# Research articles for the 2020-07-13

A micro-to-macro approach to returns, volumes and waiting times
Guglielmo D'Amico,Filippo Petroni
arXiv

Fundamental variables in financial market are not only price and return but a very important role is also played by trading volumes. Here we propose a new multivariate model that takes into account price returns, logarithmic variation of trading volumes and also waiting times, the latter to be intended as the time interval between changes in trades, price, and volume of stocks. Our approach is based on a generalization of semi-Markov chains where an endogenous index process is introduced. We also take into account the dependence structure between the above mentioned variables by means of copulae. The proposed model is motivated by empirical evidences which are known in financial literature and that are also confirmed in this work by analysing real data from Italian stock market in the period August 2015 - August 2017. By using Monte Carlo simulations, we show that the model reproduces all these empirical evidences.

A stochastic control problem with linearly bounded control rates in a Brownian model
Jean-François Renaud,Clarence Simard
arXiv

Aiming for more realistic optimal dividend policies, we consider a stochastic control problem with linearly bounded control rates using a performance function given by the expected present value of dividend payments made up to ruin. In a Brownian model, we prove the optimality of a member of a new family of control strategies called delayed linear control strategies, for which the controlled process is a refracted diffusion process. For some parameters specifications, we retrieve the strategy initially proposed by Avanzi & Wong (2012) to regularize dividend payments, which is more consistent with actual practice.

An Effectiveness Assessment of Preventive Management Strategies in Order to Manage Non Performing Assets in Indian Banks: A Case Study
Meher, Bharat Kumar,Puntambekar, G. L.,Hawaldar, Iqbal Thonse ,Spulbar, Cristi Marcel ,Birau, Felicia Ramona ,Rebegea, Christian
SSRN
There are two kinds of strategies to control Non Performing Assets i.e. curative and preventive. The paper is an attempt to focus on the effectiveness of various preventive strategies in controlling NPA in future. For this study primary data have been collected from 82 branches out of 138 branches of Sagar District in Madhya Pradesh of India. The respondents are the branch managers or recovery officer of each branch. The primary data are related to the causes of NPA, actual usage of preventive measures and effectiveness of each preventive strategy. It highlights few new causes which are barely covered by the earlier researches. The study also represents the actual usage of various preventive measures along with the effectiveness of preventive measures in averting NPA to be occurred in future. The outcome of this study could provide a valuable insight about which strategy is more effective to prevent these stressed assets. Besides that, it could aware the banking authorities regarding the problems faced by the managers in using the preventive measure.

Applied Finance and The Third Culture
Cates, Sonya,Garrahan, Maria,Lawrence, Stephen
SSRN
In his 2001 paper, Leo Breiman describes two diametrically opposed cultures in data science: the model driven statistician and the algorithm driven data scientist. His argument, that an algorithmic approach is often preferable to an iterative model-driven approach is unlikely to resonate with many financial professionals for whom theory is king, and simplicity is a virtue. This third culture of applied finance is as far removed from either culture described in the original paper.We propose a horse race between these three cultures: applied finance and an iterative search of simple heuristic models, traditional econometricians armed with classical regression techniques and data science with a mature approach nonlinear algorithmic exploration. We compare several approaches to modeling market volatility and downside risk and explore the role that modeling discipline has on the stability of the outcome. Our tests are performed both on historical equity market and currency market returns and on a return-mimicking data generating process, from which we can more thoroughly test the stability of each approach.We find that each culture has its own idiosyncrasies and limitations, which need to be carefully understood as practitioners start to experiment with tools from other disciplines. The necessity of algorithmic approaches to harness the burgeoning opportunities of alternative data may be tempered by the limited work that has been done to bridge the knowledge and techniques of the three cultures.

CEO Turnover and Bankrupt Firmsâ€™ Emergence
Lin, Beiqi,Liu, Chelsea,Tan, Kelvin Jui Keng,Zhou, Qing
SSRN
This paper examines whether CEO turnover within a bankrupt firm predicts the firmâ€™s likelihood to reemerge from bankruptcy proceedings as a reorganized entity. Using 836 bankruptcy cases filed under Chapter 11 of the United States Bankruptcy Code from 1989 through 2016, we show that firms that undergo CEO turnover are significantly more likely to emerge from Chapter 11 proceedings. We conduct further analyses to examine the potential mechanisms through which CEO turnover is linked to a firmâ€™s chance of emergence. Consistent with the perspective that CEO turnover constitutes an observable event that can signal creditor support, we find that CEO turnover in bankrupt firms is positively associated with debtor-in-possession financing. Additionally, there is a significant increase in managerial quality post-turnover. Further, we document that the predictive power of CEO turnover is stronger in bankruptcy cases with greater uncertainty, such as in free-fall bankruptcies, where there is less pre-existing agreement between the firm and its creditors. Overall, our findings provide valuable insight into external investors and stakeholder groups, whose interests are significantly impacted by corporate bankruptcies.

