time varying investor protection betas reveals investor protection premiums in Egypt, Iraq, Lebanon and Tunisia and corresponding discounts in Israel, Saudi Arabia, Kuwait, Oman, Dubai and Abu Dhabi.

Divided We Fall
Livnat, Joshua,Rubin, Amir,Segal, Dan
SSRN
We analyze the effects of partisan Congressional control on the US economy. We find that economic performance is weaker when no party has the majority in both chambers of Congress (divided Congress). This weaker economic performance is attributed to reduced and less effective regulation. We provide evidence that undivided Congresses, whether Democrat or Republican, tend to enhance economic performance. Republicans seem to create value for large firms, whereas Democrats enhance competition and create value for small firms. Overall, we conclude that congressional cycles and effective regulation are important drivers of economic activity.

Dynamic complementarity in skill production: Evidence from genetic endowments and birth order
Dilnoza Muslimova,Hans van Kippersluis,Cornelius A. Rietveld,Stephanie von Hinke,S. Fleur W. Meddens
arXiv

The birth order literature emphasizes the role of parental investments in explaining why firstborns have higher human capital outcomes than their laterborn siblings. We use birth order as a proxy for investments and interact it with genetic endowments. Exploiting only within-family variation in both ensures they are exogenous as well as orthogonal to each other. As such, our setting is informative about the existence of dynamic complementarity in skill production. Our empirical analysis exploits data from 15,019 full siblings in the UK Biobank. We adopt a family-fixed effects strategy combined with instrumental variables to deal with endogeneity issues arising from omitted variables and measurement error. We find that birth order and genetic endowments interact: those with above-average genetic endowments benefit disproportionally more from being firstborn compared to those with below-average genetic endowments. This finding is a clean example of how genetic endowments (nature) and the environment (nurture) interact in producing educational attainment. Moreover, our results are consistent with the existence of dynamic complementarity in skill formation: additional parental investments associated with being firstborn are more effective for those siblings who randomly inherited higher genetic endowments for educational attainment.

Economic Costs of Climate Change
Custodio, Claudia,Ferreira, Miguel A.,Garcia-Appendini, Emilia,Lam, Adrian
SSRN
We estimate the economic costs of climate change by exploiting production networks. Specifically, we estimate the impact of changes in local temperature by comparing sales of intermediate goods across suppliers located in different regions that are selling to the same client. We find that a 1Â°C increase in average daily temperature leads to a reduction in supplier sales of about 2%. The effect is more pronounced among suppliers in manufacturing and heat-sensitive industries, which is consistent with reduced labor supply when temperatures are higher. Financially constrained and small firms are more affected, which suggests that these firms have difficulties to adapt to changes in temperatures. We also find that episodes of extremely hot and cold weather lead to significantly stronger reductions in sales. Our results suggest that the supply-side effects of climate change are large.

Error estimates for discrete approximations of game options with multivariate diffusion asset prices
Yuri Kifer
arXiv

We obtain error estimates for strong approximations of a diffusion with a diffusion matrix $\sigma$ and a drift b by the discrete time process defined recursively X_N((n+1)/N) = X_N(n/N)+N^{1/2}\sigma(X_N(n/N))\xi(n+1)+N^{-1}b(XN(n/N)); where \xi(n); n\geq 1 are i.i.d. random vectors, and apply this in order to approximate the fair price of a game option with a diffusion asset price evolution by values of Dynkin's games with payoffs based on the above discrete time processes. This provides an effective tool for computations of fair prices of game options with path dependent payoffs in a multi asset market with diffusion evolution.

