# Research articles for the 2019-09-16

A New Form of Banking -- Concept and Mathematical Model of Venture Banking
Brian P Hanley
arXiv

This model contains concept, equations, and graphical results for venture banking. A system of 27 equations describes the behavior of the venture-bank and underwriter system allowing phase-space type graphs that show where profits and losses occur. These results confirm and expand those obtained from the original spreadsheet based model. An example investment in a castle at a loss is provided to clarify concept. This model requires that all investments are in enterprises that create new utility value. The assessed utility value created is the new money out of which the venture bank and underwriter are paid. The model presented chooses parameters that ensure that the venture-bank experiences losses before the underwriter does. Parameters are: DIN Premium, 0.05; Clawback lien fraction, 0.77; Clawback bonds and equity futures discount, 1.5 x (USA 12 month LIBOR); Range of clawback bonds sold, 0 to 100%; Range of equity futures sold 0 to 70%.

A Top-Down Approach for the Multiple Exercises and Valuation of Employee Stock Options
Tim Leung,Yang Zhou
arXiv

We propose a new framework to value employee stock options (ESOs) that captures multiple exercises of different quantities over time. We also model the ESO holder's job termination risk and incorporate its impact on the payoffs of both vested and unvested ESOs. Numerical methods based on Fourier transform and finite differences are developed and implemented to solve the associated systems of PDEs. In addition, we introduce a new valuation method based on maturity randomization that yields analytic formulae for vested and unvested ESO costs. We examine the cost impact of job termination risk, exercise intensity, and various contractual features.

Additive normal tempered stable processes for equity derivatives and power law scaling
Michele Azzone,Roberto Baviera
arXiv

We introduce a simple model for equity index derivatives. The model generalizes well known L\evy Normal Tempered Stable processes (e.g. NIG and VG) with time dependent parameters. It accurately fits Equity index implied volatility surfaces in the whole time range of quoted instruments, including small time horizon (few days) and long time horizon options (years). We prove that the model is an Additive process that is constructed using an Additive subordinator. This allows us to use classical L\evy-type pricing techniques. We discuss the calibration issues in detail and we show that, in terms of mean squared error, calibration is on average two orders of magnitude better than both L\evy processes and Self-similar alternatives. We show that even if the model loses the classical stationarity property of L\evy processes, it presents interesting scaling properties for the calibrated parameters.

An SFP--FCC Method for Pricing and Hedging Early-exercise Options under L\'evy Processes
Tat Lung,Chan
arXiv

This paper extends the Singular Fourier--Pad\'e (SFP) method proposed by Chan (2018) to pricing/hedging early-exercise options--Bermudan, American and discrete-monitored barrier options--under a L\'evy process. The current SFP method is incorporated with the Filon--Clenshaw--Curtis (FCC) rules invented by Dom\'inguez et al. (2011), and we call the new method SFP--FCC. The main purpose of using the SFP--FCC method is to require a small number of terms to yield fast error convergence and to formulate option pricing and option Greek curves rather than individual prices/Greek values. We also numerically show that the SFP--FCC method can retain a global spectral convergence rate in option pricing and hedging when the risk-free probability density function is piecewise smooth. Moreover, the computational complexity of the method is $\mathcal{O}((L-1)(N+1)(\tilde{N} \log \tilde{N}) )$ with $N$ a (small) number of complex Fourier series terms, $\tilde{N}$ a number of Chebyshev series terms and $L$, the number of early-exercise/monitoring dates. Finally, we show that our method is more favourable than existing techniques in numerical experiments.

An adverse selection approach to power pricing
Clémence Alasseur,Ivar Ekeland,Romuald Elie,Nicolás Hernández Santibáñez,Dylan Possamaï
arXiv

We study the optimal design of electricity contracts among a population of consumers with different needs. This question is tackled within the framework of Principal-Agent problems in presence of adverse selection. The particular features of electricity induce an unusual structure on the production cost, with no decreasing return to scale. We are nevertheless able to provide an explicit solution for the problem at hand. The optimal contracts are either linear or polynomial with respect to the consumption. Whenever the outside options offered by competitors are not uniform among the different type of consumers, we exhibit situations where the electricity provider should contract with consumers with either low or high appetite for electricity.

Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes
Eoghan O'Neill,Melvyn Weeks
arXiv

We examine the household-specific effects of the introduction of Time-of-Use (TOU) electricity pricing schemes. Using a causal forest (Athey and Imbens, 2016; Wager and Athey, 2018; Athey et al., 2019), we consider the association between past consumption and survey variables, and the effect of TOU pricing on household electricity demand. We describe the heterogeneity in household variables across quartiles of estimated demand response and utilise variable importance measures.