Compensated and Uncompensated Risks In Global Factor Investing
SSRN
Global equity risk factors that are constructed by sorting stocks on firm characteristics associated with expected returns contain embedded region and sector exposures. We show that these positions lead to uncompensated volatility. Hedging out both region and sector exposures simultaneously increases the Sharpe ratio of the typical global factor by 50%. Hedged factors, individually or in a model, always subsume their non-hedged counterparts. Our results have implications for international asset pricing and portfolio management.

Cross-Country Differences in the Effect of Political Connections on Stock Price Informativeness
SSRN
Using an international sample of firms from 28 countries, we document that there exists a negative relationship between political connections and the informativeness of stock price, as measured by idiosyncratic volatility (IV). This finding is robust to alternative regression specifications, sub-samples analyses, and concerns related to endogeneity. A more detailed analysis shows that out of the different types of possible connections, the connectedness of the owners is the primary driver of this result. Further, the negative association is only significant for firms in countries characterized by low institutional quality (i.e. corrupted countries, countries with low access to external equity markets, and countries with low media penetration). There is no evidence of any relation between political connections and stock price informativeness for firms in countries characterized by high institutional quality. Overall, our results show that although political connections exacerbate rent-seeking that weaken the firmsâ€™ information environments on average, the negative information consequences are compensated by the countriesâ€™ institutional quality.

Data Normalization for Bilinear Structures in High-Frequency Financial Time-series
Dat Thanh Tran,Juho Kanniainen,Moncef Gabbouj,Alexandros Iosifidis
arXiv

Financial time-series analysis and forecasting have been extensively studied over the past decades, yet still remain as a very challenging research topic. Since the financial market is inherently noisy and stochastic, a majority of financial time-series of interests are non-stationary, and often obtained from different modalities. This property presents great challenges and can significantly affect the performance of the subsequent analysis/forecasting steps. Recently, the Temporal Attention augmented Bilinear Layer (TABL) has shown great performances in tackling financial forecasting problems. In this paper, by taking into account the nature of bilinear projections in TABL networks, we propose Bilinear Normalization (BiN), a simple, yet efficient normalization layer to be incorporated into TABL networks to tackle potential problems posed by non-stationarity and multimodalities in the input series. Our experiments using a large scale Limit Order Book (LOB) consisting of more than 4 million order events show that BiN-TABL outperforms TABL networks using other state-of-the-arts normalization schemes by a large margin.

Did Delaware Really Kill Corporate Law? Shareholder Protection in a Post-Corwin World
Gatti, Matteo
SSRN
Corwin v. KKR, one of many recent cases aiming to mitigate the â€œdeal taxâ€ in M&A represented by baseless litigation, is considered one of the most important corporate law decisions of the 2000s. Corwin shields directors from the enhanced scrutiny of Revlon in favor of the business judgment rule whenever a transaction â€œis approved by a fully informed, unco-erced vote of the disinterested stockholders.â€ Many legal commentators see Corwin as the poster child of an ongoing process that has been emphatically labeled with expressions such as â€œDelawareâ€™s retreat,â€ â€œthe fall of Delaware standards,â€ and even â€œthe death of corporate law;â€ in fact, the mainstream view among scholars is that Corwin is a setback in shareholder protection. This Article challenges such view and argues that shareholder protections in Revlon M&A deals have not suddenly vanished. First, Corwin applies only in the presence of certain preconditions: plaintiffsâ€™ efforts have simply been re-channeled around them. Corwin has in fact expanded the breadth of litigation challenging lack of â€œfull information.â€ Also, the requirement that shareholder approval be unco-erced is bound to pose a limit on certain director abuses in the sale process and in the adoption of deal protection devices. This Article reports of original empirical data on transactions post Corwin suggesting that not much has changed in deal-making: in other words, the decision has not opened the floodgates to bad process, possibly because deal planners anticipate the possibility that rival bids will arise, possibly because the preconditions to Corwin are taken very seriously (especially if coercion constrains ability to offer outrageous deal protection devices), and possibly because corporate planners adhere to norms and best practices and in the worst cases deal lawyers rein in their clientsâ€™ impulses.

Discounting Damage: Non-Linear Discounting and Default Compensation. Valuation of Non-Replicable Value and Damage
Christian P. Fries
arXiv

In this short note we develop a model for discounting.

A focus of the model is the discounting, when discount factors cannot be derived from market products. That is, a risk-neutralizing trading strategy cannot be performed.

This is the case, when one is in need of a risk-free (default-free) discounting, but default protection on funding providers is not traded. For this case, we introduce a default compensation factor ($\exp(+\tilde{\lambda} T)$) that describes the present value of a strategy to compensate for default (like buying default protection would do).

In a second part, we introduce a model, where the survival probability depends on the required notional. This model is different from the classical modelling of a time-dependent survival probability ($\exp(-\lambda T)$). The model especially allows that large liquidity requirements are instantly more likely do default than small ones.