Jang, Young Soo
SSRN
Using a proprietary data set of private credit agreements, I document five facts about a previously unexplored segment of the US corporate debt market: nonbank direct lending to private equity (PE) middle-market buyouts. First, PE-backed middle-market firms have high cash flow, low liquidation value of tangible assets, and exhibit strong (weak) dependence of debt capacity to cash flow (liquidation value). Second, these features are stronger for those borrowing using direct loans despite their being smaller in size. Third, direct loans face markedly higher annual borrowing costs that are over 300 basis points higher than on comparable bank loans. Fourth, direct loans instead have a much more borrower-friendly covenant structure. Fifth, borrowers of direct loans find covenant violation costly, for it may constrain future borrowing. These findings suggest that small firms are not limited to asset-based bank debt and can rely heavily on cash flow-based debt. Further, direct lenders can provide more flexible solutions to PE sponsors in exchange for greater cash flow rights without compromising ex-post enforcement of contractual rights. Overall, this paper raises important questions for research in the growing literature on shadow banking.

Green Accounting and Finance: Advancing Research on Environmental Disclosure, Value Impacts and Management Control Systems
Brooks, Chris,Schopohl, Lisa
SSRN
In recent decades, the business world â€" as well as society at large â€" has increasingly recognised the relevance of environmental factors as essential determinants of economic development and business decisions. Due to these short- and long-term effects of environmental factors on both the corporate and financial sectors, it is clear that business leaders and investors need to measure and manage these environmental risks as well as channel capital flows towards tackling the impact of such risks on business and society. As academic disciplines, accounting and finance play a key role in these efforts and are ideally placed to develop innovative approaches to incorporate environmental factors into accounting and risk management frameworks and to evaluate solutions to mobilise capital flows and finance the transition to a low-carbon and environmentally sustainable economy. This paper provides the editorial for a special issue in the British Accounting Review that aims to contribute to these important debates by offering new insights into three key areas of green finance and accounting research: firmsâ€™ environmental disclosure choices, the value impact of climate change and carbon emissions, and the latest research into environmental management control systems.

Modeling asset allocation strategies and a new portfolio performance score
Apostolos Chalkis,Ioannis Z. Emiris
arXiv

We discuss a powerful, geometric representation of financial portfolios and stock markets, which identifies the space of portfolios with the points lying in a simplex convex polytope. The ambient space has dimension equal to the number of stocks, or assets. Although our statistical tools are quite general, in this paper we focus on the problem of portfolio scoring. Our contribution is to introduce an original computational framework to model portfolio allocation strategies, which is of independent interest for computational finance. To model asset allocation strategies, we employ log-concave distributions centered on portfolio benchmarks. Our approach addresses the crucial question of evaluating portfolio management, and is relevant to the individual private investors as well as financial organizations. We evaluate portfolio performance, in a certain time period, by providing a new portfolio score, based on the aforementioned framework and concepts. In particular, it relies on the expected proportion of allocations that the portfolio outperforms when a certain set of strategies take place in that time period. We also discuss how this set of strategies -- and the knowledge one may have about them -- could vary in our framework, and we provide additional versions of our score in order to obtain a more complete picture of its performance. In all cases, we show that the score computations can be performed efficiently. Last but not least, we expect this framework to be useful in portfolio optimization and in automatically identifying extreme phenomena in a stock market.

Neural Jump Ordinary Differential Equations
Calypso Herrera,Florian Krach,Josef Teichmann
arXiv

Combinations of neural ODEs with recurrent neural networks (RNN), like GRU-ODE-Bayes or ODE-RNN are well suited to model irregularly observed time series. While those models outperform existing discrete-time approaches, no theoretical guarantees for their predictive capabilities are available. Assuming that the irregularly-sampled time series data originates from a continuous stochastic process, the $L^2$-optimal online prediction is the conditional expectation given the currently available information. We introduce the neural jump ODE (NJ-ODE) that provides a data-driven approach to learn, continuously in time, the conditional expectation of a stochastic process. Our approach models the conditional expectation between two observations with a neural ODE and jumps whenever a new observation is made. We define a novel training framework, which allows us to prove theoretical guarantees for the first time. In particular, we show that the output of our model converges to the $L^2$-optimal prediction. We provide experiments showing that the theoretical results also hold empirically. Moreover, we experimentally show that our model outperforms the baselines in more complex learning tasks and give comparisons on real-world datasets.