Household-specific estimates produced by a causal forest exhibit reasonable associations with covariates. For example, households that are younger, more educated, and that consume more electricity, are predicted to respond more to a new pricing scheme. In addition, variable importance measures suggest that some aspects of past consumption information may be more useful than survey information in producing these estimates.

Centrality-oriented Causality -- A Study of EU Agricultural Subsidies and Digital Developement in Poland
Kosiorowski Daniel,Jerzy P. Rydlewski
arXiv

Results of a convincing causal statistical inference related to socio-economic phenomena are treated as especially desired background for conducting various socio-economic programs or government interventions. Unfortunately, quite often real socio-economic issues do not fulfill restrictive assumptions of procedures of causal analysis proposed in the literature. This paper indicates certain empirical challenges and conceptual opportunities related to applications of procedures of data depth concept into a process of causal inference as to socio-economic phenomena. We show, how to apply a statistical functional depths in order to indicate factual and counterfactual distributions commonly used within procedures of causal inference. Thus a modification of Rubin causality concept is proposed, i.e., a centrality-oriented causality concept. The presented framework is especially useful in a context of conducting causal inference basing on official statistics, i.e., basing on already existing databases. Methodological considerations related to extremal depth, modified band depth, Fraiman-Muniz depth, and multivariate Wilcoxon sum rank statistic are illustrated by means of example related to a study of an impact of EU direct agricultural subsidies on a digital development in Poland in a period of 2012-2019.

Comparing the forecasting of cryptocurrencies by Bayesian time-varying volatility models
Rick Bohte,Luca Rossini
arXiv

This paper studies the forecasting ability of cryptocurrency time series. This study is about the four most capitalized cryptocurrencies: Bitcoin, Ethereum, Litecoin and Ripple. Different Bayesian models are compared, including models with constant and time-varying volatility, such as stochastic volatility and GARCH. Moreover, some crypto-predictors are included in the analysis, such as S\&P 500 and Nikkei 225. In this paper the results show that stochastic volatility is significantly outperforming the benchmark of VAR in both point and density forecasting. Using a different type of distribution, for the errors of the stochastic volatility the student-t distribution came out to be outperforming the standard normal approach.

Continuity of Utility Maximization under Weak Convergence
Erhan Bayraktar,Yan Dolinsky,Jia Guo
arXiv

In this paper we find tight sufficient conditions for the continuity of the value of the utility maximization problem from terminal wealth with respect to the convergence in distribution of the underlying processes. We also establish a weak convergence result for the terminal wealths of the optimal portfolios. Finally, we apply our results to the computation of the minimal expected shortfall (shortfall risk) in the Heston model by building an appropriate lattice approximation.

Credit Risk in Commercial Real Estate Bank Loans: The Role of Idiosyncratic Versus Macro-Economic Factors
Mokas, Dimitris,Nijskens, Rob
SSRN
The commercial real estate market is pro-cyclical. This feature, together with the relative size of the industry and the large capital inflows, has made this sector relevant for financial stability. Using a novel loan level data set covering the commercial real estate portfolios of Dutch banks we aim to uncover potential drivers of distress in commercial real estate loans. Furthermore, we estimate the relative importance of idiosyncratic and systematic factors and emphasize the importance of bank behavior for distinguishing between good and bad credit growth. We find that loans originated near the peak of the cycle are riskier, confirming the pro-cyclical nature of the market. As opposed to loans originated during busts, the risk of boom loans does not decrease when economic conditions improve. Idiosyncratic factors correlated with higher credit risk are loan-to-value ratios and interest rates, especially when coupled with variable rate contracts. Moreover, we find that collateral type plays a role, as loans for non-residential (office, retail, industrial) real estate with higher vacancy rates are riskier. These results have implications for both macroprudential and microprudential supervision, as they demonstrate the pro-cyclicality of the market and show that indicators like loan-to-value, interest rate structure and vacancy rates must be monitored more carefully in boom times.

Deep Learning Classifier with Piecewise Linear Activation Function: An Empirical Evaluation with Intraday Financial Data
Banerjee, Soham,Mukherjee, Diganta
SSRN
Price movement predictions of financial instruments using traditional time series models with a predefined mathematical structure is common. But it restricts their ability to learn latent patterns in the data. In recent times Artificial Neural Networks (ANN) have been able to learn complex hidden patterns from financial data-sets using a highly non-linear architecture. However, most of the experiments with Neural Networks require lot of time for searching a suitable network and subsequently training them. We developed a deep Multi Layer Perceptron (MLP) classifier with a zero centered Piecewise Linear Unit (PLU) activation that yielded better classification performance according to our accuracy metric and also exhibited consistently smaller training time compared to similar MLP network with Leaky ReLU and Tanh activation function. We illustrate with a large high frequency data-set on selected bank shares from the Indian stock market. We also discuss the theoretical properties and advantages of our proposal.

