Research articles for the 2021-04-21
arXiv
A group of heterogeneous players gathers information about an uncertain state before making decisions. Each player allocates his limited bandwidth between biased sources and the other players, and the resulting stochastic attention network facilitates the transmission of news from sources to him either directly or indirectly through the other players. The limit in the bandwidth leads the player to focus on his own-biased source, resulting in occasional cross-cutting exposures but most of the time a reinforcement of his predisposition. It also confines his attention to like-minded friends who, by attending to the same primary source as his, serve as secondary sources in case the news transmission from the primary source to him is disrupted. A mandate on impartial exposures to all biased sources disrupts echo chambers but entails ambiguous welfare consequences. Inside an echo chamber, even a small amount of heterogeneity between players can generate fat-tailed distributions of public opinion, and factors affecting the visibility of sources and players could have unintended consequences for public opinion and consumer welfare.
SSRN
This paper introduces a new database of financial crises, providing an important insight into the causes, duration, and consequences of different types of financial crises. Besides extending the systemic banking crises database by Laeven and Valencia (2020) to the period 1970â"2019, we develop new approaches for the identification of currency and sovereign debt crises, which we regard preferable in some respects to those in the literature. Covering 206 countries, our crises database draws on 151 systemic banking crises (1970-2019), 414 currency crises (1950-2019), 200 sovereign debt crises (1960-2019), 75 twin crises (1970-2019), and 21 triple crises (1970-2019). We provide evidence that banking and debt crises tend to coincide or precede currency crises, while debt crises and banking crises are less likely to coincide or precede each other. We also find that advanced countries experienced longer banking crises but shorter currency, debt, twin, and triple crises.
arXiv
We propose an extension of the Cox-Ross-Rubinstein (CRR) model based on q-binomial (or Kemp) random walks, with application to default with logistic failure rates. This model allows us to consider time-dependent switching probabilities varying according to a trend parameter, and it includes tilt and stretch parameters that control increment sizes. Option pricing formulas are written using q-binomial coefficients, and we study the convergence of this model to a Black-Scholes type formula in continuous time. A convergence rate of order O(1/N) is obtained when the tilt and stretch parameters are set equal to one.
arXiv
Model-Free Reinforcement Learning has achieved meaningful results in stable environments but, to this day, it remains problematic in regime changing environments like financial markets. In contrast, model-based RL is able to capture some fundamental and dynamical concepts of the environment but suffer from cognitive bias. In this work, we propose to combine the best of the two techniques by selecting various model-based approaches thanks to Model-Free Deep Reinforcement Learning. Using not only past performance and volatility, we include additional contextual information such as macro and risk appetite signals to account for implicit regime changes. We also adapt traditional RL methods to real-life situations by considering only past data for the training sets. Hence, we cannot use future information in our training data set as implied by K-fold cross validation. Building on traditional statistical methods, we use the traditional "walk-forward analysis", which is defined by successive training and testing based on expanding periods, to assert the robustness of the resulting agent.
Finally, we present the concept of statistical difference's significance based on a two-tailed T-test, to highlight the ways in which our models differ from more traditional ones. Our experimental results show that our approach outperforms traditional financial baseline portfolio models such as the Markowitz model in almost all evaluation metrics commonly used in financial mathematics, namely net performance, Sharpe and Sortino ratios, maximum drawdown, maximum drawdown over volatility.
arXiv
Backtesting risk measure forecasts requires identifiability (for model calibration and validation) and elicitability (for model comparison). We show that the three widely-used systemic risk measures conditional value-at-risk (CoVaR), conditional expected shortfall (CoES) and marginal expected shortfall (MES), which measure the risk of a position $Y$ given that a reference position $X$ is in distress, fail to be identifiable and elicitable on their own. As a remedy, we establish the joint identifiability of CoVaR, MES and (CoVaR, CoES) together with the value-at-risk (VaR) of the reference position $X$. While this resembles the situation of the classical risk measures expected shortfall (ES) and VaR concerning identifiability, a joint elicitability result fails. Therefore, we introduce a completely novel notion of multivariate scoring functions equipped with some order, which are therefore called multi-objective scores. We introduce and investigate corresponding notions of multi-objective elicitability, which may prove beneficial in various applications beyond finance. In particular, we prove that conditional elicitability of two functionals implies joint multi-objective elicitability with respect to the lexicographic order on $\mathbb{R}^2$, which makes it applicable in the context of CoVaR, MES or (CoVaR, CoES), together with VaR. We describe corresponding comparative backtests of Diebold-Mariano type, for two-sided and 'one and a half'-sided hypotheses, which respect the particularities of the lexicographic order and which can be used in a regulatory setting. We demonstrate the viability of these backtesting approaches in simulations and in an empirical application to DAX 30 and S&P 500 returns.