Combined the two approaches build a framework in which discounting (valuation) is non-linear.

The framework can lead to the effect that discount-factors for very large liquidity requirements or projects are an increasing function of time.

Do Busy Directors Impede or Spur Bank Performance and Bank Risks? Event Study Evidence from Brazil
Mbanyele, William
SSRN
The paper investigates the implications of busy directors on bank performance and bank risks in Brazil. The study employs an event study based on a change in board status as an identification strategy, Heckmanâ€™s two-stage model, and the propensity score matching method to account for endogeneity. The study findings show that busy directors contribute to an increase in bank market value. Regarding bank risks, the study shows that multiple directorships contribute to an increase in asset risk and insolvency risk. The study contributes to the existing literature by showing that busy directors are associated with high bank risks in foreign-owned banks while they disproportionately reduce bank risks in state-owned banks. Considering the importance of bank stability in promoting economic growth in Brazil and the positive impact of busy directors on bank risks, there is need for the policymakers to craft clear corporate governance clauses which guide the selection of multiple directors and enforce feedback and accountability mechanisms that govern busy directors who serve in Brazilian banks. Reducing excessive participation for busy directors serving in bank boards ensures that the directors have adequate time and attention to discharge their governance responsibilities efficiently, thus resulting in robust risk monitoring strategies in bank operations.

Do Pension Benefits Accelerate Cognitive Decline? Evidence from Rural China
arXiv

Higher life expectancy and rapidly aging populations in developing countries, especially in the last three decades, have created the need for policymakers to introduce pension programs in developing countries. China launched the New Rural Pension Scheme (NRPS) in 2009 to ease internal demographic pressures and concerns about old-age poverty. Using data from the introduction of the NRPS in China, we estimate the effects of pension benefits, due to participation in the NRPS, on individual cognition, measured by episodic memory and intact mental status, among individuals aged 60 and above. We find large negative effects of the provision of pension benefits on cognitive functioning among the elderly. We detect the most substantial impact of the program to be on delayed recall, a measure implicated in neurobiological research as a significant predictor of the onset of dementia. We show suggestive evidence that the program leads to stronger negative impacts among the female sample. Our findings support the mental retirement hypothesis, that decreased mental activity results in atrophy of cognitive skills. We show that retirement plays a significant role in explaining cognitive decline at older ages.

Driver Surge Pricing
arXiv

Ride-hailing marketplaces like Uber and Lyft use dynamic pricing, often called surge, to balance the supply of available drivers with the demand for rides. We study driver-side payment mechanisms for such marketplaces, presenting the theoretical foundation that has informed the design of Uber's new additive driver surge mechanism. We present a dynamic stochastic model to capture the impact of surge pricing on driver earnings and their strategies to maximize such earnings. In this setting, some time periods (surge) are more valuable than others (non-surge), and so trips of different time lengths vary in the induced driver opportunity cost.

First, we show that multiplicative surge, historically the standard on ride-hailing platforms, is not incentive compatible in a dynamic setting. We then propose a structured, incentive-compatible pricing mechanism. This closed-form mechanism has a simple form and is well-approximated by Uber's new additive surge mechanism. Finally, through both numerical analysis and real data from a ride-hailing marketplace, we show that additive surge is more incentive compatible in practice than is multiplicative surge.

Dynamic Network Risk
Jozef Barunik,Michael Ellington
arXiv

This paper examines the pricing of short-term and long-term dynamic network risk in the cross-section of stock returns. Stocks with high sensitivities to dynamic network risk earn lower returns. We rationalize our finding with economic theory that allows the stochastic discount factor to load on network risk through the precautionary savings channel. A one-standard deviation increase in long-term (short-term) network risk loadings associate with a 7.66% (6.71%) drop in annualized expected returns.

Dynamical approach to Zipf's law
Giordano De Marzo,Andrea Gabrielli,Andrea Zaccaria,Luciano Pietronero
arXiv

The rank-size plots of a large number of different physical and socio-economic systems are usually said to follow Zipf's law, but a unique framework for the comprehension of this ubiquitous scaling law is still lacking. Here we show that a dynamical approach is crucial: during their evolution, some systems are attracted towards Zipf's law, while others presents Zipf's law only temporarily and, therefore, spuriously. A truly Zipfian dynamics is characterized by a dynamical constraint, or coherence, among the parameters of the generating PDF, and the number of elements in the system. A clear-cut example of such coherence is natural language. Our framework allows us to derive some quantitative results that go well beyond the usual Zipf's law: i) earthquakes can evolve only incoherently and thus show Zipf's law spuriously; this allows an assessment of the largest possible magnitude of an earthquake occurring in a geographical region. ii) We prove that Zipfian dynamics are not additive, explaining analytically why US cities evolve coherently, while world cities do not. iii) Our concept of coherence can be used for model selection, for example, the Yule-Simon process can describe the dynamics of world countries' GDP. iv) World cities present spurious Zipf's law and we use this property for estimating the maximal population of an urban agglomeration.