DeepTriangle: A Deep Learning Approach to Loss Reserving
Kevin Kuo
arXiv

We propose a novel approach for loss reserving based on deep neural networks. The approach allows for joint modeling of paid losses and claims outstanding, and incorporation of heterogeneous inputs. We validate the models on loss reserving data across lines of business, and show that they improve on the predictive accuracy of existing stochastic methods. The models require minimal feature engineering and expert input, and can be automated to produce forecasts more frequently than manual workflows.

Dissecting Market Expectations in the Cross-Section of Book-to-Market Ratios
de Oliveira Souza, Thiago
SSRN
I find no evidence that partial least squares based on disaggregated book-to-market ratios - originally applied to market return forecasting and delivering persistently positive out-of-sample predictive R2 - delivers a similar model of market premiums. The method's previous performance has two main drivers: (i) The sample period and (ii) using market returns as forecasting targets. Other drivers are (iii) the use of book-to-market ratios of the particular portfolios double-sorted by size and book-to-market as regressors (iv) divided by their standard deviations. I argue that these results do not necessarily invalidate the method, but they seem to contradict its theoretical framework.

Diversification and Efficiency in the Indonesian Banking Industry
, Fredio O. Tarore,Prasetyo, Muhammad Budi
SSRN
The global financial crisis in 2008 caused banks to look for business models that can increase efficiency levels. Several previous studies of developed markets suggest that diversification has a positive effect on efficiency. This study aims to analyze the effect of diversification on Indonesian banking efficiency as one of the emerging markets. We used stochastic frontier analysis (SFA) to measure efficiency; the results showed that the majority of Indonesian banks operate at relatively low efficiency. Using the panel data, this study found the same result; diversification can improve Indonesian bank efficiency. Diversification can optimize the output without additional input costs that cause an increase in Indonesian bank efficiency. Other factors such as the level of bank capital also have an impact on increased efficiency. In addition, the influence of bank size and the global financial crisis is not statistically significant.

Do Stock Options Always Align Manager and Shareholdersâ€™ Interests? An Alternative Perspective
Danielson, Morris G.,Press, Eric
SSRN
Shareholders want managers to invest in all positive net present value (NPV) projects, and to avoid those with negative NPV. Using a simple model of firm value, we explain why stock op-tionsâ€"when issued by firms with high price-to-book value ratiosâ€"do not always provide the incentive for managers to pursue these value-maximizing policies. This is noteworthy because option usage in the late 1990s was concentrated in the sort of firmâ€"those with high P/B rati-osâ€"in which they can be least effective. Our model gives students the opportunity to integrate and apply concepts from stock valuation and capital budgeting, and to think critically about the relative merits of stock options and restricted stock as forms of incentive compensation.

Effective Bank Corporate Governance: Observations From the Market Crash and Recommendations for Policy
SSRN
This paper considers the extent to which inadequate corporate governance was a contributory factor to the financial market crash. It examines the experience of selected failed banks, with emphasis on the corporate governance structure in place at each firm, and the background and expertise of the Board and Directors, and draws conclusions for future policy. We find that the nature and composition of Boards was not robust enough to provide independent direction. Their membership possessed insufficient expertise, and was not geared towards a long-term view of the bankâ€™s development. Consequently many banks were drawn into a bull market spiral. The form of management direction contributed to this. Based on our conclusions we recommend that a number of bank governance measures be implemented, if necessary for imposition by regulatory fiat. These measures relate to the composition, structure and expertise of board members and non-executive directors.

EvaSylv: A user-friendly software to evaluate forestry scenarii including natural risk
Patrice Loisel,Guillerme Duvillié,Denis Barbeau,Brigitte Charnomordic
arXiv

Forest management relies on the evaluation of silviculture practices. The increase in natural risk due to climate change makes it necessary to consider evaluation criteria that take natural risk into account. Risk integration in existing software requires advanced programming skills.We propose a user-friendly software to simulate even-aged and monospecific forest at the stand level, in order to evaluate and optimize forest management. The software gives the possibility to run management scenarii with or without considering the impact of natural risk. The control variables are the dates and rates of thinning and the cutting age.The risk model is based on a Poisson processus. The Faustmann approach, including tree damage risk, is used to evaluate future benefits, economic or ecosystem services. It relies on the calculation of expected values, for which a dedicated mathematical development has been done. The optimized criteria used to evaluate the various scenarii are the Faustmann value and the Averaged yield value.We illustrate the approach and the software on two case studies: economic optimization of a beech stand and carbon sequestration optimization of a pine stand.Software interface makes it easy for users to write their own (growth-tree damage-economic) models without advanced programming skills. The possibility to run management scenarii with/without considering the impact of natural risk may contribute improving silviculture guidelines and adapting them to climate change. We propose future lines of research and improvement.

