Research articles for the 2020-06-17

A General Solution Method for Insider Problems
Francois Cocquemas,Ibrahim Ekren,Abraham Lioui

We develop a flexible approach to solve a continuous-time, multi-asset/multi-option Kyle-Back model of informed trading under very general assumptions, including on the distribution of the belief about the fundamental, and the noise process. The main insight is to postulate the pricing rule of the market maker at maturity as an optimal transport map. The optimal control of the informed trader reduces to the computation of a conjugate convex function, explicit in some cases, and otherwise easily obtainable using fast numerical algorithms. To illustrate the power of our method, we apply it to a long-standing problem: how are informed investors splitting trades between a spot asset and its options? Our method allows to i) prove the existence of an equilibrium and characterize the informed trader's trading strategy in the spot and the option markets, even for non-Gaussian price priors (e.g., lognormal); ii) show there can be cross-market price impact between the spot market and multiple options even when their noise trading is independent; and iii) compare our pricing results to a simple Black-Scholes model and quantify the price distortion of the option due to strategic trading. In particular, we show that a Black-Scholes implied volatility (IV) smile/smirk can emerge because of the market marker's adaptation to asymmetric information.

A Tweet-based Dataset for Company-Level Stock Return Prediction
Karolina Sowinska,Pranava Madhyastha

Public opinion influences events, especially related to stock market movement, in which a subtle hint can influence the local outcome of the market. In this paper, we present a dataset that allows for company-level analysis of tweet based impact on one-, two-, three-, and seven-day stock returns. Our dataset consists of 862, 231 labelled instances from twitter in English, we also release a cleaned subset of 85, 176 labelled instances to the community. We also provide baselines using standard machine learning algorithms and a multi-view learning based approach that makes use of different types of features. Our dataset, scripts and models are publicly available at:

A demographic microsimulation model with an integrated household alignment method
Amarin Siripanich,Taha Rashidi

Many dynamic microsimulation models have shown their ability to reasonably project detailed population and households using non-data based household formation and dissolution rules. Although, those rules allow modellers to simplify changes in the household construction, they typically fall short in replicating household projections or if applied retrospectively the observed household numbers. Consequently, such models with biased estimation for household size and other household related attributes lose their usefulness in applications that are sensitive to household size, such as in travel demand and housing demand modelling. Nonetheless, these demographic microsimulation models with their associated shortcomings have been commonly used to assess various planning policies which can result in misleading judgements. In this paper, we contribute to the literature of population microsimulation by introducing a fully integrated system of models for different life event where a household alignment method adjusts household size distribution to closely align with any given target distribution. Furthermore, some demographic events that are generally difficult to model, such as incorporating immigrant families into a population, can be included. We illustrated an example of the household alignment method and put it to test in a dynamic microsimulation model that we developed using dymiumCore, a general-purpose microsimulation toolkit in R, to show potential improvements and weaknesses of the method. The implementation of this model has been made publicly available on GitHub.

Addressing the Herd Immunity Paradox Using Symmetry, Convexity Adjustments and Bond Prices
Peter Cotton

In constant parameter compartmental models an early onset of herd immunity is at odds with estimates of R values from early stage growth. This paper utilizes a result from the theory of interest rate modeling, namely a bond pricing formula of Vasicek, and an approach inspired by a foundational result in statistics, de Finetti's Theorem, to show how the modeling discrepancy can be explained. Moreover the difference between predictions of classic constant parameter epidemiological models and those with variation and stochastic evolution can be reduced to simple "convexity" formulas. A novel feature of this approach is that we do not attempt to locate a true model but only a model that is equivalent after permutations. Convexity adjustments can also be used for cross sectional comparisons and we derive easy to use rules of thumb for estimating threshold infection level in one region given knowledge of threshold infection in another.

American Option Pricing: Optimal Lattice Models and Multidimensional Efficiency Tests
Shang, Qianru,Byrne, Brian
This paper introduces a set of lattice techniques with a view to accelerating computation time and improving the accuracy of American Option valuation. Estimation speed can be enhanced through developing a parsimonious early exercise boundary search routine combined with reliance on dynamic memory and lattice truncation. Furthermore, Black-Scholes and Richardson extrapolation modifications to the lattices can also be applied individually and/or together to improve the accuracy of lattices. In this paper, we investigate the improvement introduced by obtaining the best combination of varying features. By introducing these techniques to the Leisen-Reimer and Tian binomial model, we can achieve a level of accuracy and efficiency combined that surpass analytical analogues prominent in the literature. Significantly, the Leisen-Reimer and Tian structure can accommodate arbitrary improvements in accuracy by simply increasing the density of their own mesh. Analytical methods generally do not afford much scope for optimising speed and efficiency in a granular fashion. We also compare efficient lattice models with analytical formulae for pricing different groups of options according to the deepness of American quality and the moneyness of the options. The appropriate model is recommended for pricing particular types of the options. Lattices importantly afford an explicit trade-off locus between accuracy and speed that can be navigated according to predetermined precision tolerance levels and option types. This should have practical relevance to trading platforms that require real-time estimates of implied volatility.

Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package
Matteo Zampieri,Andrea Toreti,Andrej Ceglar,Pierluca De Palma,Thomas Chatzopoulos

This paper presents a Python object-oriented software and code to compute the annual production resilience indicator. The annual production resilience indicator can be applied to different anthropic and natural systems such as agricultural production, natural vegetation and water resources. Here, we show an example of resilience analysis of the economic values of the agricultural production in Europe. The analysis is conducted for individual time-series in order to estimate the resilience of a single commodity and to groups of time-series in order to estimate the overall resilience of diversified production systems composed of different crops and/or different countries. The proposed software is powerful and easy to use with publicly available datasets such as the one used in this study.

Analysis of Income Composition, Asset Quality and Profitability of Indian Commercial Banks
Pillai, Deepa,Dam, Leena
Commercial banks are traditional financial institutions accepting deposits and lending whereby maintaining financial stability. Stability of the banking system and viability of banks is considered to be of principal significance growth of the economy. The shifting landscape of financial system has brought transition in the businesses of the banks along with rise in stressed asset levels. Quality of assets of bank directly affect the income, expense and balance sheet of the banks. The paper attempts to investigate the change in the income composition of banks further it also examines the change in the asset quality of banks over a period of 10 years. The research also aims to review the relationship between the asset quality and profitability of banks. Using a sample of public and private banks from India, a panel regression analysis affirmed the interrelationship between income, asset quality and earnings which indicates banks focus on nontraditional income has improved the quality of earnings, however higher credit to deposit ratio has declined the asset quality over the time span. Lower asset quality lead to lower return on assets and return on equity which confirms to the study by Lown and Friedman (1991) lower asset quality in economies defer economic recovery by decreasing operating profit margin and eroding capital base for new loans.

Anomalies and the Cross-Section of Expected Stock Returns: Disentangling Characteristic, Covariance, and Mis-pricing via Machine Learning
Han, Xiao
I disentangle the importance of firm characteristics, covariance, and mis-pricing in driving the cross-section of expected returns and the profitability on 27 anomaly strategies via Support Vector Machine (SVM) and Random Forests classifications. I find that characteristics and mis-pricing caused by investors’ biased expectation are the most important features; covariance is only priced across stocks that are less subject to investor optimism. The long-short portfolio formed on the SVM score, the product of features and their coefficient weights from the linear support vector, yields monthly return of 5.14% with a Sharpe ratio of 0.89. More importantly, removing stocks with extreme SVM scores attenuates anomaly payoffs significantly. My findings demonstrate that characteristics, biased expectations, and covariance affect stock returns simultaneously and that such effects are time-varying with business cycles.

Associating Ridesourcing with Road Safety Outcomes: Insights from Austin Texas
Eleftheria Kontou,Noreen C. McDonald

Improving road safety and setting targets for reducing traffic-related crashes and deaths are highlighted as part of the United Nation's sustainable development goals and vision zero efforts around the globe. The advent of transportation network companies, such as ridesourcing, expands mobility options in cities and may impact road safety outcomes. In this study, we analyze the effects of ridesourcing use on road crashes, injuries, fatalities, and driving while intoxicated (DWI) offenses in Travis County Texas. Our approach leverages real-time ridesourcing volume to explain variation in road safety outcomes. Spatial panel data models with fixed effects are deployed to examine whether the use of ridesourcing is significantly associated with road crashes and other safety metrics. Our results suggest that for a 10% increase in ridesourcing trips, we expect a 0.12% decrease in road crashes (p<0.05), a 0.25% decrease in road injuries (p<0.001), and a 0.36% decrease in DWI offenses (p<0.0001) in Travis County. Ridesourcing use is not associated with road fatalities at a 0.05 significance level. This study augments existing work because it moves beyond binary indicators of ridesourcing presence or absence and analyzes patterns within an urbanized area rather than metropolitan-level variation. Contributions include developing a data-rich approach for assessing the impacts of ridesourcing use on our transportation system's safety, which may serve as a template for future analyses of other US cities. Our findings provide feedback to policymakers by clarifying associations between ridesourcing use and traffic safety, while helping identify sets of actions to achieve safer and more efficient shared mobility systems.