SSRN
The paper investigates determinants driving the banks to shifts between their interestâ"based andnon interestâ"based activities under the influence of various monetary regimes and debt policies. Bank sectors of Poland, as low inflationary environment and Ukraine, as high inflation environment, were studied. Our empirical findings suggest that monetary policy regime, risk spreads, different debt loads and magnitudes of inflationary shocks all contribute to changing the ratio of interest to nonâ"interest incomes. Yet, in economy with inflation targeting and lower debtâ"toâ"GDP ratio risk spreads, defined as difference between lending rates and relevant government bond yields, are more effective in lowering interest incomes than in more volatile inflationary environment due to risk aversion of banks to new lending. Real deposit rates are barely important factors since both economies are bankingâ"based. Rising proportion of government bonds in bank assets negatively impacts interest incomes in relation to total incomes in a more inflationary and indebted economy, while it increases this proportion in a less indebted economy, which we attribute to stable demand for safe assets in low inflation environment. In the meanwhile, narrowing risk spreads resulting from increases in government borrowing, lead to investment crowdâ"out and more feeâ"oriented banking sector.
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This paper aims to explore the daily and intraday herd behavior of various investor groups trading in an emerging equity market, Borsa Istanbul (BIST). We analyze a one-year tick-by-tick order and trade data of BIST 100 Index stocks and document differences in herding behavior of investor groups considering market capitalization, market conditions, and announcements as well as daily and intraday periodicities. We find that nonprofessional investors (brokerage houses and domestic funds) tend to herd on large (small) stocks; their herding behavior mostly exhibits a U shape (an inverse U shape) during the day. All types of investors tend to herd in down markets on a daily basis while this behavior disappears, even inverts intraday.
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The study investigates the corporate mental image in the Egyptian Stock Exchange (EGX); its Include cognitive dimension, affective dimension, and behavioral dimension; The data were collected by 432 form questionnaire representing current and potential traders at December and October 2020. The Inferential analysis concluded that the determinants of cognitive dimension include "Profitability growth", "dividend payment patterns", "cash Dividend ", " investment recommendations and fair values". But affective dimension include "Top Management", "corporate strategy", "Investor Relations", "corporate's new products" and "Social and environmental activities. Behavioral dimension; the study found difference impact of the corporate mental image between the primary and secondary market. Finally, the study recommends that the corporate focus to managing their mental image as one of the mechanisms for creating value for shareholders.
SSRN
PurposeThe purpose of this paper is to examine the link between banking crises and the subjective well-being of individuals. In addition, the authors examine the transmission of crises from the banking sector to well-being and show that negative financial shocks have significant adverse effects.Design/methodology/approachThe authors employ agent-based modeling to test for the direct and indirect welfare effects of banking crises. The model includes a support vector machine (SVM) optimized subjective well-being function. The existing literature suggests that this is influenced by both the negative psychological effects of recessions and the adverse economic effects of income loss and increased unemployment.FindingsThe authors show that the different choices of policy response to a banking crisis carry different opportunity costs in terms of welfare and that societal preferences should be taken into account. The authors demonstrate that these effects influence different population classes in an asymmetric manner. Finally, the results demonstrate that the welfare loss of a bank failure is much higher than the cost of a bailout.Practical implicationsThe authors are able to propose to the authorities the best policy mix in order to handle banking crises in the most adequate manner, according to society's preferences between financial stability and public goods.Social implicationsThe findings extend the existing literature on subjective well-being, by quantifying the welfare cost of banking crises and showing that authorities should reconsider bank bailouts as a policy solution to bank distress.Originality/valueThe originality of this article lies in the use of an agent-based model to model the relationship between societal well-being and financial stability. Also, the authors extend existing agent-based methodologies to include machine learning optimization techniques.