Financial Reporting Quality and Sustainability Information Disclosure in Brazil
Salvador de Souza, JoÃ£o AntÃ´nio,Flach, Leonardo,Borba, Jose Alonso,Broietti, Broietti
SSRN
Currently, businesses face an information disclosure approach involving the triple bottom line (social, environmental, and financial). This paper aims to investigate the relationship between corporate social responsibility (CSR) information and financial reporting quality (FRQ). We argue that CSR companies behave differently in preparing financial accounting reports. Recent literature supports this theme, providing two distinct hypotheses: transparent financial reporting and retreatment. We used a sample of 1,181 companies from the years 2012 to 2016 to identify if socially responsible companies have better quality financial accounting information. In contrast to the hypotheses raised, we didn't find a relationship between the CSR disclosures and the FRQ proxies. This suggests that sustainable companies do not explain lower or higher levels of earnings management. Our findings remain unchanged when we replace results management through discretionary accruals for manipulations of operating activities. Estimates with comparable samples also didnâ€™t change the interpretations of the results.

Financial Stability Assessment for EU Candidate Countries and Potential Candidates
Comunale, Mariarosaria,Geis, AndrÃ©,Gkrintzalis, Ioannis,Moder, Isabella,Polgar, Eva Katalin,Savelin, Li
SSRN
This paper reviews and assesses financial stability challenges in countries preparing for EU membership, i.e. Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, Serbia and Turkey. The paper mainly focuses on the period since 2016 (unless the analysis requires a longer time span) and on the banking sectors that dominate financial systems in this group of countries. For the Western Balkans, the paper analyses recent trends in financial intermediation, as well as the two main challenges that have been identified in the past. Asset quality continues to improve, but the share of non-performing loans is still high in some countries, while regulatory, legal and tax impediments are still to be resolved in most cases. High unofficial euroisation is a source of indirect credit risk for countries with their own national legal tender, which calls for continued efforts to promote the use of domestic currencies in the financial system. At the same time, banking systems seem less prone to financial stress from maturity mismatches than certain EU peers. These risks are met with a solid shock-absorbing capacity in the Western Balkans, as exemplified by robust capital and liquidity buffers. Turkey experienced a period of heightened financial stress during 2018 and, while its banking system appears to have sufficient buffers to absorb shocks overall, significant forex borrowing of corporates and high rollover needs of banks in foreign exchange on the wholesale market constitute considerable financial stability risks.

Fixed Investment in Russia in 2018
SSRN
Macroeconomic situation in 2017â€"2018 was marked by the outstripping growth rates of fixed investments relative to GDP performance and final consumption of households. In 2018, amid fixed investments increase by 4.3 percent, GDP growth constituted 2.3 percent relative to the corresponding period of the previous year. However, despite the upward trend of fixed investments seen in 2017â€"2018, the economy has retained the impact from the acute investment crisis of 2014â€"2016. Vis-a-vis pre-crisis 2012 fixed investments registered in 2018 came to merely 97.3 percent and the construction work volume to 95.7 percent.

Fundamental Characteristics of Russiaâ€™s Equity Market in 2018
Abramov, Alexander E.,Chernova, Maria
SSRN
In 2018, the Russian stock market held up its reputation as one of the most volatile markets in the world. In 2018, Russian companiesâ€™ stocks turned out to be instruments with highest returns, outperforming 36 worldâ€™s largest stock exchange markets, in contrast to 2017, when Russian stocks were at the bottom of the list of stocks with lowest returns. In 2018, the MOEX Russia Index (formerly the MICEX Index) picked up 12.3 percent, whereas the RTS Index lost 7.4 percent. In 2018, the MOEX Russia Index found itself in a small group of stock indices of Brazil, India and Argentina that managed to stay within a range of positive returns (see Fig. 1). While being composed of the same companies, the two of Russiaâ€™s indices differ in that the dollar-denominated RTS Index offers bigger returns than the ruble-denominated MOEX Russia Index. Therefore, when the Russian ruble depreciates the ruble-denominated returns on investment in the stocks composing the MOEX Russia Index are higher than the dollar-denominated returns on the RTS Index portfolio.

Generalized Duality for Model-Free Superhedging given Marginals
Arash Fahim,Yu-Jui Huang,Saeed Khalili
arXiv

In a discrete-time financial market, a generalized duality is established for model-free superhedging, given marginal distributions of the underlying asset. Contrary to prior studies, we do not require contingent claims to be upper semicontinuous, allowing for upper semi-analytic ones. The generalized duality stipulates an extended version of risk-neutral pricing. To compute the model-free superhedging price, one needs to find the supremum of expected values of a contingent claim, evaluated not directly under martingale (risk-neutral) measures, but along sequences of measures that converge, in an appropriate sense, to martingale ones. To derive the main result, we first establish a portfolio-constrained duality for upper semi-analytic contingent claims, relying on Choquet's capacitability theorem. As we gradually fade out the portfolio constraint, the generalized duality emerges through delicate probabilistic estimations.