Attention Triggers and Investors' Risk-Taking
Arnold, Marc,Pelster, Matthias,Subrahmanyam, Marti G.
This paper investigates how individual attention triggers influence financial risk-taking based on a large sample of trading records from a brokerage service that sends standardized push messages on stocks to retail investors. By exploiting the data in a difference-in-differences (DID) setting, we find that attention triggers increase investors' risk-taking. Our DID coefficient implies that attention trades carry, on average, a 19-percentage point higher leverage compared to non-attention trades. We provide a battery of cross-sectional analyses to identify the groups of investors and stocks for which this effect is stronger.

Bank Capital Regulation in a Zero Interest Environment
Döttling, Robin
How do near-zero interest rates affect optimal bank capital regulation and risk-taking? I study this question in a dynamic model, in which forward-looking banks compete imperfectly for deposit funding, but households do not accept negative deposit rates. When deposit rates are constrained by the zero lower bound (ZLB), tight capital requirements disproportionately hurt franchise values and become less effective in curbing excessive risk-taking. As a result, optimal dynamic capital requirements vary with the level of interest rates if the ZLB binds occasionally. Higher inflation and unconventional monetary policy can alleviate the problem, though their overall welfare effects are ambiguous.

Bank-Fintech Partnerships, Outsourcing Arrangements and the Case for a Mentorship Regime
Enriques, Luca,Ringe, Wolf-Georg
Fintech firms, once seen as “disruptors” of the traditional banking world, are now increasingly seen as attractive partners for established financial institutions. Such partnership agreements come in different forms and contexts, but most share the goals of outsourcing key banking functions and facilitating market entry for new market players while overcoming relatively tough regulatory hurdles.Yet such arrangements, while generally to be welcomed, pose a number of regulatory problems, in particular concerning the effective supervision of fintechs that operate outside of the direct purview of regulatory authorities. Questions of enforcement and effective supervision emerge, which may ultimately result in problems regarding market stability and systemic risk. Regulatory sandboxes represent one attempt to address these problems but may fail to do so and are often ineffective or unavailable. Other similar solutions, such as fintech charters and umbrella firms, may help but, similarly, provide an imperfect solution.Against this backdrop, we make the case for a “mentorship regime,” which provides for a reliable regulatory framework for partnership agreements between fintech firms and established banks. This would allow for a de facto “private sandbox” where experienced firms could mentor new startups and help them to cope with a complex regulatory process. At the same time, a state-backed mentorship plan would clear up the allocation of responsibilities, supervision competences, and liability questions and thus overcome problems of arbitrage and abuse. Ultimately, a mentorship regime may show the way to a new and more reliable future system of banking, making the well-established contractual practice of outsourcing banking services more reliable.

Banks and Sovereigns: Did Adversity Bring Them Closer?
Dungey, Mardi H.,Flavin, Thomas,Sheenan, Lisa
We analyse the stability of the cross-market shock transmission mechanism between banks and sovereign bonds during the Eurozone sovereign debt crisis for crisis-hit periphery countries and Germany. We also examine the shock propagation of banking shocks and sovereign bond shocks between domestic and external markets. Using a Markov-switching framework, we find strong evidence of bilateral contagion between banks and sovereign bonds and also between domestic and external banking sectors. Sovereign bond markets are different. An external shock only produces contagious effects in Greece, who were largely dependent on external aid. For all the others, external shocks lead to decoupling as investors became increasingly discerning in their perception of the debt instruments issued by different Eurozone states.

Consistent Recalibration Models and Deep Calibration
Matteo Gambara,Josef Teichmann

Consistent Recalibration models (CRC) have been introduced to capture in necessary generality the dynamic features of term structures of derivatives' prices. Several approaches have been suggested to tackle this problem, but all of them, including CRC models, suffered from numerical intractabilities mainly due to the presence of complicated drift terms or consistency conditions. We overcome this problem by machine learning techniques, which allow to store the crucial drift term's information in neural network type functions. This yields first time dynamic term structure models which can be efficiently simulated.