Equity Tail Risk in the Treasury Bond Market
Mirco Rubin,Dario Ruzzi
arXiv

This paper quantifies the effects of equity tail risk on the US government bond market. We estimate equity tail risk with option-implied stock market volatility that stems from large negative price jumps, and we assess its value in reduced-form predictive regressions for Treasury returns and a term structure model for interest rates. We find that the left tail volatility of the stock market significantly predicts one-month excess returns on Treasuries both in- and out-of-sample. The incremental value of employing equity tail risk as a return forecasting factor can be of economic importance for a mean-variance investor trading bonds. The estimated term structure model shows that equity tail risk is priced in the US government bond market and, consistent with the theory of flight-to-safety, Treasury prices increase when the perception of tail risk is higher. Our results concerning the predictive power and pricing of equity tail risk extend to major government bond markets in Europe.

Firm-level Climate Change Exposure
Sautner, Zacharias,van Lent, Laurence,Vilkov, Grigory,Zhang, Ruishen
SSRN
We introduce a method that identifies firm-level climate change exposures from conversation in earnings conference calls of more than 10,000 firms from 34 countries between 2002 and 2019. The method captures exposures related to opportunity, physical, and regulatory shocks associated with climate change. The exposure measures exhibit cross-sectional and time-series variations which align with reasonable priors, and are better in capturing firm-level variation than carbon intensities or ratings. The exposure measures relate to economic factors that prior work has identified as important correlates of climate change exposure (e.g., public climate attention). Exposure to regulatory shocks negatively correlates with firm valuations, but only in recent years.

Government intervention modeling in microeconomic company market evolution
Michał Chorowski,Ryszard Kutner
arXiv

Modern technology and innovations are becoming more crucial than ever for the survival of companies in the market. Therefore, it is significant both from theoretical and practical points of view to understand how governments can influence technology growth and innovation diffusion (TGID) processes. We propose a simple but essential extension of Ausloos-Clippe-P\c{e}kalski and related Cichy numerical models of the TGID in the market. Both models are inspired by the nonlinear non-equilibrium statistical physics. Our extension involves a parameter describing the probability of government intervention in the TGID process in the company market. We show, using Monte Carlo simulations, the effects interventionism can have on the companies' market, depending on the segment of firms that are supported. The high intervention probability can result, paradoxically, in the destabilization of the market development. It lowers the market's technology level in the long-time limit compared to markets with a lower intervention parameter. We found that the intervention in the technologically weak and strong segments of the company market does not substantially influence the market dynamics, compared to the intervention helping the middle-level companies. However, this is still a simple model which can be extended further and made more realistic by including other factors. Namely, the cost and risk of innovation or limited government resources and capabilities to support companies.

Holding-Based Evaluation upon Actively Managed Stock Mutual Funds in China
Huimin Peng
arXiv

We analyze actively managed mutual funds in China from 2005 to 2017. We develop performance measures for asset allocation and selection. We find that stock selection ability from holding-based model is positively correlated with selection ability estimated from Fama-French three-factor model, which is price-based regression model. We also find that industry allocation from holding-based model is positively correlated with timing ability estimated from price-based Treynor-Mazuy model most of the time. We conclude that most actively managed funds have positive stock selection ability but not asset allocation ability, which is due to the difficulty in predicting policy changes.

How Safe are European Safe Bonds? An Analysis from the Perspective of Modern Portfolio Credit Risk Models
Rüdiger Frey,Kevin Kurt,Camilla Damian
arXiv

Several proposals for the reform of the euro area advocate the creation of a market in synthetic securities backed by portfolios of sovereign bonds. Most debated are the so-called European Safe Bonds or ESBies proposed by Brunnermeier, Langfield, Pagano,Reis, Van Nieuwerburgh and Vayanos (2017). The potential benefits of ESBies and other bond-backed securities hinge on the assertion that these products are really safe. In this paper we provide a comprehensive quantitative study of the risks associated with ESBies and related products, using an affine credit risk model with regime switching as vehicle for our analysis. We discuss a recent proposal of Standard and Poors for the rating of ESBies, we analyse the impact of model parameters and attachment points on the size and the volatility of the credit spread of ESBies and we consider several approaches to assess the market risk of ESBies. Moreover, we compare ESBies to synthetic securities created by pooling the senior tranche of national bonds as suggested by Leandro and Zettelmeyer(2019). The paper concludes with a brief discussion of the policy implications from our analysis.

