Research articles for the 2021-03-02

(In)Stability for the Blockchain: Deleveraging Spirals and Stablecoin Attacks
Ariah Klages-Mundt,Andreea Minca
arXiv

We develop a model of stable assets, including non-custodial stablecoins backed by cryptocurrencies. Such stablecoins are popular methods for bootstrapping price stability within public blockchain settings. We derive fundamental results about dynamics and liquidity in stablecoin markets, demonstrate that these markets face deleveraging feedback effects that cause illiquidity during crises and exacerbate collateral drawdown, and characterize stable dynamics of the system under particular conditions. The possibility of such `deleveraging spirals' was first predicted in the initial release of our paper in 2019 and later directly observed during the `Black Thursday' crisis in Dai in 2020. From these insights, we suggest design improvements that aim to improve long-term stability. We also introduce new attacks that exploit arbitrage-like opportunities around stablecoin liquidations. Using our model, we demonstrate that these can be profitable. These attacks may induce volatility in the `stable' asset and cause perverse incentives for miners, posing risks to blockchain consensus. A variant of such attacks also later occurred during Black Thursday, taking the form of mempool manipulation to clear Dai liquidation auctions at near zero prices, costing $8m.



A Semiparametric Model for Bond Pricing with Life Cycle Fundamental
Cai, Zongwu,Chen, Jiazi,Niu, Linlin
SSRN
It is well documented in the literature that individual saving decisions vary with the life cycle and at the macroeconomic level, a changing demographic age structure affects aggregated savings, which then drives a slow movement of interest rates. In this paper, we propose a semiparametric affine arbitrage-free yield curve model with a low-frequency trend structure driven by the entire age distribution through a life cycle impact function. The unified framework not only fully explores the demographic age structure to robustly explain yield trend, but also utilizes efficiently the interest rate term structure to infer the S-shaped age impact function of the whole life cycle. We estimate the model with quarterly U.S. data from 1950s to present. The results show clearly that the model fits U.S. Treasury yields remarkably well in sample and outperforms popular alternative models out of sample. After removing the demography-driven trend especially pertaining to the baby boomer’s life cycle, the remaining term structure component is stationary with counter-cyclical risk premia.

A combinatorial optimization approach to scenario filtering in portfolio selection
Justo Puerto,Federica Ricca,Moisés Rodríguez-Madrena,Andrea Scozzari
arXiv

Recent studies stressed the fact that covariance matrices computed from empirical financial time series appear to contain a high amount of noise. This makes the classical Markowitz Mean-Variance Optimization model unable to correctly evaluate the performance associated to selected portfolios. Since the Markowitz model is still one of the most used practitioner-oriented tool, several filtering methods have been proposed in the literature to fix the problem. Among them, the two most promising ones refer to the Random Matrix Theory or to the Power Mapping strategy. The basic idea of these methods is to transform the correlation matrix maintaining the Mean-Variance Optimization model. However, experimental analysis shows that these two strategies are not adequately effective when applied to real financial datasets.

In this paper we propose an alternative filtering method based on Combinatorial Optimization. We advance a new Mixed Integer Quadratic Programming model to filter those observations that may influence the performance of a portfolio in the future. We discuss the properties of this new model and we test it on some real financial datasets. We compare the out-of-sample performance of our portfolios with the one of the portfolios provided by the two above mentioned alternative strategies. We show that our method outperforms them. Although our model can be solved efficiently with standard optimization solvers the computational burden increases for large datasets. To overcome this issue we also propose a heuristic procedure that empirically showed to be both efficient and effective.



Ambiguity and Retained Earnings
Amira, Khaled,Muzere, Mark Legge,Tsafack, Georges
SSRN
We investigate the implications of ambiguity aversion for retained earnings. We show that firms can eliminate distortions such as underinvestment by paying out earnings that maximizes shareholder wealth. We show that there is a negative relationship between ambiguity and retained earnings and argue that it is different from the positive relationship between retained earnings and volatility obtained in the literature. Firms pay out part of their earnings to attract ambiguity averse investors to their equity markets. We test our results and find strong and robust empirical support

Ambiguity, Nominal Bond Yields, and Real Bond Yields
Zhao, Guihai
SSRN
This paper presents an equilibrium bond-pricing model that jointly explains the upward-sloping nominal and real yield curves and the violation of the expectations hypothesis. Instead of relying on the inflation risk premium, the ambiguity-averse agent faces different amounts of Knightian uncertainty in the long run versus the short run; hence the model-implied nominal and real short rate expectations are upward-sloping under the agent’s worst-case equilibrium beliefs. The expectations hypothesis roughly holds under investors’ worst-case beliefs. The difference between the worst-case scenario and the true distribution makes realized excess returns on long term bonds predictable.

Antigone versus Creon: Hölderlin, Brecht, and a Game-theoretical Exercise
Holler, Manfred,Tridimas, George
SSRN
We take a fresh look at Sophocles’ Antigone by applying a game theoretic analysis â€" asking whether Antigone was trapped by Creon or whether Creon was trapped by Antigone. Creon, occupant of the throne of Thebes seeking to consolidate his rule decrees that Polynices, his defeated enemy, must remain unburied and un-mourned and that violators will be punished by death. Antigone, Polynices sister and Creon’s niece, with a strong claim to the throne herself, challenges the decree and administers the burial rituals for her brother. When found out, she commits suicide not knowing that Creon has previously repealed his decree. On the other hand, Creon retracted the harsh punishment before hearing of Antigone’s death. We rely on a number of translations of the play to construct and illustrate the interdependence between the decisions of Creon and Antigone and explore their dominant strategies and possible equilibria of the game. A discussion of Bertolt Brecht’s Antigone demonstrates the timelessness and universality of Sophocles’ Antigone.

Bandits in Matching Markets: Ideas and Proposals for Peer Lending
Soumajyoti Sarkar
arXiv

Motivated by recent applications of sequential decision making in matching markets, in this paper we attempt at formulating and abstracting market designs for P2P lending. We describe a paradigm to set the stage for how peer to peer investments can be conceived from a matching market perspective, especially when both borrower and lender preferences are respected. We model these specialized markets as an optimization problem and consider different utilities for agents on both sides of the market while also understanding the impact of equitable allocations to borrowers. We devise a technique based on sequential decision making that allow the lenders to adjust their choices based on the dynamics of uncertainty from competition over time and that also impacts the rewards in return for their investments. Using simulated experiments we show the dynamics of the regret based on the optimal borrower-lender matching and find that the lender regret depends on the initial preferences set by the lenders which could affect their learning over decision making steps.



Bitcoin Nation: The World’s New 17th Largest Economy
Taskinsoy, John
SSRN
Suppose there is Bitcoin nation and its currency bitcoin; with market capitalization of $1.086 trillion on 21 February 2021, Bitcoin’s market value (17th among G20) has surpassed GDPs of Netherlands ($909 billion), Saudi Arabia ($793 billion), Turkey ($754 billion), and Switzerland ($703 billion). This historic milestone was still not enough to convince opponents who claim that Bitcoin is associated with extremely volatility. Is this because of the inherent aspects of Bitcoin that cause volatility or is it due to the fact that regulators and law makers insist on running headlong into backlash to Bitcoin? But opponents clueless of the inner workings of money’s natural evolution along with short-sighted politicians lack the understanding that life-changing (revolutionary) technologies like blockchain and its prodigy Bitcoin will forge ahead unabated regardless of countless obstacles and challenges. Unlike the bursting of the Internet bubble (dot.com crisis) at the onset of the new millennium, Bitcoin will not disappear anytime soon, but regrettably will be susceptible to even more severe price corrections as long as the existing regulatory hurdle keeps curbing Bitcoin’s true potential. In the face of the U.S. raging a war against Bitcoin to protect the dollar’s “exorbitant privilege” and hegemony, Bitcoin has still achieved unthinkable price valuations (i.e. intraday high of $58,330 on February 21, 2021). In the absence of a regulatory hurdle, imagine what price levels Bitcoin may have achieved, $1,000,000? Raging a war against Bitcoin and altcoins can potentially have adverse effects on future developments of innovative technologies that are essential to building great civilizations.