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The nominee approach to equity crowdfunding pools all crowd investors into one (nominee) account where typically the platform acts as the legal owner but the crowd retains beneficial ownership. The platform plays an active digital corporate governance role that simultaneously enfranchises crowd investors with voting and ownership rights but removes the administrative burden on startups of having to deal with several hundred shareholders. Through an inter-platform and intra-platform analysis of a large sample of 1,018 initial equity crowdfunding campaigns, this paper assesses both the short-term and the long-term impact of nominee versus direct ownership. It finds that nominee initial campaigns are on average more successful than direct ownership campaigns in that they are more likely to succeed, raise more funds, attract overfunding and enjoy greater long run success in terms of successful seasoned equity crowdfunded offerings, numbers of such offerings, and probability of survival. These results hold inter-platform between the two main UK equity crowdfunding platforms (Seedrs and Crowdcube) as well as intra-platform, using the post-2015 quasi-natural experiment when the nominee approach became an option for startups raising capital on Crowdcube.
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This paper proposes a simple dynamic asset pricing model featuring extrapolative market participation by retail investors, that is, increased market participation following high returns in the stock market and high new participation growth (NPG). The model implies that extrapolative market participation induces asset bubbles and large trading volume and produces momentum and value effects simultaneously. More important, the model also implies that NPG positively predicts momentum strategy returns and negatively predicts value strategy returns. Using a composite measure for NPG, we find empirical support for these predictions. The momentum effect is 1.96% per month following high NPG and only 0.51% following low NPG, whereas the value effect is -0.10% per month following high NPG and 0.68% following low NPG. A similar, albeit weaker, pattern also holds for the time-series momentum and value effect.
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I use variation in US consumer bankruptcy laws to study the impact of employees' financial well-being on corporate performance. I find that better employees' financial well-being leads to higher firm profitability and labor productivity. The cross-sectional analysis finds more pronounced effects for more human capital intensive firms and those with fewer routine tasks. These results indicate that workers' financial hardship impairs workplace performance, especially in sectors where cognitive skills directly affect productivity. Overall, my findings suggest that policies promoting individuals' financial well-being have positive spillover effects on corporate performance.
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Portuguese Abstract: Neste capÃtulo, estudam-se duas alternativas. Primei- ro, a receita de um imposto com alÃquota baixa, de 0,005% â" isto é, 5 centavos de euro a cada ⬠1.000,00 â", proposta pelo Grupo Piloto com o objetivo único de levantar receitas para financiar o desenvolvimento. Segundo, a receita de um Im- posto sobre Transações Cambiais com alÃquota muito mais elevada, de até 0,1%, com o duplo objetivo de levantar receita e de dimiuir a especulação.Tomaremos por base trabalhos anteriores (JETIN, 2002, 2007) para calcular as receitas fiscais oriundas do ITC, usando os últimos dados do Banco de Com- pensações Internacionais (Bank for International Settlements â" BIS) sobre os mer- cados estrangeiros de câmbio (BIS, 2007). Calculamos as receitas nos nÃveis mun- dial e regional â" Europa, Tratado de Livre Comércio da América do Norte (North American Free Trade Agreement â" Nafta), América Latina e Ãsia â", no perÃodo de 2001 a 2007, partindo de diferentes hipóteses com respeito à evolução da estrutura do mercado estrangeiro de câmbio e à elasticidade do volume de transações. Finalmente, comparamos nossos resultados com outras estimativas anteriores.English Abstract: This chapter study two alternative scenarios for a currency transaction tax. First, the revenue of a very small levy of 0.005%, (i.e. 5 euro cents on â¬1,000) proposed by the âLeading Group on Solidarity Levies to Fund Developmentâ created in 2006 by the âParis Ministerial Conference on Innovative Financing Mechanismsâ, with the only objective of raising revenues to finance development. Second, the revenue of a currency transaction tax of a much higher level, up to 0.1% with the double objective of raising revenues and curbing speculation which is supported by various NGOs and social movements. We will rely on previous works (Jetin, Bruno 2007) (Jetin, Bruno 2002) to estimate the fiscal revenues of the CTT using the last BIS data on Foreign exchange markets (BIS 2007). We estimate revenues at the world level and at the regional level (Europe, NAFTA, Latin America and Asia) on the period 2001-2007 according to various hypotheses regarding the evolution of the structure of the foreign exchange market and the elasticity of the volume of transactions. We compare our results with other previous estimations.