Incentivizing Narrow-Spectrum Antibiotic Development with Refunding
Lucas Böttcher,Hans Gersbach
arXiv

The rapid rise of antibiotic resistance is a serious threat to global public health. Without further incentives, pharmaceutical companies have little interest in developing antibiotics, since the success probability is low and development costs are huge. The situation is exacerbated by the "antibiotics dilemma": Developing narrow-spectrum antibiotics against resistant bacteria is most beneficial for society, but least attractive for companies since their usage is more limited than for broad-spectrum drugs and thus sales are low. Starting from a general mathematical framework for the study of antibiotic-resistance dynamics with an arbitrary number of antibiotics, we identify efficient treatment protocols and introduce a market-based refunding scheme that incentivizes pharmaceutical companies to develop narrow-spectrum antibiotics: Successful companies can claim a refund from a newly established antibiotics fund that partially covers their development costs. The proposed refund involves a fixed and variable part. The latter (i) increases with the use of the new antibiotic for currently resistant strains in comparison with other newly developed antibiotics for this purpose---the resistance premium---and (ii) decreases with the use of this antibiotic for non-resistant bacteria. We outline how such a refunding scheme can solve the antibiotics dilemma and cope with various sources of uncertainty inherent in antibiotic R\&D. Finally, connecting our refunding approach to the recently established antimicrobial resistance (AMR) action fund, we discuss how the antibiotics fund can be financed.

Is Turkey Backsliding on Global Competitiveness and Democracy Amid Its EU Bid in Limbo?
SSRN
Turks have been around for thousands of years, who have established many states and empires in the â€œland of Turksâ€ referring to Anatolia (Asia Minor) and the Eastern Thrace. The life of Turks, previously in the Altai Mountains of western Mongolia, commenced in the interior of Asia Minor when Seljuqs defeated the Byzantines at Manzikert in 1071 (Malazgirt in Turkish), which also meant the start of Turkification of Asia Minor. After the six century long reign of the Ottoman Empire (1299-1922), Turks were introduced to democracy when Mustafa Kemal abolished the Ottoman Empire in November 1922 by overthrowing Sultan Mehmet VI Vahdettin and established Turkish Republic on October 29, 1923 (The Grand National Assembly elected Mustafa Kemal as President in 1923). After the death of Mustafa Kemal AtatÃ¼rk (November 10, 1938), Turkey has constantly faced instability-inflicting developments (i.e. coup d'Ã©tat, coup by memorandum, failed coup attempts, lack of fiscal and structural reforms, political turmoil, ineffective coalition governments, social unrest, chronic deficits, and repeated economic, financial, and currency crises. Turkeyâ€™s remarkable economic and democratic performance (6% YoY GDP growth between 2002 and 2007) was halted by endogenous (increasingly dictatorial/authoritarian rule, dysfunctional politics, negative developments in the rule of law, human rights, basic fundamentals, and the Judiciary/legal system) and exogenous factors (the 2008 global financial crisis originated in the U.S.; Cyprusâ€™ veto chapter 15 of Turkeyâ€™s EU accession negotiations; prosecution, conviction, and sentencing of the U.S. pastor Andrew Brunson of terrorism charges for taking part in the 2016 failed coup attempt; Turkeyâ€™s purchase of Russian S-400 defense system; Turkeyâ€™s removal from the F-35 program; the U.S. imposed sanctions/tariffs on steel imports from Turkey; repeated attacks on Turkish lira and the subsequent currency crisis).

Learning Agents in Black-Scholes Financial Markets: Consensus Dynamics and Volatility Smiles
Tushar Vaidya,Carlos Murguia,Georgios Piliouras
arXiv

Black-Scholes (BS) is the standard mathematical model for option pricing in financial markets. Option prices are calculated using an analytical formula whose main inputs are strike (at which price to exercise) and volatility. The BS framework assumes that volatility remains constant across all strikes, however, in practice it varies. How do traders come to learn these parameters? We introduce natural models of learning agents, in which they update their beliefs about the true implied volatility based on the opinions of other traders. We prove convergence of these opinion dynamics using techniques from control theory and leader-follower models, thus providing a resolution between theory and market practices. We allow for two different models, one with feedback and one with an unknown leader.

Mean-variance-utility portfolio selection with time and state dependent risk aversion
Ben-Zhang Yang,Xin-Jiang He,Song-Ping Zhu
arXiv

Under mean-variance-utility framework, we propose a new portfolio selection model, which allows wealth and time both have influences on risk aversion in the process of investment. We solved the model under a game theoretic framework and analytically derived the equilibrium investment (consumption) policy. The results conform with the facts that optimal investment strategy heavily depends on the investor's wealth and future income-consumption balance as well as the continuous optimally consumption process is highly dependent on the consumption preference of the investor.

Nice guys don't always finish last: succeeding in hierarchical organizations
Doron Klunover
arXiv

What are the chances of an ethical individual rising through the ranks of a political party or a corporation in the presence of unethical peers? To answer this question, I consider a four-player two-stage elimination tournament, in which players are partitioned into those willing to be involved in sabotage behavior and those who are not. I show that, under certain conditions, the latter are more likely to win the tournament.