On Cryptocurrencies as an Independent Asset Class: Long-Horizon and COVID-19 Pandemic Era Decoupling from Global Sentiments
Sifat, Imtiaz
SSRN
We report new evidence that the cryptocurrency market behaves as an independent asset class based on high-dimensional stochastic-volatility commonality tests against a basket of global investor sentiment proxies. Our approachâ€™s novelty resides in employment of appropriate sources of risk and uncertainty and two comprehensive indices (CRIX and VCRIX) that permit treating cryptocurrencies as a united pool from 2016 to 2020. Our consolidated findings suggest nugatory association between cryptocurrencies and global risk, risk aversion, and uncertainty. Further investigation of the COVID-19 pandemic period reinforces the long-horizon results.

Parametric measures of variability induced by risk measures
arXiv

We study general classes of parametric measures of variability with applications in risk management. Particular focus is put on variability measures induced by three classes of popular risk measures: the Value-at-Risk, the Expected Shortfall, and the expectiles. Properties of these variability measures are explored in detail, and a characterization result is obtained via the mixture of inter-ES differences. Convergence properties and asymptotic normality of their empirical estimators are established. We provide an illustration of the three classes of variability measures applied to financial data and analyze their relative advantages.

Risk Exposure and Acquisition of Macroeconomic Information
Roth, Christopher,Settele, Sonja,Wohlfart, Johannes
SSRN
We conduct an experiment with a representative sample from the US to study householdsâ€™ demand for macroeconomic information. Respondents who learn of a higher personal exposure to unemployment risk during recessions increase their demand for an expert forecast about the likelihood of a recession. Our findings are consistent with the basic premise of theories of rational inattention that demand for information depends on its expected benefit. Moreover, the fact that perceived risk exposure responds to information highlights frictions in householdsâ€™ knowledge about the personal relevance of particular pieces of information. Our findings inform the modeling of information frictions in macroeconomics.

Section 529 Plan Distributions and College Refunds for COVID-19
Riskin, Ross
SSRN
Tax planning and compliance challenges may arise for taxpayers who utilize 529 plans to pay for qualifying education expenses and subsequently receive refunds as a result of COVID-19. This article examines the scenarios taxpayers may be faced with and options available to help preserve the tax-efficiency of these plans and distributions made during college years.

T\^atonnement, Approach to Equilibrium and Excess Volatility in Firm Networks
Théo Dessertaine,José Moran,Michael Benzaquen,Jean-Philippe Bouchaud
arXiv

We study the conditions under which input-output networks can dynamically attain competitive equilibrium, where markets clear and profits are zero. We endow a classical firm network model with simple dynamical rules that reduce supply/demand imbalances and excess profits. We show that the time needed to reach equilibrium diverges as the system approaches an instability point beyond which the Hawkins-Simons condition is violated and competitive equilibrium is no longer realisable. We argue that such slow dynamics is a source of excess volatility, through accumulation and amplification of exogenous shocks. Factoring in essential physical constraints, such as causality or inventory management, we propose a dynamically consistent model that displays a rich variety of phenomena. Competitive equilibrium can only be reached after some time and within some region of parameter space, outside of which one observes periodic and chaotic phases, reminiscent of real business cycles. This suggests an alternative explanation of the excess volatility that is of purely endogenous nature. Other regimes include deflationary equilibria and intermittent crises characterised by bursts of inflation. Our model can be calibrated using highly disaggregated data on individual firms and prices, and may provide a powerful tool to describe out-of-equilibrium economies.

The Effect of â€˜Brexitâ€™ Uncertainty on the FTSE 100 Index and the UK Pound
McCann, Rory,Broby, Daniel
SSRN
We investigate the impact of the uncertainty surrounding the United Kingdomâ€™s proposed departure from the European Community (â€œBrexitâ€) on financial assets. We conduct an event study around the November 14th 2018 draft withdrawal agreement. Our motivation was that the economic impact of the various political permutations that persisted throughout the negotiation period were both measurable and distinct. The probability of each Brexit scenario that was discussed varied over the political discourse. Using opinion poll data we investigate the event impact on both the FTSE 100 and the UK Pound. We found that, in accordance with existing academic evidence, asset prices discounted the weighted probabilistic economic impact of likely outcomes. We observe, however, that this impact was not as immediate as theory suggests. Interestingly, currency markets had the greater sensitivity. Our conclusions have important implications for the pricing of country risk premia in general and the European Union in particular.