Deep learning Profit & Loss
Pietro Rossi,Flavio Cocco,Giacomo Bormetti

Building the future profit and loss (P&L) distribution of a portfolio holding, among other assets, highly non-linear and path-dependent derivatives is a challenging task. We provide a simple machinery where more and more assets could be accounted for in a simple and semi-automatic fashion. We resort to a variation of the Least Square Monte Carlo algorithm where interpolation of the continuation value of the portfolio is done with a feed forward neural network. This approach has several appealing features. Neural networks are extremely flexible regressors. We do not need to worry about the fact that for multi assets payoff, the exercise surface could be non connected. Neither we have to search for smart regressors. The idea is to use, regardless of the complexity of the payoff, only the underlying processes. Neural networks with many outputs can interpolate every single assets in the portfolio generated by a single Monte Carlo simulation. This is an essential feature to account for the P&L distribution of the whole portfolio when the dependence structure between the different assets is very strong like the case where one has contingent claims written on the same underlying.

Executives’ Connections to Directors and Internal Governance
Mkrtchyan, Anahit,Hoitash, Udi
Outside directors’ monitoring effectiveness is curtailed by information asymmetry between boards and management. Connections between independent directors and non-CEO executives may overcome this challenge by facilitating information sharing between the connected parties. Such connections can also empower executives to withstand pressure from CEOs to take actions undermining executives’ performance in their functional areas. Indeed, we find that earnings restatements, class-action litigations, and real earnings management decrease when directors are connected with executives responsible for these areas. Overall, findings show that directorâ€"executive ties are associated with stronger internal governance, suggesting that boards may benefit from forging stronger relationships with executives.

How Does the Various Sectors of the Financial Market Influence Growth Around the Globe?
Dwumfour, Richard Adjei,Ntow- Gyamfi, Matthew
We explore the links between financial markets, institutional quality and economic growth. We document that the unconditional effect of finance on growth is ambiguous. This variation is caused by regional bloc, income level and legal origin differences. Our results suggest that, for financial development (banking sector, insurance sector, stock market) to elicit positive effect on growth, there needs to be an effective institutional framework in place. However, in cases where finance in itself elicits positive effect on growth, further tightening of the institutional framework could be harmful to growth; hence, must be done with caution. Policy implications are discussed.

Identifying Financial Constraints
Ferrando, Annalisa,Mulier, Klaas,Cherchye, Laurens,Rock, Bram De,Marijn, Verschelde
We propose a new methodology to recover firm-time varying financial constraints from firms’ production behavior. We model financial constraints as the profitability that firms forgo when budget constraints on production inputs bind, impeding them from using the optimal level of inputs and technology. We estimate and validate our measure using unique data combining firms’ balance sheets with survey information on self-reported financial constraints, like loan rejections. In contrast to three popular indices of financial constraints, our measure recovers financial constraints beyond observable firm characteristics, recovers cross-sectional and time-varying stylized facts of financial constraints, and is applicable to both public and private firms.

Learning a functional control for high-frequency finance
Laura Leal,Mathieu Laurière,Charles-Albert Lehalle

We use a deep neural network to generate controllers for optimal trading on high frequency data. For the first time, a neural network learns the mapping between the preferences of the trader, i.e. risk aversion parameters, and the optimal controls. An important challenge in learning this mapping is that in intraday trading, trader's actions influence price dynamics in closed loop via the market impact. The exploration--exploitation tradeoff generated by the efficient execution is addressed by tuning the trader's preferences to ensure long enough trajectories are produced during the learning phase. The issue of scarcity of financial data is solved by transfer learning: the neural network is first trained on trajectories generated thanks to a Monte-Carlo scheme, leading to a good initialization before training on historical trajectories. Moreover, to answer to genuine requests of financial regulators on the explainability of machine learning generated controls, we project the obtained "blackbox controls" on the space usually spanned by the closed-form solution of the stylized optimal trading problem, leading to a transparent structure. For more realistic loss functions that have no closed-form solution, we show that the average distance between the generated controls and their explainable version remains small. This opens the door to the acceptance of ML-generated controls by financial regulators.

Mathematical Foundations of Regression Methods for the approximation of the Forward Initial Margin
Lucia Cipolina Kun,Simone Caenazzo,Ksenia Ponomareva

Abundant literature has been published on approximation methods for the forward initial margin. The most popular ones being the family of regression methods. This paper describes the mathematical foundations on which these regression approximation methods lie. We introduce mathematical rigor to show that in essence, all the methods propose variations of approximations for the conditional expectation function, which is interpreted as an orthogonal projection on Hilbert spaces. We show that each method is simply choosing a different functional form to numerically estimate the conditional expectation. We cover in particular the most popular methods in the literature so far, Polynomial approximation, Kernel regressions and Neural Networks.