Brexit, COVID-19, and Possible Frameworks for Future UK/EU Financial Governance Cooperation
Howell, Elizabeth
SSRN
The EU project is at an inflection point. Intra-EU alliances are altering in light of the UK’s departure, the EU’s financial markets remain segmented, and there is limited appetite for completing the Banking Union. The second stage of the Brexit negotiations also collided with the COVID-19 pandemic, a medical emergency that has placed economies around the world under tremendous strain. The combination of issues amounts to a ‘polycrisis’ for the EU, aspects of which raise existential questions about the future of the EU project.This article focuses on one strand of the debates generated within this polycrisis: future UK/EU policy cooperation with respect to financial governance; the mechanisms which support financial market regulation and supervision. The article discusses the importance of the financial services sector to the UK and the EU, and examines potential institutional options for future financial governance cooperation. In particular, the article advocates harnessing the dexterous aspects evident within precedents, including in existing EU/third country association agreements, to develop a functional arrangement for future financial governance cooperation. Such a framework could also lead to closer UK/EU cooperation than currently appears likely.

Climate Transition Risk in U.S. Loan Portfolios: Are All Banks the Same?
Nguyen, Quyen,Diaz-Rainey, Ivan,Kuruppuarachchi, Duminda,McCarten, Matthew,Tan, Eric K. M.
SSRN
We examine banks’ exposure to climate transition risk using a bottom-up, loan-level methodology incorporating climate stress test based on the Merton probability of default model and transition pathways from the IPCC. Specifically, we match machine learning predictions of corporate carbon footprints to syndicated loans initiated in 2010-2018 and aggregate these to loan portfolios of the twenty largest banks in the United States. Banks vary in their climate transition risk not only due to their exposure to the energy sectors but also due to borrowers’ carbon emission profiles from other sectors. Banks generally lend a minimal amount to coal (0.4%) but hold a considerable exposure in oil and gas (8.6%) and electricity firms (4.6%) and thus have a large exposure to the energy sectors (13.5%). We observe that climate transition risk profile was stable over time, save for a temporary (in some cases) and permanent (in others), reduction in their fossil-fuel exposure after the Paris Agreement. From the stress testing, the median loss is 0.5% of US syndicated loans, representing a decrease in CET1 capital of 4.1% but this may grow twice as large in the 1.5oC scenarios (1.4%-2.1% of loan value, 12%-16% of CET1 capital) compared to the 2oC target (0.6%-1.1% of loan value, 5%-9% of CET1 capital) with significant tail-end risk (7.7% of loan value, 62% of CET1 capital). Banks’ vulnerabilities are also driven by the ex-ante financial risk of their borrowers more generally, highlighting that climate risk is not independent from conventional risks.

Commentary on World Development Report 2020: Trading for Development in the Age of Global Value Chains
Rajkumar Byahut,Sourish Dutta,Chidambaran G. Iyer,Manikantha Nataraj
arXiv

The importance of trade to an economy needs no emphasis. You sell products or services that you are competitive at and buy those where you are not. Experience of countries such as South Korea and China demonstrate that resources required for development can be garnered through trade; thus, motivating many countries to embrace trade as a means for development. Simultaneously, emergence of 'Global Value Chain' or 'GVC' as they are popularly known has changed the way we trade. Though the concept of GVC was introduced in the early 2000s, there are examples of global value chains before the 1980s. However, the scale of the phenomenon and the way in which technological change, by lowering trade costs, has allowed fragmentation of production was not possible before (Hernandez et al., 2014). In this context, the World Bank has recently published its 'World Development Report 2020: Trading for Development in the Age of Global Value Chains' (WDR). The report prescribes that GVCs still offer developing countries a clear path to progress and that developing countries can achieve better outcomes by pursuing market-oriented reforms specific to their stage of development.



Comovements in Corporate Waves and the Monetary Policy
Colak, Gonul,Hasan, Iftekhar,Tekatli, Necati
SSRN
This paper analyses the comovements in corporate event waves and assesses the effects of monetary policy on creating the comovement dynamics. First, we trace the time-series properties of these waves and highlight their common statistical properties. Second, developing a novel Bayesian factor model based on these statistical similarities, we extract and examine the waves' common factors and common volatilities representing the comovements in corporate events. We observe that the variables closely associated with and under the influence of the monetary policy are highly related to the corporate event dynamics. Finally, we show that the Fed's policy actions and announcements as well as the resultant policy uncertainty drive a significant fraction of the comovements in corporate events, forming the basis for their common dynamics.

Confidence, Bond Risks, and Equity Returns
Zhao, Guihai
SSRN
I show that investor confidence (size of ambiguity) about future consumption growth is driven by past consumption growth and inflation. The impact of inflation on confidence has moved considerably over time and switched on average from negative to positive in 1997. Motivated by this evidence, I develop and estimate a model in which the confidence process has discrete regime shifts, and I find that the time-varying impact of inflation on confidence enables the model to match bond risks over different subperiods. The model can also account for stock and bond return predictability, and correlation between price-dividend ratios and inflation, among other features of the data.

Corporate Restructuring and Creditor Power: Evidence from European Insolvency Law Reforms
Closset, Frédéric,Großmann, Christoph,Kaserer, Christoph,Urban, Daniel
SSRN
In an attempt to match US bankruptcy law, many European countries have reformed their insolvency laws towards a regime that fosters corporate restructuring. This paper evaluates the implications of these reforms. Based on a staggered difference-in-differences analysis around eight insolvency reforms in 15 European countries, this paper finds a relative increase in the cost of debt by about 50 bps in countries with such a reform. The effect is more pronounced among firms being closer to default. As a result of increased cost of debt financing, firms cut investment and employee pay by about 2 percent. Overall, the results are consistent with the view that creditors may be negatively affected by insolvency law reforms oriented towards restructuring and, thus, demand higher risk premia.

Currency Carry Trades and Global Funding Risk
Nissinen, Juuso,Suominen, Matti,Ferreira Filipe, Sara
SSRN
We measure funding constraints in international currency markets by deviations in the covered interest rate parity. Our measure of funding risk is the standard deviation of the magnitude of the funding constraints. This funding risk measure appears to be driven by conditions in the financial sector in the low interest rate, so called carry trade short countries, oil price volatility, as well as by the actions of the main central banks. Although funding risk has been present throughout our sample, it becomes only relevant in currency carry trading after 2008, suggesting that investors’ funding constraints start binding at that time. We document evidence that since 2008 funding risk has affected the magnitude of currency carry trading activity, carry trade returns, correlation between carry long and short currencies, relative equity returns in carry trade long vs. short countries, and the economies of carry trade long countries measured through changes in industrial production. We develop a theory of currency markets under funding constraints that has several testable implications. For instance, as funding constraints start to bind, our theory predicts that both the investment and funding currencies drop relative to a safe asset. This result is observable also in our empirical analysis, when we proxy for the safe asset with gold. In line with theory, funding risk forecasts currency crashes in the carry trade long and short countries.

Defaultable term structures driven by semimartingales
Sandrine Gümbel,Thorsten Schmidt
arXiv

In this work we consider a market with a term structure of credit risky bonds in the single-name case. We aim at minimal assumptions extending existing results in this direction. First, the random field of forward rates should be driven by general semimartingales. We show that in this case, it is necessary to extend the Heath-Jarrow-Morton approach to account for stochastic discontinuities. We do so by introducing an additional component which is an integral with respect to a random measure capturing those future jumps in the term structure which are visible from the current time. Also the forward rates for this second part are driven by general semimartingales. Finally, we pose only minimal assumptions on the associated recovery scheme, i.e. the recovery process is only assumed to be non-increasing.

In this general setting we derive generalized drift conditions which characterize when a given measure is a local martingale measure, thus yielding no asymptotic free lunch with vanishing risk (NAFLVR), the right notion for this large financial market to be free of arbitrage.



Distributional Implications of Corporate Financing
Khan, Haris,Shehzad, Choudhry Tanveer
SSRN
It is shown that the pecking order of corporate financing causes perpetual growth in corporate income inequality via concentrated growth of capital income share in total corporate income. Moreover, equity financing is shown to cause a perpetual decline in corporate income inequality via participative growth of capital income share, without any significant compromises notable in the growth rate of capital income.