Optimal Characteristic Portfolios
McGee, Richard,Olmo, Jose
SSRN
Characteristic-sorted portfolios are the workhorses of modern empirical finance, deployed widely to evaluate anomalies and construct asset pricing models. We propose a new method for their estimation that is simple to compute; makes no ex-ante assumption on the nature of the relationship between the characteristic and returns; and does not require ad hoc selections of percentile breakpoints or portfolio weighting schemes. Characteristic portfolio weights are implied directly from data, through maximizing the expected value of a mean-variance utility function estimated non-parametrically over the cross section of the assets. To illustrate the method we use it to evaluate the size, value and momentum anomalies.

Optimal allocation using the Sortino ratio
Tarek Nassar,Sandro Ephrem
arXiv

In this paper we present an asset allocation strategy based on the maximization of the Sortino ratio. Unlike the Sharpe ratio, the Sortino ratio penalizes negative return variances only. The resulting allocation is valid for any time horizon unlike. The returns of a strategy based on such an allocation are empirically illustrated using historical Dow Jones data and display a significant upgrade on more traditional allocation strategies such as the Kelly criterion.

Parametric Insurance and Technology Adoption in Developing Countries
Biffis, Enrico,Chavez, Erik,Louaas, Alexis,Picard, Pierre
SSRN
Technology adoption is crucial for the development of low income countries. This paper investigates how parametric insurance can contribute to improving access to finance, and hence to technology, for smallholder farmers. In a model with moral hazard, we show that bundling parametric insurance with loans may lower collateral requirements, thus promoting the financial inclusion of poor households. The case of agricultural input loans and weather-index insurance is studied in detail and related to bundled finance solutions recently piloted among smallholder farmers in Tanzania.

Portfolio optimization with two coherent risk measures
Tahsin Deniz Aktürk,Çağın Ararat
arXiv

We provide analytical results for a static portfolio optimization problem with two coherent risk measures. The use of two risk measures is motivated by joint decision-making for portfolio selection where the risk perception of the portfolio manager is of primary concern, hence, it appears in the objective function, and the risk perception of an external authority needs to be taken into account as well, which appears in the form of a risk constraint. The problem covers the risk minimization problem with an expected return constraint and the expected return maximization problem with a risk constraint, as special cases. For the general case of an arbitrary joint distribution for the asset returns, under certain conditions, we characterize the optimal portfolio as the optimal Lagrange multiplier associated to an equality-constrained dual problem. Then, we consider the special case of Gaussian returns for which it is possible to identify all cases where an optimal solution exists and to give an explicit formula for the optimal portfolio whenever it exists.

Price Discovery in Two-Tier Markets
Bjonnes, Geir Hoidal,Osler, Carol L.,Rime, Dagfinn
SSRN
This paper examines the price discovery process in a two-tier market, specifically the foreign exchange market. The goal is to identify the sources of private information and to gain insights into the process through which that information influences the market price. Using a transactions database that includes trading-party identities, we show that sustained post-trade returns rise with bank size, implying that larger banks have an information advantage. The larger banks exploit this information advantage in placing limit orders as well as market orders. We also show that the bankâ€™s private information does not come from their corporate or government customers or from some asset managers. Instead, the bankâ€™s private information appears to come from other asset managers, including hedge funds, and from the bankâ€™s own analysis.

Quantification of Risk in Classical Models of Finance
Alois Pichler,Ruben Schlotter
arXiv

This paper enhances the pricing of derivatives as well as optimal control problems to a level comprising risk. We employ nested risk measures to quantify risk, investigate the limiting behavior of nested risk measures within the classical models in finance and characterize existence of the risk-averse limit. As a result we demonstrate that the nested limit is unique, irrespective of the initially chosen risk measure. Within the classical models risk aversion gives rise to a stream of risk premiums, comparable to dividend payments. In this context we connect coherent risk measures with the Sharpe ratio from modern portfolio theory and extract the Z-spread -- a widely accepted quantity in economics to hedge risk. The results for European option pricing are then extended to risk-averse American options, where we study the impact of risk on the price as well as the optimal time to exercise the option. We also extend Merton's optimal consumption problem to the risk-averse setting.

Race and gender income inequality in the USA: black women vs. white men
Ivan Kitov
arXiv

Income inequality between different races in the U.S. is especially large. This difference is even larger when gender is involved. In a complementary study, we have developed a dynamic microeconomic model accurately describing the evolution of male and female incomes since 1930. Here, we extend our analysis and model the disparity between black and white population in the U.S., separately for males and females. Unfortunately, income microdata provided by the U.S. Census Bureau for other races and ethnic groups are not time compatible or too short for modelling purposes. We are forced to constrain our analysis to black and white population, but all principal results can be extrapolated to other races and ethnicities. Our analysis shows that black females and white males are two poles of the overall income inequality. The prediction of income distribution for two extreme cases with one model is the main challenge of this study.