Measuring the Effect of Sustainability on Tobin’s Q
Gregory, Richard Paul
Do sustainable practices affect the value of the firm, as measured by Tobin’s Q ratio, and if so, would its effect be detectable on firm value? We propose a model where a renewable resource is viewed as an input as part of the firm’s production function. It is found that a measure of sustainable resource use must also reflect pricing power of the firm, tax rates and the cost of capital. I then provide evidence from simulations and small sample estimation that simple corrections to sustainability measures suggested by the model improve the statistical power of testing for the effects of sustainability on firm value. The estimated effects of sustainable resource use for a sample of 39 electricity utilities finds that even an improper correction of a sustainability measure can yield substantial improvements.

Monetary Policies and Destabilizing Carry Trades Under Adaptive Learning
Dell'Eva, Cyril,Girardin, Eric,Pintus, Patrick
This paper investigates how different monetary policy designs alter the effect of carry trades on a host small open economy. Capital inflows are expansionary, leading the central bank to raise the interest rate, increasing carry trades' returns, and generating further capital inflows (carry trades' vicious circle). This paper shows how monetary authorities can mitigate or suppress this vicious circle, when agents do not have full information about the central bank's objectives. The best way to deal with the destabilizing effect of carry trades is to target both inflation and capital inflows.

Prior knowledge distillation based on financial time series
Jie Fang,Jianwu Lin

One of the major characteristics of financial time series is that they contain a large amount of non-stationary noise, which is challenging for deep neural networks. People normally use various features to address this problem. However, the performance of these features depends on the choice of hyper-parameters. In this paper, we propose to use neural networks to represent these indicators and train a large network constructed of smaller networks as feature layers to fine-tune the prior knowledge represented by the indicators. During back propagation, prior knowledge is transferred from human logic to machine logic via gradient descent. Prior knowledge is the deep belief of neural network and teaches the network to not be affected by non-stationary noise. Moreover, co-distillation is applied to distill the structure into a much smaller size to reduce redundant features and the risk of overfitting. In addition, the decisions of the smaller networks in terms of gradient descent are more robust and cautious than those of large networks. In numerical experiments, we find that our algorithm is faster and more accurate than traditional methods on real financial datasets. We also conduct experiments to verify and comprehend the method.

Private Real Estate Returns, Style Drift, and Procyclical Risk Taking
Couts, Spencer
This paper documents that development exposure is an important determinant of private real estate returns and market risk exposure. It also documents that open-end private real estate funds have time-varying, procyclical market risk exposure through their development activities. As such, these funds are disproportionately exposed to the downside of the market cycle. Lastly, I find that fund flow pressure is the primary driver of time-varying development exposure. Funds buy a higher proportion of safe, liquid assets compared to risky, illiquid assets when they have larger unfulfilled subscriptions. While this increases assets under management quicker, it also hurts existing investors by decreasing their market risk exposure at the time when it is the most desirable and beneficial. Additionally, funds stop developing as redemption requests increase, leading to lower market risk exposure when the market recovers.

Rate of Convergence of the Probability of Ruin in the Cram\'er-Lundberg Model to its Diffusion Approximation
Asaf Cohen,Virginia R. Young

We analyze the probability of ruin for the {\it scaled} classical Cram\'er-Lundberg (CL) risk process and the corresponding diffusion approximation. The scaling, introduced by Iglehart \cite{I1969} to the actuarial literature, amounts to multiplying the Poisson rate $\la$ by $n$, dividing the claim severity by $\sqrtn$, and adjusting the premium rate so that net premium income remains constant. %Therefore, we think of the associated diffusion approximation as being "asymptotic for large values of $\la$."

We are the first to use a comparison method to prove convergence of the probability of ruin for the scaled CL process and to derive the rate of convergence. Specifically, we prove a comparison lemma for the corresponding integro-differential equation and use this comparison lemma to prove that the probability of ruin for the scaled CL process converges to the probability of ruin for the limiting diffusion process. Moreover, we show that the rate of convergence for the ruin probability is of order $\mO\big(n^{-1/2}\big)$, and we show that the convergence is {\it uniform} with respect to the surplus. To the best of our knowledge, this is the first rate of convergence achieved for these ruin probabilities, and we show that it is the tightest one in the general case. For the case of exponentially-distributed claims, we are able to improve the approximation arising from the diffusion, attaining a uniform $\mO\big(n^{-k/2}\big)$ rate of convergence for arbitrary $k \in \N$. We also include two examples that illustrate our results.