Do Social Networks Facilitate Informed Option Trading? Evidence from Alumni Reunion Networks
Cheong, Harvey,Kim, Joon Ho,Münkel, Florian,Spilker III, Harold D.
SSRN
Material private information transmits through social networks. Using manually collected information on networks of alumni reunion cohorts, we show that hedge fund managers connected to directors of firms engaged in merger deals increase call option holdings on target firms before deal announcements. Effects are larger when reunion events for connected cohorts occur just before announcements. Independent directors, directors with short tenure, and directors with low stock ownership are more likely to transmit information. Our results are robust to confounding factors and alternative specifications. These findings highlight the role of social networks as channels of private information dissemination.

Does Holding Passive ETFs Change Retail Investors’ Trading Behavior for the Better?
D'Hondt, Catherine,Elhichou Elmaya, Younes,Petitjean, Mikael
SSRN
We use random matching to study the trading behaviors of retail investors who hold passive exchange traded funds invested in stocks (P-ETFs). Using both trading records and survey data to control for all the key investor characteristics, we find strong evidence that retail investors trade differently when they hold P-ETFs. They have a higher portfolio size, a lower turnover, and keep their assets for a longer period of time than the control group of retail investors who hold individual stocks only. P-ETF retail investors are also better protected against stock gambling and those among them who follow a core-satellite approach are least likely to hold lottery-like stocks.

Factor Investing using Capital Market Assumptions
Elkamhi, Redouane,Lee, Jacky S.H.,Salerno, Marco
SSRN
Capital market assumptions (CMAs), which are long-term risk and return forecasts for asset classes, are a pillar of the investment industry. However, using CMAs reliably in portfolio optimization exercises involving numerous asset classes has been (and still is) a challenge in the industry. Despite this challenge, this paper demonstrates that publicly available CMAs can be successfully applied to factor portfolio construction. Specifically, using a small set of macroeconomic factors, the authors detail a methodology to derive a multi-asset factor model using CMAs and show that the CMAs returns can be priced by those factors. Examples in factor portfolio construction and asset-liability management using industry's CMAs show stable and intuitive factor allocations can be generated through time. Our methodology can help reduce the barrier-to-entry for factor portfolio allocation by removing the necessity to build custom factor models and utilizing publicly available CMAs.

Fairness in Credit Scoring: Assessment, Implementation and Profit Implications
Nikita Kozodoi,Johannes Jacob,Stefan Lessmann
arXiv

The rise of algorithmic decision-making has spawned much research on fair machine learning (ML). Financial institutions use ML for building risk scorecards that support a range of credit-related decisions. Yet, the literature on fair ML in credit scoring is scarce. The paper makes two contributions. First, we provide a systematic overview of algorithmic options for incorporating fairness goals in the ML model development pipeline. In this scope, we also consolidate the space of statistical fairness criteria and examine their adequacy for credit scoring. Second, we perform an empirical study of different fairness processors in a profit-oriented credit scoring setup using seven real-world data sets. The empirical results substantiate the evaluation of fairness measures, identify more and less suitable options to implement fair credit scoring, and clarify the profit-fairness trade-off in lending decisions. Specifically, we find that multiple fairness criteria can be approximately satisfied at once and identify separation as a proper criterion for measuring the fairness of a scorecard. We also find fair in-processors to deliver a good balance between profit and fairness. More generally, we show that algorithmic discrimination can be reduced to a reasonable level at a relatively low cost.



Fishing among sharks â€" GP-LP investment syndication in later-stage venture capital
Achleitner, Ann‐Kristin,Braun, Reiner,Keppler, Henry
SSRN
Venture capital (VC) syndication mainly occurs to compensate for a lack of resources, whether financial or otherwise. The current literature does not sufficiently explore the extent to which the motives differ for syndication between general partners (GPs) or between GPs and limited partners (LPs). This paper investigates this matter, using a qualitative research design and focusing explicitly on heterogenous GP-LP syndicates. We document substantial differences between GPs and LPs in terms of syndication motives and criteria. For example, GPs aim to maximize influence by pooling control rights, while LPs wish to play a more passive role. More broadly, we find that the investment context, particularly the target company’s business model, presents another factor for determining the most effective syndicate setup.

Greenwashing and Product Market Competition
Arouri, Mohamed ,El Ghoul, Sadok,Gomes, Mathieu
SSRN
This study examines the relationship between corporate greenwashing and product market competition (PMC). Using an unbalanced panel of 324 US firms over the 2005-2015 period, we find that the negative impact of PMC on greenwashing is conditional on the level of environmental costs. Our results suggest that PMC is an effective disciplinary mechanism for achieving economic efficiency --in the case of firms featuring a high level of environmental costs-- through an increase in the disclosure of reliable and material information.

How do secured funding markets behave under stress? Evidence from the gilt repo market
Hüser, Anne-Caroline,Lepore, Caterina,Veraart, Luitgard Anna Maria
SSRN
We examine how the overnight gilt repo market operates during three episodes of liquidity stress, using novel transaction-level data on repurchase agreements on gilts. Using network analysis we document that the structure of the repo market significantly changes during stress relative to normal times, with a focus on how sectors adjust volumes, spreads and haircuts in their repo transactions. We find several common patterns in the two most recent stress episodes (the US repo turmoil in 2019 and the Covid-19 crisis in 2020): a preference for dealers and banks to transact in the cleared rather than the bilateral segment of the market, increased usage of the market by hedge funds and central counterparties increasing their reinvestment of cash margin into reverse repo.

How good is good? Probabilistic benchmarks and nanofinance+
Rolando Gonzales Martinez
arXiv

Benchmarks are standards that allow to identify opportunities for improvement among comparable units. This study suggests a 2-step methodology for calculating probabilistic benchmarks in noisy data sets: (i) double-hyperbolic undersampling filters the noise of key performance indicators (KPIs), and (ii) a relevance vector machine estimates probabilistic benchmarks with denoised KPIs. The usefulness of the methods is illustrated with an application to a database of nano-finance+. The results indicate that-in the case of nano-finance groups-a higher discrimination power is obtained with variables that capture the macro-economic environment of the country where a group operates. Also, the estimates show that groups operating in rural regions have different probabilistic benchmarks, compared to groups in urban and peri-urban areas.



Implementation of a cost-benefit analysis of Demand-Responsive Transport with a Multi-Agent Transport Simulation
Conny Grunicke,Jan Christian Schlüter,Jani-Pekka Jokinen
arXiv

In this paper, the technical requirements to perform a cost-benefit analysis of a Demand Responsive Transport (DRT) service with the traffic simulation software MATSim are elaborated in order to achieve the long-term goal of assessing the introduction of a DRT service in G\"ottingen and the surrounding area. The aim was to determine if the software is suitable for a cost-benefit analysis while providing a user manual for building a basic simulation that can be extended with public transport and DRT. The main result is that the software is suitable for a cost-benefit analysis of a DRT service. In particular, the most important internal and external costs, such as usage costs of the various modes of transport and emissions, can be integrated into the simulation scenarios. Thus, the scenarios presented in this paper can be extended by data from a mobility study of G\"ottingen and its surroundings in order to achieve the long-term goal. This paper is aimed at transport economists and researchers who are not familiar with MATSim, to provide them with a guide for the first steps in working with a traffic simulation software.



Implied Asset Return Profiles, Firm Fundamentals, and Stock Returns
Lee, Jongsub,Naranjo, Andy,Sirmans, Stace
SSRN
We introduce a novel approach to ascertain firms’ unobserved asset return distribution implied by the joint pricing of equity and credit securities within a structural framework. Motivated by Q-theory, we propose a two-factor model that captures asset growth and risk-shifting effects on stock returns. We show that strong asset returns representing systematic growth options predict higher stock returns, whereas shifting risk from equity to credit forecasts lower stock returns. We also find that the performance of many popular stock market factors (that overlook the optionality of equity) are significantly improved after controlling for asset-level risk-shifting exposure.