Recombining tree approximations for Game Options in Local Volatility models
Benjamin Gottesman Berdah
arXiv

In this paper we introduce a numerical method for optimal stopping in the framework of one dimensional diffusion. We use the Skorokhod embedding in order to construct recombining tree approximations for diffusions with general coefficients. This technique allows us to determine convergence rates and construct nearly optimal stopping times which are optimal at the same rate. Finally, we demonstrate the efficiency of our scheme with several examples of game options.

Reinsurance Demand and Liquidity Creation: A Search for Bi-Causality
SSRN
We analyze the relationship between insurersâ€™ liquidity creation and reinsurance demand. Early theoretical contributions on liquidity creation propose that financial institutions enhance economic growth by creating liquidity in the economy. Liquidity creation means financing relatively illiquid assets with relatively liquid liabilities. However, liquidity creation exposes insurers to financial risks. There is a trade-off between getting higher returns on risky investments and being able to compensate clients at a low cost when unexpected claims happen. Unexpected claims can be protected by reinsurance, which introduces a second trade-off between reinsurance demand and liquidity creation. This trade-off can be more important for insurers that have fewer diversification opportunities. Our main empirical results, from regularized GMM and ML-SME methods of estimation, show similar positive bi-causal effects between liquidity creation and reinsurance demand for small insurers (22% of insurance activity). The link between the two activities is not significant for large insurers (60% of insurance activity). We obtain mixed results for medium insurers. In all estimations, the standard GMM model is rejected.

Retaining Worried Depositors: Evidence from Multi-Brand Banks
Chavaz, Matthieu,Slutzky, Pablo
SSRN
We develop a novel approach to study how banks respond to fluctuations in the risk of panic-driven retail deposit withdrawals. To proxy for changes in withdrawal risk, we track online information acquisition about different brands of UK banks. We find that banks facing surges in information acquisition during the global financial crisis increase interest rates on instant-access deposits. Exploiting variation in information acquisition for different brands of the same bank, we show that part of this response cannot be explained by fundamentals. Comparing similar onshore and offshore deposits offered by the same brand, we show that the effect is stronger when the absence of deposit insurance increases the potential for strategic complementarities. Our results point to a previously undocumented source of self-fulfilling bank fragility.

Risks and Risk Premia in the US Treasury Market
Li, Junye,Sarno, Lucio,Zinna, Gabriele
SSRN
We analyze the risk-return trade-off in the US Treasury market using a term-structure model that features volatility-in-mean effects of multiple sources, and yet preserves tractable bond prices. We find a strong positive relation between risks and risk premia over the 1966-2018 period. While interest-rate risk is the main driver of such positive relation, macro risk plays a non-trivial role, and its omission leads to unstable estimates of the trade-off. Notably, macro risk contributes to the surge and consequent fall of risk premia around the 1980s, whereas it moves inversely with risk premia during the recent `low yield' period.

Securitization, Monetary Policy and Bank Stability
Bakoush, Mohamed,Mishra, Tapas,Wolfe, Simon
SSRN
We provide new evidence about the effect of securitization on bank stability and systemic risk in the run-up to and following the global financial crisis by considering the role of the bank lending channel of monetary policy. In so doing, we use a structural model of bank stability to construct a new measure of the net effect of securitization on bank stability. Analyzing the dynamics of this measure at the individual bank and the banking system levels shows that securitization activities have a destabilizing effect on banks, although this effect decreases after the crisis. To explain this change, we then use the bank lending channel as the main link between securitization and monetary policy. We find that low monetary policy interest rates in the aftermath of the global financial crisis have mitigated the destabilizing effect of securitization on banks.

Systemic Risk Channels of Asset Managers: Evidence from Hedge Funds and Mutual Funds
Greppmair, Stefan
SSRN
Using a sample of hedge funds and mutual funds, I examine two channels through which asset managers can contribute to systemic risk: the service channel when funds act as liquidity suppliers and the asset liquidation channel when funds act as liquidity demanders. Consistent with the latter channel being more important, I find that contributions to systemic risk increase significantly when hedge funds demand liquidity. Conversely, no such effect exists for mutual funds. A decomposition of systemic risk reveals that the higher level of systemic risk for liquidity-demanding hedge funds can be explained by a higher degree of interconnectedness. Providing further evidence for the asset liquidation channel, I document that systemic risk is considerably larger when hedge funds demand liquidity in times of low funding liquidity and during stock market boom and bust phases.

The Effect of Shadow Banking on the Bank Lending Channel of Monetary Policy
Zink, David
SSRN
I present cross-sectional evidence that shadow banks have weakened the credit channel of monetary policy. Using data from the Home Mortgage Disclosure Act (HMDA) from 2000 through 2016, I show that shadow banks increase (decrease) mortgage lending relative to traditional banks in response to an increase (decrease) in the Federal Funds rate. I control for confounding demand side factors by including a full set of census-tract by time fixed effects, thereby comparing the lending response to monetary policy of banks and shadow-banks located in the same census-tract. This result is economically significant: shadow banks reduce lending by two percentage points less than traditional banks for every one percentage point increase in the Federal Funds rate. Second stage results consider the implications of shadow banking on the downstream effects of monetary policy on home prices and employment. Results indicate that in response to an increase in the Federal Funds rate, counties with more exposure to shadow banking experience a smaller reduction in home prices and unemployment.