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This paper introduces a new methodology to estimate timeâvarying alphas and betas in conditional factor models, which allows substantial flexibility in a timeâvarying framework. To circumvent problems associated with the previous approaches, we introduce a Bayesian timeâvarying parameter model where innovations of the state equation have a spikeâandâslab mixture distribution. The mixture distribution specifies two states with a specific probability. In the first state, the innovation variance is set close to zero with a certain probability and parameters stay relatively constant. In the second state, the innovation variance is large and the change in parameters is normally distributed with mean zero and a given variance. The latent state is specified with a threshold that governs the state change. We allow a separate threshold for each parameter; thus, the parameâ ters may shift in an unsynchronized manner such that the model moves from one state to another when the change in the parameter exceeds the threshold and vice versa. This approach offers great flexibility and nests a plethora of other timeâvarying model specifications, allowing us to assess whether the betas of conditional factor models evolve gradually over time or display infrequent, but large, shifts. We apply the proposed methodology to industry portfolios within a fiveâfactor model setting and show that the threshold Capital Asset Pricing Model (CAPM) provides robust beta estimates coupled with smaller pricing errors compared to the alternative approaches. The results have significant implications for the implementation of smart beta strategies that rely heavily on the accuracy and stability of factor betas and yields.
arXiv
The Internet of Value (IOV) with its distributed ledger technology (DLT) underpinning has created new forms of lending markets. As an integral part of the decentralised finance (DeFi) ecosystem, lending protocols are gaining tremendous traction, holding an aggregate liquidity supply of over $40 billion at the time of writing. In this paper, we enumerate the challenges of traditional money markets led by banks and lending platforms, and present advantageous characteristics of DeFi lending protocols that might help resolve deep-rooted issues in the conventional lending environment. With the examples of Maker, Compound and Aave, we describe in detail the mechanism of DeFi lending protocols. We discuss the persisting reliance of DeFi lending on the traditional financial system, and conclude with the outlook of the lending market in the IOV era.
arXiv
We consider identification of peer effects under peer group miss-specification. Our model of group miss-specification allows for missing data and peer group uncertainty. Missing data can take the form of some individuals being completely absent from the data, and the researcher need not have any information on these individuals and may not even know that they are missing. We show that peer effects are nevertheless identifiable if these individuals are missing completely at random or missing at random, and propose a GMM estimator which jointly estimates the sampling probability and peer effects. In practice this means that the researcher need only have access to an individual/household level sample with group identifiers. The researcher may also be uncertain as to what is the relevant peer group for the outcome under study. We show that peer effects are nevertheless identifiable provided that the candidate peer groups are nested within one another (e.g. classroom, grade, school) and propose a non-linear least squares estimator. We conduct a Monte-Carlo experiment to demonstrate our identification results and the performance of the proposed estimators in a setting tailored to real data (the Dartmouth room-mate data).
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We examine an international sample of 68,044 completed, or envisaged but abandoned,M&A transactions involving unlisted targets to determine the effect of transactionrumors on deal-closing propensity and transaction value. Our focus on unlistedfirms eliminates the problem of the groundless M&A rumors that are sometimesspread in public stock markets for trading purposes. Addressing the impact ofrumors is challenging because (i) rumors may be spread on purpose or may emergeaccidentally; (ii) they may be caused by the same observable and omitted driversthat also effect deal closing and transaction value; and (iii) transaction values areonly observable for completed deals and there is no regulatory requirement to disclosethis information. We apply indirect inference methodology to overcome thesechallenges. Our analyses reveal that (1) M&A rumors are deal breakers; (2) rumoreddeals have higher transaction values if they do actually manage to close; and (3) thecombined economic impact of M&A rumors as deal breakers and as value drivers isstrongly negative â" M&A rumors destroyed 32% of the aggregated transaction valueof our sample.
arXiv
This study leverages narrative from global newspapers to construct theme-based knowledge graphs about world events, demonstrating that features extracted from such graphs improve forecasts of industrial production in three large economies compared to a number of benchmarks. Our analysis relies on a filtering methodology that extracts "backbones" of statistically significant edges from large graph data sets. We find that changes in the eigenvector centrality of nodes in such backbones capture shifts in relative importance between different themes significantly better than graph similarity measures. We supplement our results with an interpretability analysis, showing that the theme categories "disease" and "economic" have the strongest predictive power during the time period that we consider. Our work serves as a blueprint for the construction of parsimonious - yet informative - theme-based knowledge graphs to monitor in real time the evolution of relevant phenomena in socio-economic systems.