The Impact of Balance Sheet Lending versus Securitization Booms on the Severity of the Great Recession
Zink, David
SSRN
I separately estimate the effect of local credit booms driven by balance sheet lending and those driven by securitization during the 2002-2006 period on the severity of the 2007-2009 recession in the United States. I construct a novel dataset, linking publicly available data on residential mortgage originations from the Home Mortgage Disclosure Act together with bank financial statements and county level economic outcomes. I exploit geographic variation in bank origination activity across counties to construct county level measures of exposure to securitization and balance sheet lending activity during the 2002-2006 period that are orthogonal to local economic conditions. Results show that 2002-2006 securitization exposure is predictive of sharper declines in home prices, employment, and a rise in mortgage delinquencies during the subsequent crisis period. The same is not true for balance sheet lending, which does not affect crisis period home prices and generates a drop in employment that is confined to the nontradable sector. Results suggest that this difference is driven by risk taking that is specific to securitized lending. Balance sheet booms generate an expansion in lending to higher quality borrowers, while securitization booms increase credit availability at the lower end of the credit distribution.

The Impact of Personality Traits on Attitude to Financial Risk
Brooks, Chris,Williams, Louis
SSRN
While the effects of emotions on attitudes to investment risk are now well documented, the influence of personality factors has been much less researched. This paper examines the role of personality traits in determining financial risk tolerance. Using an extensive survey of UK-based retail investors, we show that personality traits and characteristics are more important than emotions in determining attitude to risk. We also observe that the widely adopted â€˜Big Fiveâ€™ framework is insufficient to characterise this relationship adequately, with significant roles for financial self-efficacy, resilience, trait anger and intolerance of uncertainty. Since some of these characteristics can be modified, our findings are suggestive that appropriate training and support for those making financial decisions could lead to better outcomes over the longer term.

The Impact of the Institutional Environment on Analystsâ€™ Herding Behavior: Evidence from Broker Acquisitions
Fiechter, Peter,Mangeney, Louis
SSRN
We examine the influence of institutional factors on herding behavior by exploring changes in security analystsâ€™ institutional environments. Specifically, we identify analysts employed at privately held brokers subsequently acquired by a publicly listed institution (hereafter, â€œtreated analystsâ€). We posit that, after the treatment, analysts are less independent (e.g., due to increased peer pressure or more regulated environments), and thus they issue more herding forecasts. Using a staggered difference-in-differences design, we find that treated analysts issue significantly more herding forecasts in the post-treatment period. In contrast, we do not find a change in herding behavior for analysts subject to acquisitions by non-public brokers, indicating that the institutional change from private to public, not the acquisition per se, drives our inferences. Consistent with the decreasing independency explanation, we find stronger treatment effects for less experienced analysts, more substantial organizational changes, institutional changes associated with higher job uncertainty, and in periods of stricter regulation of public institutions. Taken together, our findings suggest a causal link between the institutional environment and herding behavior.

The More We Know, the Less We Agree: A Test of the Trading Horizon Heterogeneity Theory
Dai, Lili,Parwada, Jerry T.,Winchester, Donald W.,Zhang, Bohui
SSRN
This paper examines the Kondor (2012) theoretical explanation of an enduring puzzle: trading volumes and stock return volatility peak after the release of public information. Using a comprehensive data set of institutional holdings and earnings announcements, we find supporting evidence that the proportion of short-term investors is positively associated with post-announcement spikes in trading volume and return volatility. This finding survives in the identification test based on the annual reconstitutions of the Russell 1000 and 2000 indices. We show our results largely withstand several alternative explanations related to the constitution of institutional investors, informed trading, and heterogeneous beliefs.