Information Quality and Workplace Safety
Hope, Ole-Kristian,Wang, Danye,Yue, Heng,Zhao, Jianyu
SSRN
This paper examines the effect of internal information quality on workplace safety. Using establishment-level data on workplace injuries from the Occupational Safety and Health Administration (OSHA) and employing a strict fixed-effects structure, we show that higher information quality is associated with significantly lower work-related injury rates. Further investigation reveals that the effect is stronger when more decision rights reside in headquarters, weaker when employees have greater bargaining power, and weaker when firms are subject to financial constraints. Our findings are robust to the use of two plausibly exogenous shocks and other robustness checks. Our study suggests an important economic consequence of information quality not examined by prior literature.

Le Sommet UE-Afrique 2021 : Quo vadis, compte tenu du Brexit et de la Covid-19 (The EU-Africa summit 2021 : Quo vadis, in the light of Brexit and Corona)
Kohnert, Dirk
SSRN
The English version of this paper can be found at http://ssrn.com/abstract=3792996French Abstract: Tous les trois ans, le sommet UA-UE réunit les dirigeants africains et européens pour définir l'orientation future de la coopération. Le 6e sommet devait réaffirmer et renouveler le partenariat entre les deux blocs déjà en octobre 2020, mais il a été repoussé au premier trimestre 2021, ou même plus tard, en raison de la crise du COVID-19. En outre, Bruxelles a dû faire face à sa propre situation post-Brexit, compte tenu l'exclusion du Royaume-Uni, et à ses répercussions sur les relations UE-Afrique. Les États africains, pour leur part, souhaitaient renégocier le partenariat UE-Afrique, et l'équilibrer avec les nouvelles visions post-Brexit prometteuses du Premier ministre britannique Johnson sur le renforcement des liens économiques avec l'Anglosphère africaine. La Chine et d'autres acteurs mondiaux sont en concurrence avec l'UE et ses États membre dans la nouvelle ruée vers les ressources africaines. Étant donné que l'Afrique est de plus en plus courtisée par d'autres partenaires, elle pourrait être encline à limiter successivement ses relations avec l'UE et à la considérer comme un simple fournisseur d'aide et de sécurité contre le terrorisme islamique. Cette tendance a été renforcée par le fait que la nouvelle stratégie UE-Afrique n'a toujours pas été approuvée par les États membres de l'UE. Et un remplacement opportun de l'accord de Cotonou, qui expire en novembre 2021, est sujet à caution.English Abstract: Every three years, the AU-EU summit reunites African and EU leaders to outline the future direction of cooperation. The 6th summit had been to reaffirm and renew the partnership between the two blocks already in October 2020, but it was pushed back to the first quarter of 2021 or even later due to COVID-19 crisis. Besides, Brussels had to deal with its own post-Brexit situation and its repercussions on EU-Africa relations, excluding the UK. African states, for their part, wanted to renegotiate the EU-Africa partnership and to balance it with new promising Post-Brexit visions of the British premier Johnson about increased economic ties with the African Angloshere. China and other global players compete with the EU and its member states in the new scramble for African resources. Given that Africa is increasingly courted by other partners it could be inclined to successively limit its relations with the EU and see it as a mere provider of aid and security against Islamic terrorism. This trend was reinforced by the fact that the new EU-Africa strategy still hasn't been approved by EU member states. And a timely replacement of the Cotonou Agreement, which expires in November 2021, is open to question.

Learning, Equilibrium Trend, Cycle, and Spread in Bond Yields
Zhao, Guihai
SSRN
Some key features in the historical dynamics of U.S. Treasury bond yields â€" a trend in long-term yields, business cycle movements in short-term yields, and a level shift in yield spreads â€" pose serious challenges to existing equilibrium asset pricing models. This paper presents a new equilibrium model to jointly explain these key features. The trend is generated by learning from the stable components in GDP growth and inflation, which share similar patterns to the neutral rate of interest (r Star) and trend inflation (pi Star) estimates in the literature. Cyclical movements in yields and spreads are mainly driven by learning from the transitory components in GDP growth and inflation. The less-frequent inverted yield curves observed after the 1990s are due to the recent secular stagnation and procyclical inflation expectation.

Liquidity in Competitive Dealer Markets
Peter Bank,Ibrahim Ekren,Johannes Muhle-Karbe
arXiv

We study a continuous-time version of the intermediation model of Grossman and Miller (1988). To wit, we solve for the competitive equilibrium prices at which liquidity takers' demands are absorbed by dealers with quadratic inventory costs, who can in turn gradually transfer these positions to an exogenous open market with finite liquidity. This endogenously leads to transient price impact in the dealer market. Smooth, diffusive, and discrete trades all incur finite but nontrivial liquidity costs, and can arise naturally from the liquidity takers' optimization.



Macroeconomic News and Acquirer Returns in M&As: The Impact of Investor Alertness
Barbopoulos, Leonidas G.,Adra, Samer,Saunders, Anthony
SSRN
We investigate the extent to which the scheduled release of macroeconomic indicators affects the acquirer's value in Mergers and Acquisitions (M&As). We find that M&As announced on days of the release of key macroeconomic indicators (i.e. indicator days) realize higher announcement period risk-adjusted returns compared to counterparts announced on non-indicator days. The positive wealth effect is due to the higher market attention on indicator days, which is parti- cularly relevant for smaller M&As that are not usually exposed to significant investor scrutiny. The results hold after addressing self-selection bias concerns. We also find that firms announcing M&As on indicator days are more likely to “listen” to the market's feedback.

Market Efficiency in the Age of Machine Learning
Barbopoulos, Leonidas G.,Dai, Rui,Putniņš, Tālis J.,Saunders, Anthony
SSRN
As machines replace humans in financial markets, how is informational efficiency impacted? We shed light on this issue by exploiting unique data that allow us to identify when machines access company information (8-K filings) versus when humans access the same information. We find that increased access by machines, particularly from cloud computing services, significantly improves informational efficiency, by reducing the price drift following information events. We address identification through a quasi-natural experiment, instrumental variables, and exogenous power outages. We show that machines are better able to handle linguistically complex filings and are less susceptible to bias from negative sentiment, whereas humans are better at combining incremental information.

Market Pricing of Fundamentals at the Shanghai Stock Exchange: Evidence from a Dividend Discount Model with Adaptive Expectations
Li, Mingyang,Niu, Linlin,Pua, Andrew
SSRN
We study market pricing of fundamentals at the Shanghai Stock Exchange, incorporating possible irrational pricing behavior with adaptive expectation. Using panel data of listed stocks to overcome the limited information in aggregate time series data, we estimated key parameters of the price elasticity of dividends and the expectation adjustment based on a linear dynamic panel data model. We use a major subset of stocks with stationary real prices and cash flows and apply methods that correct for incidental parameter bias. The resulting price elasticity of dividends is about 0.46 (0.35) based on annual (quarterly) data, which is sizable given high PD (PE) ratios in the market. Our results imply that slow expectation adjustment contributes to “bubble-like” price patterns. We also show prices significantly react to macro information related to the discount rate, but these effects are very sensitive to the information set used.

Market Reaction to the COVID-19: Evidence from the Emerging and Developed Markets
Harjoto, Maretno A.,Rossi, Fabrizio
SSRN
This study examines the market reaction to the World Health Organization (WHO) announcement of the novel coronavirus (COVID-19) as a global pandemic on the emerging equity markets and compares the reaction with developed markets. Using the Morgan Stanley Capital International (MSCI) daily stock indices data and the Carhart and the GARCH(1,1) models for an event study, this study finds that the COVID-19 pandemic had a significantly greater negative impact to the stock markets in emerging countries than in the developed countries. The negative impact on the emerging markets is more pronounced for firms with small market capitalizations and for growth stocks. The negative impact of the COVID-19 pandemic is stronger in the energy and financial sectors in both emerging and developed markets. The positive impact of the COVID-19 pandemic occurred in healthcare and telecommunications for the emerging markets and information technology (IT) for the developed markets. This study also finds that the equity markets in both emerging and developed countries recovered faster from the COVID-19 pandemic relative to the 2008 global financial crisis. This study extends the literature that examines market reactions to stock market shocks by examining the market reactions to the COVID-19 outbreak on the emerging and developed equity markets across different market capitalizations, valuation, and sectors.