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While recently the after-cost profits of many anomalies are close to zero, investing according to the Mean-Variance (MV) criterion has never been so rewarding. The Global Minimum Variance Portfolio is the simplest option to profitably gain exposure to the market by timing stock covariances. Minimizing over transaction costs restores credibility in the capability of MV strategies to efficiently target risk premia by timing stock risk premia, additionally it lowers downside risk and enhances scalability. More generally, market timing and estimation error are important drivers behind the MV profitability in the U.S. stock market over the last century.
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Recent research suggests managerial short-termism is associated with lower corporate sustainability, measured by environmental, social, and governance (ESG) ratings and sustainable institutional ownership. Using plant-level data on toxic releases from the United States Environmental Protection Agency (US EPA), we first show that US firms that meet or just beat consensus EPS forecasts (indicating short-termism) release significantly more toxins because they cut pollution abatement costs to boost earnings. Next, we investigate whether the positive relation between meeting benchmarks and pollution is attenuated for environmentally sustainable firms. To our surprise, we find that it is higher for firms with higher ESG ratings (E more than S and G) and higher environmentally sustainable institutional ownership. In addition to contributing to the real earnings management literature by documenting a negative externality of financial reporting incentives on the environment and society, our paper contributes to the ESG literature by showing a positive link between measures of corporate sustainability and managerial short-termism.
arXiv
In this paper, we provide causal evidence on abortions and risky health behaviors as determinants of mental health development among young women. Using administrative in- and outpatient records from Sweden, we apply a novel grouped fixed-effects estimator proposed by Bonhomme and Manresa (2015) to allow for time-varying unobserved heterogeneity. We show that the positive association obtained from standard estimators shrinks to zero once we control for grouped time-varying unobserved heterogeneity. We estimate the group-specific profiles of unobserved heterogeneity, which reflect differences in unobserved risk to be diagnosed with a mental health condition. We then analyze mental health development and risky health behaviors other than unwanted pregnancies across groups. Our results suggest that these are determined by the same type of unobserved heterogeneity, which we attribute to the same unobserved process of decision-making. We develop and estimate a theoretical model of risky choices and mental health, in which mental health disparity across groups is generated by different degrees of self-control problems. Our findings imply that mental health concerns cannot be used to justify restrictive abortion policies. Moreover, potential self-control problems should be targeted as early as possible to combat future mental health consequences.
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This study on News Media Framing and the Coverage of Boko-Haram Insurgency in North-East Nigeria is a position paper set out to identify the pattern of frames adopted by Nigerian news media in the coverage of Boko Haram insurgency. Because since2009 when the activities of the Boko Haram sect became pronounced in Nigeria, its activities have continued to dominate public discourse. To this end, the media at national and international fronts keyed into the reportage of the rebellious activities of this terror group. Through various strategies adopted by the sect, they carry out their nefarious activities which include: suicide bombings, massacre, abductions, and other deadly activities. The study established that Nigerian media dominantly use news frames: peace neutral and mixed frames. The successes, most of which were attributed to the way and manner in which media handles them. The study blamed the media on several occasions for flaming the conflict, particularly regarding the nature of their reportage. The study also addressed the critical question; that the Nigerian media can play a critical role in resolving and or addressing insurgency in Nigeria. Adopting the media framing theory, it, therefore, recommends the optimization of positive frames to promote the peace media initiative which forms the critical plank of positive media interventions.
arXiv
In the context of nonlinear prices, the empirical evidence suggests that the consumers have cognitive biases represented in a limited understanding of nonlinear price structures, and they respond to some alternative perceptions of the marginal prices. In particular, consumers usually make choices based more on the average than the marginal prices, which can result in a suboptimal behavior. Taking the misspecification in the marginal price as exogenous, this document analyzes how is the optimal quadratic price scheme for a monopolist and the optimal quadratic price scheme that maximizes welfare when there is a continuum of representative consumers with an arbitrary perception of the marginal price. Under simple preferences and costs functional forms and very straightforward hypotheses, the results suggest that the bias in the marginal price doesn't affect the maximum welfare attainable with quadratic price schemes, and it has a negligible effect over the efficiency cost caused by the monopolist, so the misspecification in the marginal price is not relevant for welfare increasing policies. However, almost always the misspecification in the marginal price is beneficial for the monopolist. An interesting result is that under these functional forms, more misspecification in the marginal price is beneficial for both the consumers and the monopolist if the level of bias is low, so not always is socially optima to have educated consumers about the real marginal price. Finally, the document shows that the bias in the marginal price has a negative effect on reduction of aggregate consumption using two-tier increasing tariffs, which are commonly used for reduction of aggregate consumption.