How to 'Fix' the Venture Capital Model? Regulation versus Disruption
Fenwick, Mark,Vermeulen, Erik P. M.
SSRN
There is something special about venture capital. And this â€œspecial somethingâ€ goes beyond the large financial returns that can come from investing in successful start-ups. At its core, venture capital is about identifying the life-changing innovations of tomorrow and then facilitating the development and deployment of those innovations today. As such, venture capital is in the business of changing the world. This is not to downplay the central role of entrepreneur-founders in developing the underlying technologies, creating and scaling a business, and improving peopleâ€™s lives, but rather to acknowledge the central role of venture capital in this process. Stories of successful start-ups in a U.S. context â€" think Amazon, Facebook or Google â€" all contain one recurring feature: the crucial support of one or more venture capitalists.However, doubts relating to the venture capital model have been emanating from all corners of the start-up ecosystem for over a decade, raising concern that the whole model is broken. The answer is simple: the venture capital industry should also adapt to new circumstances and a rapidly changing (digital) environment.

Identifying the Discount Factor in Dynamic Discrete Choice Models
Jaap H. Abbring,Øystein Daljord
arXiv

Empirical research often cites observed choice responses to variation that shifts expected discounted future utilities, but not current utilities, as an intuitive source of information on time preferences. We study the identification of dynamic discrete choice models under such economically motivated exclusion restrictions on primitive utilities. We show that each exclusion restriction leads to an easily interpretable moment condition with the discount factor as the only unknown parameter. The identified set of discount factors that solves this condition is finite, but not necessarily a singleton. Consequently, in contrast to common intuition, an exclusion restriction does not in general give point identification. Finally, we show that exclusion restrictions have nontrivial empirical content: The implied moment conditions impose restrictions on choices that are absent from the unconstrained model.

Information, Market Power and Price Volatility
Bergemann, Dirk,Heumann, Tibor,Morris, Stephen
SSRN
We consider demand function competition with a ï¬nite number of agents and private information. We show that any degree of market power can arise in the unique equilibrium under an information structure that is arbitrarily close to complete information. In particular, regardless of the number of agents and the correlation of payoï¬€ shocks, market power may be arbitrarily close to zero (so we obtain the competitive outcome) or arbitrarily large (so there is no trade in equilibrium). By contrast, price volatility is always less than the variance of the aggregate shock across all information structures.

Informational Benefits of Managerial Myopia
Li, Cheng
SSRN
We show that managerial myopia has an informational benefit that has been overlooked in the prior research. A moderately myopic manager incentivizes the advocate of a risky project to produce full information about the project, leading to fully informed decision making and highest firm value.

Lead-lag Relationships in Foreign Exchange Markets
arXiv

Lead-lag relationships among assets represent a useful tool for analyzing high frequency financial data. However, research on these relationships predominantly focuses on correlation analyses for the dynamics of stock prices, spots and futures on market indexes, whereas foreign exchange data have been less explored. To provide a valuable insight on the nature of the lead-lag relationships in foreign exchange markets here we perform a detailed study for the one-minute log returns on exchange rates through three different approaches: i) lagged correlations, ii) lagged partial correlations and iii) Granger causality. In all studies, we find that even though for most pairs of exchange rates lagged effects are absent, there are many pairs which pass statistical significance tests. Out of the statistically significant relationships, we construct directed networks and investigate the influence of individual exchange rates through the PageRank algorithm. The algorithm, in general, ranks stock market indexes quoted in their respective currencies, as most influential. In contrast to the claims of the efficient market hypothesis, these findings suggest that all market information does not spread instantaneously.

MayorÃ­as econÃ³micas y regulaciÃ³n financiera: una mirada desde la teorÃ­a de planes (Economic Majorities and Financial Regulation: A Planning Theory Approach)
Camacho, Jose Miguel
SSRN

Measuring Changes in Liquidity Using the Bid-Offer Price Proxy: Determinants of Liquidity in the United Kingdom Gilt Market
SSRN
Financial market liquidity is an important yardstick of value for investors and central monetary authorities. Secondary market liquidity itself cannot be observed directly and is instead measured using a number of different proxies. The most common proxy is the asset bid-off price spread. In this study we conduct time series analysis of the bid-offer spread in order to ascertain if the level of liquidity in a specified market has improved over a period of time. The market we select is the United Kingdom government bond market or gilt market. During the 1990s the UK monetary authorities introduced a number of structural reforms in the gilt market, designed to improve secondary market liquidity. We measure the success of the reforms by attempting to determine if liquidity levels improved in the post-reform period, via the examination of the bid-offer spread. We examine the determinants of this proxy measure, and estimate which of the explanatory variables carries the greatest weight in influencing liquidity levels. We conclude that a number of the independent variables that we examined, including bond issue size and maturity, are found to be significant determinants of liquidity. We conclude further that similar structural reforms should be considered by other central monetary authorities wishing to improve bond market liquidity levels, and that the determinant factors we cite should be reviewed during periods of market correction, when liquidity levels decrease.