Should I Stay or Should I Go? Trading Behavior Under Ambiguity
Ben-Rephael, Azi,Izhakian, Yehuda (Yud)
We provide new empirical evidence on investors' firm-level trading behavior in response to daily changes in stock ambiguity-Knightian uncertainty. The effect of ambiguity is distinct from and contrasts with the well-documented effect of risk, and shares a similar economic significance. An increase in ambiguity is associated with a subsequent reduction in stock and option trading and holdings, and is consistent with limited participation. A similar response is triggered by closest peers' ambiguity, suggesting information spillovers. Interestingly, an increase in ambiguity is associated with a subsequent increase in book-depth and a lower price impact, consistent with information inertia.

Stock Price Anomalies in Contrast to Stock Performance Predictors â€" A Comprehensive Study of Cement Industry in Pakistan
Nazir, Atif,Alvi, Jahanzaib,Rehan, Muhammad
This research paper has attempted to gauge the relationship amongst dependent and independent variable of firms in Pakistan. Book Value per Share, Earning per Share, Dividend per Share, Gross Domestic Product and Interest Rate are considered as influence factors on movement of Stock Price. For this research 16 organizations are viewed as, recorded in the Pakistan Stock Exchange amid the day and age 2007 to 2016. This exploration will underline on working influences and money related influences and their impact on the profit of the organizations. To gauge the relationship amongst influence and benefit of firms of Pakistan relapse demonstrate and spellbinding measurements will be utilized. Our outcomes will empower the organizations to discover the huge relationship amongst influence and profit of the firm. This study sought to investigate the impact of Book Value per Share, Earning per Share, Dividend per Share, Gross Domestic Product and Interest Rate on Stock Price movement of Pakistan‘s firm. Importantly there is positive relation between independent variable, i.e. Earning per Share, Dividend per Share & Interest Rate and dependent variable that is Stock Price

Stopper-Controller Games embedded in Single-Player Control Problems
Martin Larsson,Marvin S. Mueller,Josef Teichmann

In 2002, Benjamin Jourdain and Claude Martini discovered that for a class of payoff functions, the pricing problem for American options can be reduced to pricing of European options for an appropriately associated payoff, all within a Black-Scholes framework. This discovery has been investigated in great detail by S\"oren Christensen, Jan Kallsen and Matthias Lenga in a recent work in 2020. In the present work we prove that this phenomenon can be observed in a wider context, and even holds true in a setup of non-linear stochastic processes. We analyse this problem from both probabilistic and analytic viewpoints. In the classical situation, Jourdain and Martini used this method to approximate prices of American put options. The broader applicability now potentially covers non-linear frameworks such as model uncertainty and controller-and-stopper-games.

Strategic Timing in Closed-End Fund Portfolio Holdings Disclosure
Kallenos, Theodosis L.,Lesmond, David A.,Nishiotis, George
Using a sample of equity closed-end funds, we document significant portfolio holdings disclosure valuation effects and strategic disclosure timing by portfolio managers. An event study analysis reveals statistically significant positive (negative) abnormal returns associated with early (late) disclosure. We find that the returns of a long-short arbitrage strategy portfolio become statistically significant exactly when the implementation of such a strategy is facilitated by the timely disclosure of portfolio holdings. Our findings support the argument that managers of funds trading at high discounts are more likely to disclose earlier in order to reduce discounts and protect themselves from activist investor attacks. This is despite the documented strong motives for late disclosure stemming from copycatting and front running threats shared with open-end fund managers.

Transmission of the Sovereign Debt Crisis: Bank-Firm Level Evidence From France
Grandi, Pietro,Darriet, Elisa,Guille, Marianne,Belin, Jean
Using a large panel dataset of more than 60.000 firms matched to 125 banks in France, we investigate the transmission of the Sovereign Debt Crisis to the French economy via lending relations. We show that French banks’ exposure to sovereign stress negatively affected their corporate borrowers and this impact is heterogeneous across firms. We document three main findings. First, banks most exposed to risky sovereign debt decreased overall lending by more relatively to less exposed banks during the Sovereign Debt Crisis. Second, firms that borrowed from banks with higher sovereign debt exposure obtained less short-term loans and faced higher funding costs with respect to firms related to other banks. Third, the magnitude of these effects depends on the likelihood of firms being financially constrained: among firms related to banks with larger exposure to sovereign risk, younger and smaller firms were relatively more affected by these credit restrictions. These results support existing evidence on the spill-overs of the Sovereign Debt Crisis in the Euro Area from peripheral to core countries via the direct exposure of their domestic banking system.