The relative impact of private research on scientific advancement
Giovanni Abramo,Ciriaco Andrea D'Angelo,Flavia Di Costa
arXiv

Literature about the scholarly impact of scientific research offers very few contributions on private sector research, and the comparison with public sector. In this work, we try to fill this gap examining the citation-based impact of Italian 2010-2017 publications distinguishing authorship by the private sector from the public sector. In particular, we investigate the relation between different forms of collaboration and impact: how intra-sector private publications compare to public, and how private-public joint publications compare to intra-sector extramural collaborations. Finally, we assess the different effect of international collaboration on private and public research impact, and whether there occur differences across research fields.

The use of scaling properties to detect relevant changes in financial time series: a new visual warning tool
Ioannis P. Antoniades,Giuseppe Brandi,L. G. Magafas,T. Di Matteo
arXiv

The dynamical evolution of multiscaling in financial time series is investigated using time-dependent Generalized Hurst Exponents (GHE), $H_q$, for various values of the parameter $q$. Using $H_q$, we introduce a new visual methodology to algorithmically detect critical changes in the scaling of the underlying complex time-series. The methodology involves the degree of multiscaling at a particular time instance, the multiscaling trend which is calculated by the Change-Point Analysis method, and a rigorous evaluation of the statistical significance of the results. Using this algorithm, we have identified particular patterns in the temporal co-evolution of the different $H_q$ time-series. These GHE patterns, distinguish in a statistically robust way, not only between time periods of uniscaling and multiscaling, but also among different types of multiscaling: symmetric multiscaling (M) and asymmetric multiscaling (A). We apply the visual methodology to time-series comprising of daily close prices of four stock market indices: two major ones (S\&P~500 and NIKKEI) and two peripheral ones (Athens Stock Exchange general Index and Bombay-SENSEX). Results show that multiscaling varies greatly with time: time periods of strong multiscaling behavior and time periods of uniscaling behavior are interchanged while transitions from uniscaling to multiscaling behavior occur before critical market events, such as stock market bubbles. Moreover, particular asymmetric multiscaling patterns appear during critical stock market eras and provide useful information about market conditions. In particular, they can be used as 'fingerprints' of a turbulent market period as well as provide warning signals for an upcoming stock market 'bubble'. The applied visual methodology also appears to distinguish between exogenous and endogenous stock market crises, based on the observed patterns before the actual events.

Top of the Batch: Interviews and the Match
Federico Echenique,Ruy Gonzalez,Alistair Wilson,Leeat Yariv
arXiv

Most doctors in the NRMP are matched to one of their most-preferred internship programs. Since various surveys indicate similarities across doctors' preferences, this suggests a puzzle. How can nearly everyone get a position in a highly-desirable program when positions in each program are scarce? We provide one possible explanation for this puzzle. We show that the patterns observed in the NRMP data may be an artifact of the interview process that precedes the match. Our analysis highlights the importance of interactions occurring outside of a matching clearinghouse for resulting outcomes, and casts doubts on analysis of clearinghouses that take reported preferences at face value.

What Drives Asset Holdings? Commonality in Investor Demand
BÃ¼chner, Matthias
SSRN
I empirically show that changes in investor holdings exhibit a low-dimensional factor structure that is economically interpretable. Using an extended version of Instrumented Principal Components Analysis (IPCA), I model changes in a large sample of sector-level investor holdings and recover latent factors and sector-specific loadings on the factors. I find that the recovered factors reflect the state of the macroeconomy and financial constraints of investors. Investor loadings on the factors reveal partially pro-cyclical trading behavior of the banking sector and of mutual funds, while hedge funds and pension funds act partially counter-cyclically. In addition, I document that the set of characteristics relevant for explaining changes in holdings is likely wider than implied by common risk factor models. Finally, using the decomposition of holdings changes implied by IPCA, I demonstrate asset pricing effects consistent with institutional price pressures from banks and mutual funds, as well as market-timing ability of investment advisors that is unrelated to common asset characteristics.

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Kondratjev, Alexey
SSRN
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