Modern Perspectives on Reinforcement Learning in Finance
Kolm, Petter N.,Ritter, Gordon
SSRN
We give an overview and outlook of the field of reinforcement learning as it applies to solving financial applications of intertemporal choice. In finance, common problems of this kind include pricing and hedging of contingent claims, investment and portfolio allocation, buying and selling a portfolio of securities subject to transaction costs, market making, asset liability management and optimization of tax consequences, to name a few. Reinforcement learning allows us to solve these dynamic optimization problems in an almost model-free way, relaxing the assumptions often needed for classical approaches.A main contribution of this article is the elucidation of the link between these dynamic optimization problem and reinforcement learning, concretely addressing how to formulate expected intertemporal utility maximization problems using modern machine learning techniques.

On the Valuation and Analysis of Risky Debt: A Theoretical Approach Using a Multivariate Extension of the Merton Model
Fischer, Edwin O.,Kampl, Lisa-Maria,WÃ¶ckl, Ines
SSRN
We contribute to the literature on the valuation of risky debt by providing three nested multivariate extensions of the standard Merton model. First, we lay forth an approach to pricing risky debt irrespective of its interest payment structure and the specified redemption agreement. Second, we propose a technique for valuing multiple debt instruments within the same firm. Third, we provide an approach for pricing one or more debt instruments with continuous dividend payments.

Optimal management of pumped hydroelectric production with state constrained optimal control
Athena Picarelli,Tiziano Vargiolu
arXiv

We present a novel technique to solve the problem of managing optimally a pumped hydroelectric storage system. This technique relies on representing the system as a stochastic optimal control problem with state constraints, these latter corresponding to the finite volume of the reservoirs. Following the recent level-set approach presented in O. Bokanowski, A. Picarelli, H. Zidani, "State-constrained stochastic optimal control problems via reachability approach", SIAM J. Control and Optim. 54 (5) (2016), we transform the original constrained problem in an auxiliary unconstrained one in augmented state and control spaces, obtained by introducing an exact penalization of the original state constraints. The latter problem is fully treatable by classical dynamic programming arguments.

Personal Finance Decisions with Untruthful Advisors: an Agent-Based Model
Loretta Mastroeni,Maurizio Naldi,Pierluigi Vellucci
arXiv

Investors usually resort to financial advisors to improve their investment process until the point of complete delegation on investment decisions. Surely, financial advice is potentially a correcting factor in investment decisions but, in the past, the media and regulators blamed biased advisors for manipulating the expectations of naive investors. In order to give an analytic formulation of the problem, we present an Agent-Based Model formed by individual investors and a financial advisor. We parametrize the games by considering a compromise for the financial advisor (between a sufficient reward by bank and to keep his/her reputation), and a compromise for the customers (between the desired return and the proposed return by advisor). Then we obtain the Nash equilibria and the best response functions of the resulting game. We also describe the parameter regions in which these points result acceptable equilibria and the greediness/naivety of the customers emerge naturally from the model. Finally, we focus on the efficiency of the best Nash equilibrium.

Pipeline: The Worst Transportation Method of Oil, Except for All the Rest
Luong, Phat V.
SSRN
This paper studies the safety and environmental impacts of different crude oil transportation methods. The frequency, spillage volume, and environmental damage costs of pipeline accidents seem to be significantly higher than of trains and trucks. However, after adjusting for the distance and volume of oil transported by each method, pipeline has the lowest number of accidents, the least amount of oil discharged and the smallest environmental damage and clean-up cost per ton-mile. Moreover, lacking oil transmission pipeline hinders the producer's ability to collect associated gas. Consequently, the gas is flared or vented. The Granger causality between the excess takeaway capacity of oil pipeline and natural gas flaring confirms the impact of having inadequate transmission pipeline capacity.