Networks and Business Cycles
Zhu, Wu,Yang, Yucheng
SSRN
The speed at which the US economy has recovered from recessions ranges from months to years. We propose a model incorporating the innovation network, the production network, and cross-sectional shocks and show that their interactions jointly explain large variations in the recovery speed across recessions in the US. In the model, besides the production linkages, firms learn insights on production from each other through the innovation network. We show when the innovation network takes a low-rank structure, there exists one key direction: the impact a shock becomes persistent only if the shock is parallel to this key direction; in contrast, the impact declines quickly if the shock follows other directions. Empirically, we estimate the model in a state-space form and document a set of new stylized facts of the US economy. First, the innovation network among sectors takes a low-rank structure. Second, the innovation network has non-negligible overlap with the production network. Third, recessions with slow recovery are those witnessing sizable negative shock to sectors in the center of the innovation network. Such network structures and the time-varying sectoral distribution of the shocks can well explain the large variation in the recovery speed across recessions in the US. Finally, to emphasize the prevalence of the channel, we explore the application of the theory in asset pricing.

No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging
Shota Imaki,Kentaro Imajo,Katsuya Ito,Kentaro Minami,Kei Nakagawa
arXiv

Deep hedging (Buehler et al. 2019) is a versatile framework to compute the optimal hedging strategy of derivatives in incomplete markets. However, this optimal strategy is hard to train due to action dependence, that is, the appropriate hedging action at the next step depends on the current action. To overcome this issue, we leverage the idea of a no-transaction band strategy, which is an existing technique that gives optimal hedging strategies for European options and the exponential utility. We theoretically prove that this strategy is also optimal for a wider class of utilities and derivatives including exotics. Based on this result, we propose a no-transaction band network, a neural network architecture that facilitates fast training and precise evaluation of the optimal hedging strategy. We experimentally demonstrate that for European and lookback options, our architecture quickly attains a better hedging strategy in comparison to a standard feed-forward network.



OPEN BANKING: IMPACTOS E DESAFIOS NO MERCADO FINANCEIRO (Open Banking: Impacts and Challenges in the Financial Market)
Ogêda, Alexandre,Bagnoli, Vicente
SSRN
Portuguese Abstract: O presente artigo busca analisar os desafios que os bancos vêmenfrentando com o avanço das tecnologias digitais, as quais fizeram surgir, no cenário financeiro, a ideia principal de Open Banking, que está sendo aplicada em muitas instituições que procuram formas de criar serviços mais inovadores e flexíveis. O Open Banking é um modelo de negócios que funciona de uma forma diferente, peloqual o agente econômico passa a ter um foco maior nos seus processos críticos,liberando interfaces baseadas em Application Programming Interfaces (APIs), para que outras empresas possam criar aplicativos que agreguem valor aos serviços do negócio. Assim, os bancos podem focar no seu serviço primário enquanto odesenvolvimento de aplicativos ou integrações passa a ser de responsabilidade de uma comunidade de servidores. Com isso, as tecnologias, mais uma vez, modificam arelação dos consumidores com as instituições financeiras e alteram a dinâmica da concorrência. O Banco Central do Brasil (BCB), por sua vez, enquanto agentenormativo regulador, deve atuar, seja na coordenação do assunto, seja para regular o impacto das atividades financeiras realizadas frente às suas diretrizes. Já o Conselho Administrativo de Defesa Econômica (CADE), enquanto autoridade da concorrência, enfrenta e decide questões relacionadas à competição decorrentes dessa nova realidade no sistema financeiro.English Abstract: This article seeks to analyze the challenges that banks have been facing with the advancement of digital technologies, which have given rise to the main idea of Open Banking in the financial landscape, which is being applied in manyinstitutions looking for ways to create more innovative and flexible services. Open Banking is a differently functioning business model, whereby the economic agentbecomes more focused on its critical processes, releasing based interfaces onApplication Programming Interfaces (APIs), so that other companies can createapplications that aggregate value to business services. Thus, banks can focus on their primary service while application development or integration becomes theresponsibility of a server community. As a result, technologies once again change the relationship between consumers and financial institutions and modify dynamics of competition. The Central Bank of Brazil, in turn, as a regulatory agent, should act, either in coordinating the matter or in regulating the impact of financial activities carried out in accordance with its guidelines. On the other hand, Administrative Council for Economic Defense (CADE), as competition authority, faces and decides on competition issues arising from this new reality in the financial system.

Optimal Dynamic Selling Mechanism and Deal Protections in Mergers and Acquisitions
Chen, Yi,Wang, Zhe
SSRN
We study the dynamic profit-maximizing selling mechanism in an M&A environment with costly bidder entry and without entry fees. Depending on the parameters, the optimal mechanism is implemented by a standard auction, or by a two-stage procedure with exclusive offers to one bidder followed by an auction potentially favoring that bidder. The optimal mechanism may involve common deal protections like termination fees, asset lockups, or stock option lockups. Our proposed procedures resemble sales of targets filing Chapter 11 bankruptcy or M&A involving public targets; they shed light on how to use deal protections in practice.

Optimal level, Partial Speed of Adjustment and Determinants of Corporate Cash Holding: Evidence from MENA Countries
Raghibi, Abdessamad,Nguyen, Thanh Cuong ,Oubdi, Lahsen
SSRN
This paper investigates the existence of an optimal cash level, speed of adjustment, and cash holdings determinants. The threshold regression and dynamic model were used in this study on four MENA countries from 2007 to 2018. The findings show there is a nonlinear relationship between cash level and firm’s value which is consistent with the trade-off theory. Furthermore, our study confirms that firms holding cash above the optimal level of having a lower speed of adjustment than the firms with cash levels below the optimal level with size, growth, and net-working capital being key corporate cash determinants. Our results extend the theoretical implications of the trade-off theory to MENA countries and would help corporate policymakers to adjust their cash levels within the thresholds’ levels to maximize their firm value.

Optimal pair-trade execution with generalized cross-impact
Shimoshimizu, Makoto,Ohnishi, Masamitsu
SSRN
We examine a discrete-time optimal pair-trade execution problem with generalized cross-impact. This research is an extension of Fukasawa, Ohnishi, and Shimoshimizu (2020), which considers the price impact of aggregate random orders posed by small traders with a Markovian dependence. We focus on how a risk-averse large trader optimally executes two correlated assets to maximize his/her expected utility from the terminal wealth over a finite horizon. A Markov decision process modeling constitutes the basis for the formulation of the optimal pair-trade execution problem. Then, under some regularity conditions, the backward induction method of dynamic programming enables us to derive the optimal pair-trade execution strategy and its associated optimal value function. The trading orders of each risky asset posed by small traders do affect the optimal execution volume of both risky assets. Moreover, numerical results with simulation experiments show that the cross-impact affects the optimal execution strategy and a round-trip trade exists for the large trader to utilize a `statistical' arbitrage and to increase his/her expected utility under our model setting of cross-impact.

Pricing Interest Rate Derivatives under Volatility Uncertainty
Julian Hölzermann
arXiv

We study the pricing of contracts in fixed income markets in the presence of volatility uncertainty. The starting point is an arbitrage-free bond market under volatility uncertainty. The uncertainty about the volatility is modeled by a G-Brownian motion, which drives the forward rate dynamics. The absence of arbitrage is ensured by a drift condition. Such a setting leads to a sublinear pricing measure for additional contracts, which yields either a single price or a range of prices. Similar to the forward measure approach, we define the forward sublinear expectation to simplify the pricing of cashflows. Under the forward sublinear expectation, we obtain a robust version of the expectations hypothesis and we show how to price bond options. In addition, we develop pricing methods for contracts consisting of a stream of cashflows, since the nonlinearity of the pricing measure implies that we cannot price a stream of cashflows by pricing each cashflow separately. With these tools, we derive robust pricing formulas for all major interest rate derivatives. The pricing formulas provide a link to the pricing formulas of traditional models without volatility uncertainty and show that volatility uncertainty naturally leads to unspanned stochastic volatility.