arXiv
We develop a quantitative framework for understanding the class of wicked problems that emerge at the intersections of natural, social, and technological complex systems. Wicked problems reflect our incomplete understanding of interdependent global systems and the hyper-risk they pose; such problems escape solutions because they are often ill-defined and thus mis-identified and under-appreciated by problem-solvers and the communities they constitute. Because cross-boundary problems can be dissected from various viewpoints, such diversity can nevertheless contribute confusion to the collective understanding of the problem. We illustrate this paradox by analyzing the development of both topical and scholarly communities within three wicked domains: deforestation, invasive species, and wildlife trade research. Informed by comprehensive bibliometric analysis of both topical and collaboration communities emerging within and around each domain, we identify symptomatic characteristics of wicked uncertainty based upon quantitative assessment of consolidation or diversification of knowledge trajectories representing each domain. We argue that such knowledge trajectories are indicative of the underlying uncertainties of each research domain, which tend to exacerbate the wickedness of the problem itself. Notably, our results indicate that wildlife trade may become a neglected wicked problem due to high uncertainty, research paucity, and delayed knowledge consolidation.
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Online Appendix A to ``Security Design for Asset Acquisitions'' shows that seller debt securities can be optimal security designs when informed sellers, rather than uninformed buyers, make acquisition offers, and when acquirers are cash constrained. In contrast, acquirer overconfidence and seller private information are essential components of our analysis of seller debt financing. Online Appendix B to ``Security Design for Asset Acquisitions'' shows that the ratio condition, Assumption 4, is satisfied by all standard textbook distributions (supported by the non-negative real line) whenever the standard monotone likelihood ratio conditions (Assumptions 1 and 2) of security design are satisfied. The distributions families considered are Chi-Squared, Exponential, Gamma, Gompertz, Half Normal, Lognormal, and Weibull. General sufficient conditions for the satisfaction of Assumption 5 are also developed.The paper is available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3731086.
arXiv
This paper studies the finite horizon portfolio management by optimally tracking a ratcheting capital benchmark process. It is assumed that the fund manager can dynamically inject capital into the portfolio account such that the total capital dominates a non-decreasing benchmark floor process at each intermediate time. The tracking problem is formulated to minimize the cost of accumulated capital injection. We first transform the original problem with floor constraints into an unconstrained control problem, however, under a running maximum cost. By identifying a controlled state process with reflection, the problem is further shown to be equivalent to an auxiliary problem, which leads to a nonlinear Hamilton-Jacobi-Bellman (HJB) equation with a Neumann boundary condition. By employing the dual transform, the probabilistic representation and some stochastic flow analysis, the existence of the unique classical solution to the HJB equation is established. The verification theorem is carefully proved, which gives the complete characterization of the feedback optimal portfolio. The application to market index tracking is also discussed when the index process is modeled by a geometric Brownian motion.
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This paper investigates the effects of ownership patterns on bank cost and profit efficiencies taking a sample of 607 commercial banks operating in 53 African countries during the period 2005-2015. Using pooled and modified true fixed effects (TFE) stochastic frontier panel approaches, we obtain two principal results. First, foreign-owned banks are more profit and cost efficient than their domestic peers. Second, privately owned banks outperform state-owned banks. These findings result not only from bank-level inefficiency but also from differences related to other bank- and country-specific factors. Specifically, larger, older, and listed banks with many years of operations in host countries are associated with higher cost and profit efficiency. This study also reveals that ownership concentration (blockholding) has adverse effects for the profit and cost efficiency of banks.