Relation between non-exchangeability and measures of concordance of copulas
Damjana Kokol Bukovšek,Tomaž Košir,Blaž Mojškerc,Matjaž Omladič
arXiv

An investigation is presented of how a comprehensive choice of five most important measures of concordance (namely Spearman's rho, Kendall's tau, Spearman's footrule, Gini's gamma, and Blomqvist's beta) relate to non-exchangeability, i.e., asymmetry on copulas. Besides these results, the method proposed also seems to be new and may serve as a raw model for exploration of the relationship between a specific property of a copula and some of its measures of dependence structure, or perhaps the relationship between various measures of dependence structure themselves. In order to simplify the view on this method and provide a more conceptual interpretation a formulation is proposed borrowed from the imprecise probability setting which has been made possible for a standard probability method due to some recent discoveries.

Russiaâ€™s Banking Sector in 2018
Khromov, Michael
SSRN
As of January 1, 2019, the Russian banking system numbered 484 credit organizations. A year earlier then number stood at 542. During the year the number decreased by 58 organizations. Six years ago at the beginning of 2013, the number of credit organizations exceeded one thousand (1094). The Bank of Russia policy aimed at clearing the banking sector has triggered a reduction of the number of banks in operation. Over this period, the Bank of Russia withdrew more than 400 banking licenses. From late 2014 the policy aimed at withdrawing from the market those credit organizations which do not satisfy the requirements of the regulator coincided with the deterioration of the situation in the Russian economy and the imposition of international sanctions on major Russian banks. Correspondingly, already from 2014 the rate of banking license revocation has increased. When in 2013, around 4â€"5 banks on average per month lost their licenses then in 2014 the rate of banking license revocation increased to 7 lending organizations per month, and during the time of peak manifestations of crisis in the Russian economy and financial system seen in 2015â€"2016 on average 8 credit organizations per month lost the right to continue their banking activity. The number of revoked banking licenses peaked in 2016: the number of revoked licenses during that year hit 97. Moreover, 2016 saw the peak on the aggregate amount of the bank assets of the banks which lost their banking licenses: RUB 1.7 trillion or 2.0 percent of the overall volume of the banking sector assets.

Russiaâ€™s Public Sector and Privatization Policy in 2018
SSRN
From 2016, statistical data began to be published in the framework of the System of Public Property Management Efficiency Estimates. It was approved by Decree of the RF Government No 72 dated January 29, 2015, and introduced by way of replacing the public sector monitoring data, collected and released by the Federal State Statistics Service (Rosstat) since the early 2000s in accordance with the provisions stipulated in RF Government Decree No. 1 dated January 4, 1999 (as amended on December 30, 2002). Among other things, the System contains data on the number of federal state unitary enterprises (FSUEs) and joint-stock companies (JSCs) with RF stakes in their capital. Previously, such data were usually published as part of government privatization programs (from 2011 â€" for three-year period, and prior to 2011 â€" for one-year period). In the current Forecast Plan (Program) of Federal Property Privatization and the Main Directions of Federal Property Privatization for 2017â€"2019, relevant data are available only as of early 2016 (Table 1), and so in order to describe the processes taking place over the period 2016â€"2018, one must rely on data in the System of Public Property Management Efficiency Estimates.

Secondary Market Liquidity and Primary Market Allocations in Corporate Bonds
Flanagan, Thomas,Kedia, Simi,Zhou, Xing (Alex)
SSRN
Using a regulatory version of TRACE data that include almost all primary and secondary market trades in corporate bonds over the period 2010-2017, we provide the first comprehensive study on the primary market for corporate bonds. Secondary market illiquidity can drive gains from primary market allocations to far exceed underpricing. Based on initial allocations identified from regulatory disclosures by insurance firms, we find that gains from initial allocations are greater for investors with trading relationships with the underwriter. Such favoritism toward investors with trading relationships increases with secondary market illiquidity.

Steady State and Efficiency Convergence Dynamics in Alternative Banking Systems: The Cases of Islamic and Community Banks
Izzeldin, Marwan,Johnes, Jill,Ongena, Steven,Pappas, Vasileios,Tsionas, Efthymios G.
SSRN
This paper compares the efficiency dynamics of Islamic and community banks relative to their conventional counterparts. We employ parametric and non-parametric methods to analyze: i) a cross-country panel of Islamic and conventional banks from 23 countries; and, ii) a panel of community and conventional banks from the US. Parametric methods find no significant differences between the steady states and convergence rates for Islamic and conventional banks, but reveal distinctive patterns between community and conventional banks. To identify factors pertaining to these observed differences, we subject both data sets to further analyses. For the cross-country panel, factors like financial depth, transparency, economic stability and banking concentration can explain the different steady state levels and convergence rates between Islamic and conventional banks across sample countries. For the US panel, efficiency and liquidity creation compete as objectives for conventional banks, while liquidity creation is not penalized in steady state efficiency terms among community banks. In addition, for these banks steady state efficiency is positively related with profitability and negatively with capitalization.