Pricing high-dimensional Bermudan options with hierarchical tensor formats
Christian Bayer,Martin Eigel,Leon Sallandt,Philipp Trunschke
arXiv

An efficient compression technique based on hierarchical tensors for popular option pricing methods is presented. It is shown that the "curse of dimensionality" can be alleviated for the computation of Bermudan option prices with the Monte Carlo least-squares approach as well as the dual martingale method, both using high-dimensional tensorized polynomial expansions. This discretization allows for a simple and computationally cheap evaluation of conditional expectations. Complexity estimates are provided as well as a description of the optimization procedures in the tensor train format. Numerical experiments illustrate the favourable accuracy of the proposed methods. The dynamical programming method yields results comparable to recent Neural Network based methods.



Pricing of Climate Risk Insurance: Regulatory Frictions and Cross-Subsidies
Sen, Ishita,Tenekedjieva, Ana-Maria
SSRN
Homeowners’ insurance provides households financial protection from climate losses. To improve access and affordability, state regulators impose price controls on insurance companies. Using novel data, we construct a new measure of rate setting frictions for individual states and show that different states exercise varying degrees of price control, which positively correlates with how exposed a state is to climate events. In high friction states, insurers are more restricted in their ability to set rates and adjust rates less frequently and by a lower amount after experiencing climate losses. In part, insurers overcome pricing frictions by cross-subsidizing insurance across states. We show that in response to losses in high friction states, insurers increase rates in low friction states. Over time, rates get disjoint from underlying risk, and grow faster in states with low pricing frictions. Our findings have consequences for how climate risk is shared in the economy and for long-term access to insurance.

Quasi-Merit Goods: The Concept and a Case Study
Vernikov, Andrei
SSRN
Relying on the merit goods concept developed by Richard A. Musgrave, this paper introduces the notion of quasi-merit good. The criteria of eligibility for merit goods are vague. Quasi-merit good constitutes a special case where government protection and sponsorship are obtained via public choice influenced by special interests or a misconception. I claim that private bank deposits are a quasi-merit good meant to satisfy the public want of bank stability and uninterrupted supply of household savings into the financial system. Bank stakeholders join with other social and political groups to demand government intervention. It becomes institutionalized in the shape of a government-backed deposit protection scheme that ‘nudges’ depositors to act in a desirable way. Government assumes an implicit liability under deposit guarantee, but may be required to inject public funds to keep the scheme running. Deposit protection has distributional effects: welfare is redistributed in favor of special interests. Its premature enactment generates massive moral hazard among depositors and bankers.

Reducing the Volatility of Cryptocurrencies -- A Survey of Stablecoins
Ayten Kahya,Bhaskar Krishnamachari,Seokgu Yun
arXiv

In the wake of financial crises, stablecoins are gaining adoption among digital currencies. We discuss how stablecoins help reduce the volatility of cryptocurrencies by surveying different types of stablecoins and their stability mechanisms. We classify different approaches to stablecoins in three main categories i) fiat or asset backed, ii) crypto-collateralized and iii) algorithmic stablecoins, giving examples of concrete projects in each class. We assess the relative tradeoffs between the different approaches. We also discuss challenges associated with the future of stablecoins and their adoption, their adoption and point out future research directions.



Risk Aversion Connectedness in Developed and Emerging Equity Markets before and after the COVID-19 Pandemic
Fassas, Athanasios
SSRN
This study investigates the dynamic connectedness across the variance risk premium in international developed and emerging equity markets based on a Bayesian time-varying parameter vector autoregressive methodology.The empirical results indicate that the total spillover index is on average 65.6%, indicating a high, albeit declining, level of interconnectedness across the investor sentiment in the three markets under review until early 2020. Following the COVID-19 outbreak though, the total investors' risk aversion connectedness â€" as expected â€" strengthens, but more importantly, its dynamics alter, indicating that the risk aversion of emerging markets is an important contributor to the connectedness of international markets.

SWIFT calibration of the Heston model
Eudald Romo,Luis Ortiz-Gracia
arXiv

In the present work, the European option pricing SWIFT method is extended for Heston model calibration. The computation of the option price gradient is simplified thanks to the knowledge of the characteristic function in closed form. The proposed calibration machinery appears to be extremely fast, in particular for a single expiry and multiples strikes, outperforming the state-of-the-art method we compare with. Further, the a priori knowledge of SWIFT parameters makes possible a reliable and practical implementation of the presented calibration method. A wide set of stress, speed and convergence numerical experiments is carried out, with deep in-the-money, at-the-money and deep out-of-the-money options for very short and very long maturities.



Sinqapur maliyyə sisteminin inkişafını şərtləndirən əsas faktorlar (The Main Factors Contributing to the Development of the Financial System of Singapore)
Azimzadeh, Aslan,Huseynli, Jabbar
SSRN
Azerbaijani Abstract: Tədqiqatın məqsədi: “Dörd Asiya Pələngi”ndən biri olan Sinqapur maliyyə sisteminin uğurunu və inkişafını şərtləndirən əsas faktorları öyrənmək eyni zamanda bu təcrübədən yararlanmaq. Tədqiqatın metodologiyası: Müqayisəli təhlil, statistik təhlil, məntiqi ümumilləşdirmə. Tədqiqatın nəticəsi: Sinqapur maliyyə sisteminin inkişaf mərhələlərinin və müasir vəziyyətinin sistemləşdirilərək kompleks araşdırılmasından eyni zamanda Sinqapur maliyyə sisteminin inkişafını şərtləndirən əsas faktorların müəyyən edilməsindən ibarətdir. Açar sözlər: Sinqapur birjası, Sinqapur maliyyə sistemi, bank aktivləri, valyuta bazarı.English Abstract: Purpose of the research: To study the main factors that contribute to the success and development of the financial system of Singapore, one of the “Four Asian Tigers.” And also, take advantage of this experience. Methodology of the research: Comparative analysis, statistical analysis, logical summarization. Results of the research: A systematic comprehensive study of the stages and current state of development of the financial system of Singapore at the same time determines the main factors that contribute to the development of the financial system of Singapore.

SoK: Decentralized Finance (DeFi)
Sam M. Werner,Daniel Perez,Lewis Gudgeon,Ariah Klages-Mundt,Dominik Harz,William J. Knottenbelt
arXiv

Decentralized Finance (DeFi), a blockchain powered peer-to-peer financial system, is mushrooming. One year ago the total value locked in DeFi systems was approximately 600m USD, now, as of January 2021, it stands at around 25bn USD. The frenetic evolution of the ecosystem makes it challenging for newcomers to gain an understanding of its basic features. In this Systematization of Knowledge (SoK), we delineate the DeFi ecosystem along its principal axes. First, we provide an overview of the DeFi primitives. Second, we classify DeFi protocols according to the type of operation they provide. We then go on to consider in detail the technical and economic security of DeFi protocols, drawing particular attention to the issues that emerge specifically in the DeFi setting. Finally, we outline the open research challenges in the ecosystem.



Social Connections and Information Leakage: Evidence from Target Stock Price Run-Ups in Takeovers
Hasan, Iftekhar,Tong, Lin,Yan, An
SSRN
Does information leakage in a target’s social networks contribute to increase in its stock price prior to a merger announcement? Evidence reveals that a target with better social connections indeed experiences a higher pre-announcement price run-up. This effect does not exist during or after merger announcement, or in windows ending two months before the announcement. It is more pronounced among targets with severe asymmetric information, and weaker when public information about an upcoming merger is available prior to the announcement. It is also weaker in expedited deals such as in tender offers.

Social Responsibility and Bank Resiliency
Gehrig, Thomas,Iannino, Maria Chiara,Unger, Stephan
SSRN
We provide transatlantic evidence about the relation between social responsibility and resiliency in the banking industry. We analyse various measures of resiliency, an exposure measure (SRISK) and a contribution measure (Delta CoVaR) to systemic risk, as well as measures of systematic risk (beta) and insolvency risk (z-score). Social responsibility is measured by Thomson Reuters' ESG-scores and their subcategories, both according to the older Asset 4 and the present TR ESG Refinitiv classification. We find that the social aggregate score significantly enhances resiliency in all dimensions and in both classifications. On the level of subcategories, we identify significant common resiliency enhancing factor proxies for long-term orientation, such as product responsibility and workforce training, while short-term objectives proxied by shareholder orientation tend to relate to lower levels of resiliency. Looking deeper into the components of each ESG pillar, we also discover significant transatlantic differences mainly related to the different organization of labour markets as well as the board structure.