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Social enterprises (SEs) have been active for some decades and have been regulated by law in several countries. Their operation showed ability to complement the provision of welfare services, especially social services, by the public sector and private enterprises, and to innovate in the introduction of new services, organizational and managerial models. In some cases, SEs succeeded in producing and innovating in an autonomous way, without depending on public financial support and procurement agreements. This paper starts from the state of the art in the study of SEs to propose different avenues through which they can be able to expand supply of welfare services and contribute to the decentralization of welfare systems. It traces these specific abilities to SEsâ peculiar institutional structure, especially their non-profit nature, the pursuit of public benefit and social missions, and multi-stakeholder governance. This last feature is considered the most remarkable emerging characteristic in the evolution of this organizational form. The paper then proceeds to focus on price discrimination as specific governance mechanism of the relations of production and exchange, involving different stakeholders and allowing SEs to widen their supply of services, achieve financial sustainability and contribute to the decentralization of the welfare system.
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The aim of this manuscript is to provide the mathematical and statistical foundations of actuarial learning. This is key to most actuarial tasks like insurance pricing, product development, claims reserving and risk management. The basic approach to these tasks is regression modeling. This manuscript describes the exponential dispersion family which is the most commonly used family of distributions in actuarial modeling. It discusses model fitting and parameter estimation using classical tools from mathematical statistics. It then introduces the crucial tools for prediction and forecast evaluation. Based on these statistical concepts various regression models are studied such as generalized linear models, mixture models and neural network regression models. We explore these modeling approaches from a theoretical and a practical viewpoint on publicly available data and we discuss their applications to insurance modeling. This involves model fitting using Fisher's scoring method, gradient descent algorithms or the expectation-maximization algorithm, model selection, parameter selection, regularization, etc.
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We propose a novel approach to quantify spillovers on financial markets based on a structural version of the Diebold-Yilmaz framework. Key to our approach is a SVARGARCH model that is statistically identified by heteroskedasticity, economically identified by maximum shock contribution and that allows for time-varying forecast error variance decompositions. We analyze credit risk spillovers between EZ sovereign and bank CDS. Methodologically, we find the model to better match economic narratives compared with common spillover approaches and to be more reactive than models relying on rolling window estimations. We find, on average, spillovers to explain 37% of the variation in our sample, amid a strong variation of the latter over time.
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We propose a novel approach to quantify spillovers on financial markets based on a structural version of the Diebold-Yilmaz framework. Key to our approach is a SVARGARCH model that is statistically identified by heteroskedasticity, economically identified by maximum shock contribution and that allows for time-varying forecast error variance decompositions. We analyze credit risk spillovers between EZ sovereign and bank CDS. Methodologically, we find the model to better match economic narratives compared with common spillover approaches and to be more reactive than models relying on rolling window estimations. We find, on average, spillovers to explain 37% of the variation in our sample, amid a strong variation of the latter over time.
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We study the effects of going public using a unique panel of firms in 16 European countries for which we observe financial data before and after firms' initial-public-offering (IPO) attempts. We compare firms that complete their IPO with firms that withdraw their IPO. We instrument the going public decision using prior market returns. We find that firm profitability goes up after going public - reversing previous results in the literature. We also find an expansion in the number of subsidiaries and countries where firms operate post-IPO. Our findings for firms in financially dependent industries and in countries with higher investor protection suggest that going public relaxes financial constraints and has a stronger impact when agency problems are contained. Overall, our results are consistent with IPOs moving firms towards a strategy of commercialization that privileges profitability.
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This paper investigates the role of executive compensation in the transmission of monetary shocks to corporate investments. We find that a managerial compensation structure that facilitates risk-taking (high Vega) is a positive and significant contributor to the translation of monetary shocks into subsequent corporate investments. The investments of high Vega firms are three times as sensitive to monetary shocks as the investments of low Vega firms. This mediating effect is robust across size, age, and leverage. We also show that the executive compensation Vega is highly responsive to monetary shocks, especially for firms with apriori preference for risk-taking. The design of executive compensation packages not only addresses agency problems within the firm but also has relevant macroeconomic consequences.
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Abstract. This paper attempts to determine if intellectual capital (IC) has an impact on firm performance in the industrial companies in Jordan. A quantitative approach was used, with value-added intellectual coefficient (VAICTM) methodology of IC measurement. Secondary data were used in measuring the study variables. The relationship between VAICTM in fourth industrial revolution (IR 4.0) and the ratios of earnings per share (EPS) and return on assets (ROA) were examined. The study sample comprised 50 industrial companies listed on the Amman Stock Exchange (ASE) covering the 2008-2017 period. Multiple Regression analysis was used in data analysis, involving panel data models. The obtained results prove a positive significant influence of VAICTM on EPS and ROA, and a positive significant relationship between human capital efficiency (HCE) and structural capital efficiency (SCE), and EPS and ROA, while no relationship was found between capital employed efficiency (CEE) and EPS and ROA. The results suggest the need for industrial companies in Jordan and in the Middle East to focus on intellectual capital (IC) elements, particularly human capital (HC), which is core to VAICTM. Moreover, this study is valuable to policymakers and managers in determining the industry development for better corporate returns.