Utility-based pricing and hedging of contingent claims in Almgren-Chriss model with temporary price impact
Ibrahim Ekren,Sergey Nadtochiy

In this paper, we construct the utility-based optimal hedging strategy for a European-type option in the Almgren-Chriss model with temporary price impact. The main mathematical challenge of this work stems from the degeneracy of the second order terms and the quadratic growth of the first order terms in the associated HJB equation, which makes it difficult to establish sufficient regularity of the value function needed to construct the optimal strategy in a feedback form. By combining the analytic and probabilistic tools for describing the value function and the optimal strategy, we establish the feedback representation of the latter. We use this representation to derive an explicit asymptotic expansion of the utility indifference price of the option, which allows us to quantify the price impact in options' market via the price impact coefficient in the underlying market.

What Drives Financial Development? A Meta-Regression Analysis
Doucouliagos, Chris,Haan, Jakob de,Sturm, Jan-Egbert
This paper offers a meta-regression analysis of the literature on the drivers of financial development. Our results based on 1900 estimates suggest that institutional quality is positively correlated to both private sector credit and stock market capitalization (both as share of GDP). Domestic financial openness has a positive effect on both proxies for financial development, while trade openness seems only important for stock market capitalization. Inflation has an adverse effect on financial development, which is larger for stock market capitalization. Finally, we conclude that the literature has not yet robustly established that remittances and trust matter for financial development.

When Does Greenwashing Pay Off?
Gregory, Richard Paul
I construct a neoclassical model of investment for a firm that greenwashes its commitment to corporate social responsibility in exaggerating its minimization of using polluting inputs and maximizing its investment in social capital. I assume that greenwashing allows the firm some pricing power in its output market, but in tradeoff, it results in a dead weight loss due to the risk of being caught greenwashing that acts as a negative call option on the increased value of the firm. I find that there are limited circumstances where greenwashing pays off for the firm: when firm volatility is low, when the time till they expect to be caught is short, when interest rates are high and when their pricing power is high. As a result, without government intervention, the circumstances that favor greenwashing are very limited.

iConVis: Interactive Visual Exploration of the Default Contagion Risk for Networked-guarantee Loans
Zhibin Niu,Runlin Li,Junqi Wu,Dawei Cheng,Jiawan Zhang

Groups of enterprises can guarantee each other and form complex networks to obtain loans from commercial banks. During economic slowdown period, the corporate default may spread like a virus and lead to large-scale defaults or even systemic financial crises. To help the financial regulatory authorities and banks manage the risk brought by the networked loans, we identified the default contagion risk as a pivotal issue to take preventive measures, and develop iConVis, an interactive visual analysis tool, to facilitate the closed-loop analysis process. A novel financial metric - contagion effect is formulated to quantify the infectious consequence of the guarantee chains in the network. Based on the metric, we design and implement a serial of novel and coordinated views to address the analysis the financial problem. Experts evaluated the system using real-world financial data. The proposed approach grants them the ability to overturn the previous ad hoc analysis methodology and extends the coverage of the conventional Capital Accord in the banking industry.