The Impact of Cryptocurrency Regulation on Trading Markets
Feinstein, Brian D.,Werbach, Kevin
SSRN
Some policymakers and scholars view cryptocurrencies as conduits of illegality and fraud, which therefore should be tightly regulated. Others warn that regulation could simply cause trading activity to cross borders into less-regulated jurisdictionsâ€"or even smother a promising new financial asset class. To assess these claims, we assemble original data on cryptocurrency regulations worldwide and use them to empirically examine global movement in trading activity following key regulatory announcements. A wide variety of models yields almost entirely null results. These findings call into question the notion that capital flight should be a first-order concern when designing a regulatory regime for cryptocurrencies.

The International Legal (Dis)order: Deleterious Effects of â€˜Us and Themâ€™ Politics, Zero-Sum Games, and Flagrancy of Power at Global Scale
SSRN
This article posits the international legal order has fundamentally broken down. A range of government, private, and academic sources depict a world where corporate power is ascendant, individual human rights are stagnant and under threat by both private and public institutions, and governments are disinterested in transparently and thoroughly performing their treaty obligations. Central to the systemic breakdown assertion is the interdependency of what may appear as discrete or independent areas of law â€" private and public, domestic and international, human rights, environmental â€" and sectors of scalable local, national, regional, and global economies. Idiosyncratic state conduct and uneven compliance with fundamentals of international law support the theme. Numerous examples from dozens of countries, and the United States in particular, illustrate a pluralistic status quo where wealthy and powerful actors disregard rule of law, instead relying on corrupt practices and antiquated rules of force. Recommendations call for paradigm shift and revised approach to contemporary issues at law.

The New Digital Platforms: Merger Control in Pakistan
arXiv

The Pakistan competition policy, as in many other countries, was originally designed to regulate business conduct in traditional markets and for tangible goods and services. However, the development and proliferation of the internet has led to the emergence of digital companies which have disrupted many sectors of the economy. These platforms provide digital infrastructure for a range of services including search engines, marketplaces, and social networking sites. The digital economy poses a myriad of challenges for competition authorities worldwide, especially with regard to digital mergers and acquisitions (M&As). While some jurisdictions such as the European Union and the United States have taken significant strides in regulating technological M&As, there is an increasing need for developing countries such as Pakistan to rethink their competition policy tools. This paper investigates whether merger reviews in the Pakistan digital market are informed by the same explanatory variables as in the traditional market, by performing an empirical comparative analysis of the Competition Commission of Pakistan's (CCP's) M&A decisions between 2014 and 2019. The findings indicate the CCP applies the same decision factors in reviewing both traditional and digital M&As. As such, this paper establishes a basis for igniting the policy and economic debate of regulating the digital platform industry in Pakistan.

The Value of Economic Growth in a Democracy
Mittal, Amit,Garg, Ajay Kumar
SSRN
The recent longstanding Global Crisis which seems to have no end has created a divisive debate on the utility of Academic research and in particular on the business of studying Economics and proffering solutions for alleviating world problems. The study , kickstarts an exercise in Critical thinking to analyse some known facets of the study of Democracy and align with conceptions of Economic growth and review in the current literature whether academic research has indeed attempted to and found the right questions and if we are near a solution for the real world with its political, economic and geographical constraints. This is a foundation study to enable other researchers to form more relevant and current analyses with a foundation in economic literature.

Time-inhomogeneous Gaussian stochastic volatility models: Large deviations and super roughness
Archil Gulisashvili
arXiv

We introduce time-inhomogeneous stochastic volatility models, in which the volatility is described by a nonnegative function of a Volterra type continuous Gaussian process that may have very rough sample paths. The main results obtained in the paper are sample path and small-noise large deviation principles for the log-price process in a time-inhomogeneous super rough Gaussian model under very mild restrictions. We use these results to study the asymptotic behavior of binary barrier options, exit time probability functions, and call options.

Zero Black-Derman-Toy interest rate model
Grzegorz Krzyżanowski,Ernesto Mordecki,Andrés Sosa
arXiv

We propose a modification of the classical Black-Derman-Toy (BDT) interest rate tree model, which includes the possibility of a jump with small probability at each step to a practically zero interest rate. The corresponding BDT algorithms are consequently modified to calibrate the tree containing the zero interest rate scenarios. This modification is motivated by the recent 2008-2009 crisis in the United States and it quantifies the risk of a future crises in bond prices and derivatives. The proposed model is useful to price derivatives. This exercise also provides a tool to calibrate the probability of this event. A comparison of option prices and implied volatilities on US Treasury bonds computed with both the proposed and the classical tree model is provided, in six different scenarios along the different periods comprising the years 2002-2017.