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The share of households using mobile banking has increased from 16% to 28% between 2014 and 2019. Using data across all census tracts between 2014 and 2019, we investigate the incidence of mobile banking and its relationship with traditional brick-and-mortar bank branches. First, we document three stylized facts: mobile banking is more common in areas with a higher concentration of individuals employed in information and professional services sectors, areas with higher shares of college graduates, and areas with a higher share of youth between ages 18 and 30. Second, we estimate the elasticity between mobile banking and both the incidence of banking deserts and the number of physical bank locations. Exploiting within-tract variation and controlling for time-varying shocks, we find that residents of banking deserts are 1.3-4.7% more likely to have mobile banking and that an additional physical branch opening, net of closures, is associated with a 0.3-0.7% decline in mobile banking usage. Our results suggest that mobile banking can serve as an important vehicle for financial inclusion by providing an alternate avenue for consumers to access banking services, particularly in rural communities.
SSRN
This paper is an effort to bring collectively all such research instruments, scales, tools & techniques, so as to help prospective researchers in comparing the same and selecting the one which is close to their usage. The paper also tries to summarize the dimensions and attributes used by authors for different service businesses. The methodology used is a plain evaluation method between a variety of studies conducted on service quality issues, using available research papers from different sources like online databases example- EBSCO & Emerald, and journals from libraries.
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This paper suggests insurance represents a quid pro quo transaction across states of the world and is purchased to transfer income to a state where it is more valued. It also suggests that gambling represent a similar quid pro quo transaction across states but that consumers gamble to transfer income to a state where it is less costly to obtain. In both cases, preferences regarding uncertainty do not motivate demand, but uncertainty allows for the augmentation of the payout compared to the premium or wager. These motivations do not conflict with evidence supporting prospect theory and accommodate the insurance-purchasing gambler. The implications are that insurance is far more valuable than conventional theory suggests, and that recreational gambling may also be more valuable.
SSRN
Prior research has proposed numerous variables to differentiate between well-performing and poorly performing active equity funds. We combine eight prominent representatives of these measures to obtain a composite, aggregate fund predictor. While only three of the eight individual variables are significant predictors of future fund performance in a multivariate setting, the composite predictor has strong forecasting power. A hypothetical quintile-based long-short strategy based on the composite predictor realizes a four-factor alpha of 5.4% per year. The performance spread is robust to different regression specifications, is similar for different size classes and investment styles, and persists over time. Our results point towards inefficiency in the market for actively managed equity funds.
arXiv
We prove three theorems about the exact solutions of a generalized or interacting Black-Scholes equation that explicitly includes arbitrage bubbles. These arbitrage bubbles can be characterized by an arbitrage number $A_N(T)$. The first theorem states that if $A_N(T) = 0$, then the solution at the maturity of the interacting equation is identical to the solution of the free Black-Scholes equation with the same initial interest rate $r$. The second theorem states that if $A_N(T) \ne 0$, the solution can be expressed in terms of all higher derivatives of solutions to the free Black-Scholes equation with the initial interest rate $r$. The third theorem states that whatever the arbitrage number is, the solution is a solution to the free Black-Scholes equation with a variable interest rate $r(\tau) = r + (1/\tau) A_N(\tau)$. Also, we show, by using the Feynman-Kac theorem, that for the special case of a Call contract, the exact solution for a Call with strike price $K$ is equivalent to the usual Call solution to the Black-Scholes equation with strike price $\tilde{K} = K e^{-A_N(T)}$.
arXiv
An approach to modelling volatile financial return series using stationary d-vine copula processes combined with Lebesgue-measure-preserving transformations known as v-transforms is proposed. By developing a method of stochastically inverting v-transforms, models are constructed that can describe both stochastic volatility in the magnitude of price movements and serial correlation in their directions. In combination with parametric marginal distributions it is shown that these models can rival and sometimes outperform well-known models in the extended GARCH family.