Концентрация и конкуренция в современном банковском секторе Сербии: анализ индексов концентрации (Concentration and Competition in Modern Serbian Banking Sector: Concentration Indices Analysis)
Bukvic, Rajko
Russian abstract: Ð'ведение: в статье анализируются степень концентрации и конкуренция в современном банковском секторе в Сербии, который в период трансформации находится в процессе приспособления к рыночным условиям ведения дел. Ð'нимание обращается на ситуацию в текущем десятилетии, в частности на период 2016â€"2019, для которого вычислены соответственные показатели концентрации.Материалы и методы: анализ обоснован в первой очереди на финансовых отчÑ'тах банков, также на квартальных отчÑ'тах Народного банка Сербии. Ð"ля оценки концентрации рынка использованы как традиционные показатели концентрации (CRn и HH индексы) и индексы Ð"жини и Тайдмана-Холла, так и сравнительно редко использованные индексы Линда. Степень концентрации вычислялся на основе пяти балансовых величин: совокупные активы, депозиты, капитал, операционные доходы банков, и кредиты.Результаты: в статье показано, что среди сравнительно большого числа банков в Сербии существующий степень концентрации является низким. Ð'сÑ'-таки, показатели концентрации оказываются достаточно близкими к умеренной степени концентрации, что предупреждает о возможности появления олигополистической структуры, особенно имея в виду уже долго длящийся процесс интеграций и укрупнений в банковском секторе.Обсуждение: в общем-то результаты показывают низкую степень концентрации. Но, уже между самыми простыми показателями CR3 и CR4 выявляется различие: согласно коэффициенту CR4 концентрация является умеренной, почти для всех переменных. Ð'лизкими к умеренной степени концентрации оказались и коэффициенты HH, при этом не в равной степени во всех случаях. Наконец, индексы Линда подтверждают, что существующий степень концентрации отвечает полной конкуренции, с исключением переменной «Капитал», где подозревается олигополистическая структура.Заключение: степень концентрации в банковском секторе Сербии низок, хотя и достаточно близкий умеренной, и несмотря на многолетние процессы укрупнения банков, преимущественно через поглощения. Существующее число банков и соответствующая степень концентрации создают хорошие условия для развития здоровой конкуренции между ними. С другой стороны, полученные результаты не отличаются однозначностью, что особенно оказывается в динамическом плане. Этот момент подчÑ'ркивает не только необходимость использования большего числа показателей, но и особую чувствительность в толковании их результатов. Ð'сÑ' это надо учитывать в последующих анализах.English abstract: Introduction: the paper analyzes the degree of concentration and competition in modern Serbian banking sector in the recent decade, particularly in the years 2016-2019. In the transition period the Serbian banking sector adapt to the market business circumstances.Materials and Methods: the analysis is based on bank financial statements and Quarterly Reviews of National Bank of Serbia. For the estimation of the market concentration, it were used the traditional concentration indicators (CRn and HH indices) and Gini and Tideman-Hall indexes, as well as the relatively rarely used Linda indices. The concentration degree is calculated based on five balance variables: total assets, deposits, capital, operating income of banks, and loans.Results: it has been demonstrated that in the case of the relatively large number of banks in Serbia, the existing concentration degree is relatively low. However, the approximation of the indices to moderate concentration within the period analyzed warns of the appearance of oligopoly, especially in regards to many years continued process of integration and enlargement in banking sector.Discussion: in general the results show the low degree of concentration. But, just between simplest indexes CR3 and CR4 it can be seen the difference: according to coefficient CR4 concentration is moderate, for almost all observes variables. Close to moderate degree of concentration are the indices HH, but not in all cases. Finally, the Linda indices accept, that existing concentration degree comply with perfect competition, but with the exception of the variable “Capital”, where the suspicion to oligopolistic structure was demonstrated.Conclusion: the degree of concentration in Serbian banking sector is low, but close to moderate, despite to many years continued processes of enlargement of banks, principally through the acquisitions. The actual number of banks and adequate market concentration degree provides suitable conditions for the development of healthy competition among banks. On the other side, the results of analysis are not equivocal, and this manifests firstly in dynamic consideration. This emphasizes not only the need for the use of many indicators, but also the sensitivity in interpretation its results. All that must be taken into account in the next analyses.

Управление Предприятием и Интерес Акционеров: Концепция Максимизации Рыночной Стоимости (Corporate Governance and Shareholders’ Interests: Concept of the Maximization of the Market Values of Companies)
Bukvic, Rajko,Rajnović, Ljiljana
Russian abstract: Одним из основных и широко отстаиваемых постановлений корпоративного управления является управление предприятиями в интересах акционеров, Ñ‚.е. собственников предприятия. Этот концепт обоснован на аргументах, что у собственников самый сильный интерес в предприятии и что от этого интереса прямо зависит эффективность ведения дел, пока в то же время интересы акционеров наименее защищены среди интересов всех конституэнтов. Ð' некоторых странах этот концепт воздвигнут до абсолюта (в США как единственый интерес который надо защищать, выдвигается интерес акционеров), но и там где это не правило, Ñ‚.е. где уважаются и интересы других конституэнтов, интерес акционеров неприкосновенен и выдвигается на первое место. Ð' докладе рассматриваются основы и виды, с которыми в различных странах и в различных условиях мотивируется такой образ корпоративного управления, также последствия, которые такие требования и их выполнение порождают. Особенно указывается на крушение концепции максимизации рыночной стоимости акций, которая была исключительно популярной в последние десятилетия XX и в начале этого столетия.English abstract: One of the basic and widely represented corporate governance settings is corporate governance in the interests of shareholders, or company owners. This concept is based on the arguments that the owners have the strongest interest in the company and that the efficiency of the business depends directly on this interest, while at the same time the interests of shareholders are at least protected among the interests of all constituents. In some countries, this concept has been elevated to the absolute (in the United States as the only interest to be protected, the interest of shareholders is emphasized), but where this is not the case, or where the interests of other constituents are respected, the interest of the shareholders is inviolable and stands out in the first plan. The paper discusses the basis and modalities that motivate different forms of corporate governance in different countries and different conditions, as well as the consequences that such requirements and their fulfillment produce. In particular, the crash of the concept of maximizing the market value of shares, which was extremely popular in the last decades of the 20th and the beginning of this century, is particularly indicative.