Solvency Distress Contagion Risk: Network Structure, Bank Heterogeneity and Systemic Resilience
Abduraimova, Kumushoy,Nahai-Williamson, Paul
SSRN
We systematically analyse how network structure and bank characteristics affect solvency distress contagion risk in interbank networks. As interbank networks become more connected and more regular in structure, the contagion risk of system-wide shocks and individual bank defaults initially increases and then decreases, all else being equal. The low density heterogeneous network structures that typify real interbank networks are particularly prone to solvency distress contagion risk, when banks are similar in balance sheet size and capitalisation. However, when networks are calibrated to UK data, the higher capitalisation of large, highly-connected banks relative to their interbank exposures significantly increases the resilience of the system and reduces the importance of network structure. These findings reinforce the importance and effectiveness of imposing higher capital buffers on systemically important banks and of policies that limit interbank exposures. We also demonstrate that for real-world interbank networks, simple network metrics other than individual bank connectedness do not provide robust indicators for monitoring solvency contagion risk, suggesting that policymakers should continue efforts to model these risks explicitly rather than rely on simple aggregate indicators.

Taxing the American Emigrant
Snyder, Laura
SSRN
American emigrants face many consequences from the extraterritorial application of U.S. taxation and banking policies. Their names, addresses, and Social Security numbers are collected, placed on lists of “suspected U.S. persons,” and submitted to a “Crimes Enforcement Network.” They struggle with incompatible tax systems, resulting in penalizing taxation, the inability to make investments and save for retirement, the inability to hold title to family assets, the denial of bank accounts and other financial services, and the denial of employment, entrepreneurial, and community service opportunities.These stigmatizing policies and their consequences are frequently justified on the basis that American emigrants are wealthy persons seeking to avoid taxation. This is evidenced by the comments that U.S. policymakers and other public figures have made about American emigrants throughout the country’s history, as well as the manifest anti-emigrant bias in the academic literature and media.Further, the policies have consequences for the countries in which American emigrants live: they negate legal protections provided by these countries in such areas as data protection, banking, human rights, retirement, savings and investment, and succession planning. They also undermine the fiscal and monetary policies of these countries and the authority of their policymakers. In short, U.S. policies toward American emigrants jeopardize the sovereignty of many countries around the world.Citizenship is a human right. Leaving one’s country and returning to it are human rights. Countries, also, have a right to self-determination. The extraterritorial application of U.S. taxation and banking policiesâ€"which is justified through the stigmatization of American emigrantsâ€"places all of these rights in peril.The stigmatization of American emigrants must, like other forms of stigmatization, be identified and held unacceptable. Otherwise, there is little hope for change.

The EU-Africa summit 2021 : Quo vadis, in the light of Brexit and Corona
Kohnert, Dirk
SSRN
La version française de cet article peut être consultée à:http://ssrn.com/abstract=3793996Every three years, the AU-EU summit reunites African and EU leaders to outline the future direction of cooperation. The 6th summit had been to reaffirm and renew the partnership between the two blocks already in October 2020, but it was pushed back to the first quarter of 2021 or even later due to COVID-19 crisis. Besides, Brussels had to deal with its own post-Brexit situation and its repercussions on EU-Africa relations, excluding the UK. African states, for their part, wanted to renegotiate the EU-Africa partnership and to balance it with new promising Post-Brexit visions of the British premier Johnson about increased economic ties with the African Angloshere. China and other global players compete with the EU and its member states in the new scramble for African resources. Given that Africa is increasingly courted by other partners it could be inclined to successively limit its relations with the EU and see it as a mere provider of aid and security against Islamic terrorism. This trend was reinforced by the fact that the new EU-Africa strategy still hasn't been approved by EU member states. And a timely replacement of the Cotonou Agreement, which expires in November 2021, is open to question.

The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network
Zijian Shi,Yu Chen,John Cartlidge
arXiv

In an order-driven financial market, the price of a financial asset is discovered through the interaction of orders - requests to buy or sell at a particular price - that are posted to the public limit order book (LOB). Therefore, LOB data is extremely valuable for modelling market dynamics. However, LOB data is not freely accessible, which poses a challenge to market participants and researchers wishing to exploit this information. Fortunately, trades and quotes (TAQ) data - orders arriving at the top of the LOB, and trades executing in the market - are more readily available. In this paper, we present the LOB recreation model, a first attempt from a deep learning perspective to recreate the top five price levels of the LOB for small-tick stocks using only TAQ data. Volumes of orders sitting deep in the LOB are predicted by combining outputs from: (1) a history compiler that uses a Gated Recurrent Unit (GRU) module to selectively compile prediction relevant quote history; (2) a market events simulator, which uses an Ordinary Differential Equation Recurrent Neural Network (ODE-RNN) to simulate the accumulation of net order arrivals; and (3) a weighting scheme to adaptively combine the predictions generated by (1) and (2). By the paradigm of transfer learning, the source model trained on one stock can be fine-tuned to enable application to other financial assets of the same class with much lower demand on additional data. Comprehensive experiments conducted on two real world intraday LOB datasets demonstrate that the proposed model can efficiently recreate the LOB with high accuracy using only TAQ data as input.



The Origination and Distribution of Money Market Instruments: Sterling Bills of Exchange during the First Globalization
Olivier Accominotti,Delio Lucena-Piquero,Stefano Ugolini
arXiv

This paper presents a detailed analysis of how liquid money market instruments -- sterling bills of exchange -- were produced during the first globalisation. We rely on a unique data set that reports systematic information on all 23,493 bills re-discounted by the Bank of England in the year 1906. Using descriptive statistics and network analysis, we reconstruct the complete network of linkages between agents involved in the origination and distribution of these bills. Our analysis reveals the truly global dimension of the London bill market before the First World War and underscores the crucial role played by London intermediaries (acceptors and discounters) in overcoming information asymmetries between borrowers and lenders on this market. The complex industrial organisation of the London money market ensured that risky private debts could be transformed into extremely liquid and safe monetary instruments traded throughout the global financial system.



The Revolving Door and Insurance Solvency Regulation
Tenekedjieva, Ana-Maria
SSRN
Financial solvency regulation of the U.S. insurance industry occurs at the state level, and is led by insurance commissioners. Insurance commissioners wield significant discretion over the regulatory process, but their incentives may be affected by post-term job opportunities ("revolving door"). I construct a novel data set of the employment history of insurance commissioners from 2000 to 2018 and find 38% of them work in the insurance industry after their term ends ("post-term revolvers"). Before leaving office, post-term revolvers are laxer financial regulators along several dimensions: they perform fewer financial exams per year, the exams they perform have fewer negative consequences for firms, and post-term revolvers are less likely to respond to insurers' risk-taking. I show that this lax regulation leads to higher aggregate levels of solvency misreporting during 2008, and to likely over-optimistic credit ratings. Finally, post-term revolvers' behavior responds to changes in incentives. Specifically, commissioners more likely to be post-term revolvers ex ante perform more exams in states where revolving door laws have been tightened. Overall, my results suggest the revolving door induces insurance regulators to be less strict, with significant consequences for the market transparency.

Trump Tweet Impacts on the MSCI World Exposure with China Index - Evidence from An Event Study Deploying Cumulative Abnormal Returns
Klaus, Juergen
SSRN
I study US-president’s Trump tweets on the US/China trade relationship and their impact stock valuations of companies with a high China exposure. This event study deploys data from the MSCI World with China Index and identifies potential out-/underperformance using cumulative abnormal returns (CAR). My results are presented based on the full index constitutes using heatmaps to show significance of CARs where applicable.My findings suggest that statistically significant CARs are limited depending on identified tweets and appear volatile depending on the estimation window. A vast amount of statistically insignificant CARs based on Trump tweets on China supports the conclusion that his tweets had an overall low impact on the index companies.

Using Economic Links between Firms to Detect Accounting Fraud
Li, Chenchen,Li, Ningzhong,Zhang, Frank
SSRN
This paper explores whether accounting fraud can be detected using the information of firms that are economically linked to a focal firm. Specifically, we examine whether customer information disclosed by a supplier firm, combined with customers’ accounting information, helps to detect the supplier’s revenue fraud. We first confirm the economic link between the supplier and its customers by showing a strong positive correlation between the supplier’s sales growth and the growth rate of total customer purchases. We then introduce two variables based on customer accounting information â€" (1) the discrepancy between supplier sales growth and customer purchase growth and (2) customer excess purchases â€" and show that they are predictive of supplier revenue fraud. We conduct a battery of cross-sectional tests to further examine the two fraud predictors and generally find empirical results to vary cross-sectionally in a predictable way. Finally, the out-of-sample tests indicate that adding the two variables to the Dechow et al. (2011) model increases fraud prediction accuracy.

Venture Capital Financing in the Esports Industry
Niculaescu, Corina E.,Sangiorgi, Ivan,Bell, Adrian R.
SSRN
We examine the drivers of venture capital financing raised by eSports companies, using the CrunchBase database containing information on private and public companies receiving any type of venture capital funding worldwide. We find that companies located in Asia-Pacific and Americas attract more funding than in Europe. Venture capital funds are more likely to fund late stage and older companies, than innovative early stage and younger firms. We also observe that the founders’ previous experience plays a significant role in explaining the level of funding. Companies with at least one founder with previous eSport, managerial or start-up experience are more likely to get more funding by venture capital funds. Our research provides new evidence on how venture capital funding is allocated between late stage and early stage firms as well as between older and younger companies in the eSport-industry and in different markets.

Was there a COVID-19 harvesting effect in Northern Italy?
Augusto Cerqua,Roberta Di Stefano,Marco Letta,Sara Miccoli
arXiv

We investigate the possibility of a harvesting effect, i.e. a temporary forward shift in mortality, of the COVID-19 pandemic by looking at the excess mortality trends of one of the areas with the highest death toll in the world, Northern Italy. We do not find any evidence of a sizable COVID-19 harvesting effect, neither in the summer months following the slowdown of the first wave nor at the beginning of the second wave. According to our estimates, only a minor share of the total excess deaths detected in Northern Italy over the entire period under scrutiny (February - November 2020) can be attributed to an anticipatory role of COVID-19. A somewhat more sizable harvesting effect is detected for the most severely affected areas (the provinces of Bergamo and Brescia, in particular), but even in these territories, the harvesting effect only accounts for less than 20% of excess deaths. Furthermore, the lower excess mortality rates observed in these areas at the beginning of the second wave could be due to several factors other than a harvesting effect, including behavioral change and some degree of temporary herd immunity. The very limited presence of mortality displacement in the short-run restates once more the case for containment policies aimed at minimizing the health impacts of the pandemic.



What Do the Portfolios of Individual Investors Reveal About the Cross-Section of Equity Returns?
Betermier, Sebastien,Calvet, Laurent E.,Knüpfer, Samuli,Kvaerner, Jens
SSRN
We construct a parsimonious set of equity factors by sorting stocks according to the sociodemographic characteristics of the individual investors who own them. The analysis uses administrative data on the stockholdings of Norwegian investors in 1997-2018. Consistent with financial theory, a mature-minus-young factor, a high wealth-minus-low wealth factor, and the market factor price stock returns. Our three factors span size, value, investment, profitability, and momentum, and perform well in out-of-sample bootstrap tests. The tilts of investor portfolios toward the new factors are driven by wealth, indebtedness, macroeconomic exposure, age, gender, education, and investment experience. Our results are consistent with hedging and sentiment jointly driving portfolio decisions and equity premia.

What Drive Excessive Borrowing and Under-Borrowing? Theory and Field Experiment
Li, King King,Liu, Dan,Mai, Xin Da,Zhang, Qiu Ju,Ren, Xiao Yu,Xu, Gao Qian,Zhang, Kai
SSRN
We investigate the determinants of excessive/under-borrowing. Our study differs from the literature by measuring excessive/under-borrowing, and estimating the effect of self-control, financial literacy, and misperception of interest rates, in addition to present bias. We observe both excessive borrowing and under-borrowing, with higher proportion of subjects exhibiting the latter. Subjects with better self-control are less likely to exhibit excessive borrowing, and are more likely to exhibit under-borrowing. It suggests that excessive (under-) borrowing can be due to over-estimation (under-estimation) of self-control. Subjects with better financial literacy are less likely to exhibit excessive borrowing. An additional level of better self-control leads to 10.34% lower borrowing interest rate in real-life. An additional level of better financial literacy leads to 3.44% lower interest rate. Borrowers exhibiting interest rate misperception pay about 11.49% higher interest rate. The findings on the role of financial literacy and misperception of interest rate suggest that excessive-borrowing is not merely a self-control problem, and it can be reduced through appropriate financial education.

Where Have the Profits Gone? Market Efficiency and the Disappearing Equity Anomalies in Country and Industry Returns
Zaremba, Adam,Umutlu, Mehmet,Maydybura, Alina
SSRN
We are the first to demonstrate the decline in the cross-sectional predictability of country and industry returns in recent years. We examine 53 anomalies in country and industry indices from 64 markets for the years 1973â€"2018. The profitability of the strategies has significantly decreased recently, driven particularly by the disappearance of value and reversal effects. The phenomenon is strongest in large developed markets. Neither changes in country- and industry-specific risks, nor investor learning from the academic literature can explain the effect. Our findings support the view that the fall in return predictability is caused by the overall improvement in market efficiency.

Who Owns What? A Factor Model for Direct Stockholding
Balasubramaniam, V.,Campbell, John Y.,Ramadorai, Tarun,Ranish, Benjamin
SSRN
We build a cross-sectional factor model for investors' direct stockholdings, by analogy with standard time-series factor models for stock returns. We estimate the model using data from almost 10 million retail accounts in the Indian stock market. We find that stock characteristics such as firm age and share price have strong investor clienteles associated with them. Similarly, account attributes such as account age, account size, and extreme underdiversification (holding a single stock) are associated with particular characteristic preferences. Coheld stocks tend to have higher return covariance, suggestive of the importance of clientele effects in the stock market.

Who buys Bitcoin? The Cultural Determinants of Bitcoin Usage
Foley, Sean,Frijns, Bart,Garel, Alexandre,Roh, Tai-Yong
SSRN
We examine the relationship between national culture and a country’s Bitcoin usage. Given that Bitcoin is a high-risk currency/investment that is frequently used for illegal purposes and whose market is relatively opaque, we focus on the cultural dimension of individualism, which has been related to risk-taking behavior and overconfidence. Using unique data that includes the originating country for Bitcoin transactions, we examine the relationship between individualism and a country’s Bitcoin usage for a sample of 80 countries between 2009-2018. We find a significant and positive relationship between a country’s individualism and its use of Bitcoin consistent with cultural values affecting the demand for such high-risk currency/investments.

Withdrawal of Management Earnings Guidance During the COVID-19 Pandemic
Aaron, Aurelius,Kang, Jian,Ng, Jeffrey,Rusticus, Tjomme O.
SSRN
The COVID-19 pandemic has resulted in extreme uncertainty in the future earnings of many firms. In this paper, we examine how firms’ exposure to the pandemic affects their guidance withdrawals. Almost half the firms in our sample withdraw their management earnings guidance instead of maintaining or revising it. Our empirical analysis reveals that firms more affected by the pandemic are more likely to withdraw guidance. This is consistent with firms generally being unwilling to commit to earnings targets when facing extreme uncertainty. The effect is more pronounced for firms facing higher litigation risk and product market competition. Guidance withdrawal also is associated with downward revisions in analyst forecasts, increased analyst forecast dispersion, and reduced analyst forecast accuracy, as well as greater share turnover, bid-ask spreads, and stock return volatility. Our paper provides novel insight into the phenomenon of guidance withdrawal as a disclosure response in times of extreme uncertainty.