The Dynamics and Pattern of Russiaâ€™s Economic Growth in 2018
SSRN
In 2016â€"2018, the economic situation was characterized by the gradual recovery of GDP positive dynamics with GDP growth rates increasing from 100.3 percent in 2016 to 101.6 percent and 102.3 percent in 2017 and 2018, respectively. The GDP real volume surpassed by 1.6 percentage point the indicator of 2014, having compensated the crisis decrease seen in 2015. Unlike the conditions of the previous two years, the nature of development of the economy in 2017-2018 was determined by simultaneous growth in demand on the international and domestic markets. With a relatively favorable foreign economic situation and sustainable positive dynamics, in 2018 exports amounted to 119.4 percent (as per the methods of the system of national accounts (SNA)) as compared to 2014. With the speed-up of the growth rates of the volume of exports to 6.3 percent, in 2018 the contribution of net exports to GDP increased to 3.5 percent against the indicator of 2.8 percent a year before in comparable prices (10.0 percent against 5.3 percent in current prices). Growth in net exports had a considerable effect on the dynamics and pattern of formation of GDP and compensated the weakening of domestic market dynamics.

The Information Content of Short-Term Options
Oikonomou, Ioannis,Stancu, Andrei,Symeonidis, Lazaros,Wese Simen, Chardin
SSRN
We exploit weekly options on the S&P 500 index to compute the weekly implied variance. We show that the weekly implied variance is a strong predictor of the weekly realized variance. In an encompassing regression test, it crowds out the information content of the monthly implied variance. Further tests reveal that the weekly implied variance outperforms not only the monthly implied variance but also well-established time series models of realized variance. This result holds both in- and out-of-sample and the forecast accuracy gains are significant.

The Optimal Deterrence of Crime: A Focus on the Time Preference of DWI Offenders
Yuqing Wang,Yan Ru Pei
arXiv

We develop a general model for finding the optimal penal strategy based on the behavioral traits of the offenders. We focus on how the discount rate (level of time discounting) affects the criminal propensity on the individual level, and how the aggregation of these effects influences criminal activities on the population level. The effects are aggregated based on the distribution of discount rate among the population. We study this distribution empirically through a survey with 207 participants, and we show that it follows zero-inflated exponential distribution. We quantify the effectiveness of the penal strategy as its net utility for the population, and show how this quantity can be maximized. During the maximization procedure, we discover that the effectiveness of DWI deterrence depends critically on the amount of fine and prison condition.

The Role of Capital on Islamic Bank Spin-Offs in Indonesia
SSRN
Some Islamic banks have experienced decreasing performance after spinning off from the parent company, and it is presumed that the amount of capital may have contributed to the decline. Hence, this paper aims to find a minimum amount of capital that Islamic bank must own after spin-offs in order to able to compete in the market and to achieve excellent performance. We employ the OLS method for small banks (asset below Rp 5 trillion) with variable Capital as the dependent variable and Bank Performance as the independent variable. We found that the relationship between performance and bank capital is a non-linear (quadratic) relationship that is convex, indicating that capital is not the only critical factor that contributes to the bankâ€™s improvement. The cluster analysis partially confirms that there is a specific pattern of capital in each of the clusters.

The Shift From Active to Passive Investing: Potential Risks to Financial Stability?
Anadu, Kenechukwu,Kruttli, Mathias S.,McCabe, Patrick E.,Osambela, Emilio,Shin, Chaehee
SSRN
The past couple of decades have seen a significant shift in assets from active to passive investment strategies. Although researchers have examined a variety of repercussions of this shift, its broader impact on financial stability has received less attention. We create a framework to incorporate existing research as well as our own novel analysis to examine the potential effects of this shift on financial stability through four different channels: (1) effects on investment fundsâ€™ liquidity transformation and redemption risks; (2) passive strategies that amplify market volatility; (3) increases in asset-management industry concentration; and (4) the effects on valuations, volatility, and comovement of assets that are included in indexes. Overall, the shift from active to passive investment strategies appears to be increasing some types of risk while diminishing others: The shift has probably reduced liquidity transformation risks, although some passive strategies amplify market volatility, and passive-fund growth is increasing asset-management industry concentration. We find mixed evidence that passive investing is contributing to the comovement of assets. Finally, we use our framework to assess how financial stability risks are likely to evolve if the shift to passive investing continues, noting that some of the repercussions of passive investing ultimately may slow its growth.

The Super-Hedging Pricing Rule of Financial Markets with Interest Rates
Villar, Renata
SSRN
We study consequences of the hypothesis of non-arbitrage in financial markets with two or more future periods and a friction present as different interest rates for borrowing and lending, varying in each time period and between assets. We show that absence of arbitrage opportunities implies the existence of state-prices vectors. Then we write the super hedging pricing rule as an optimization problem with a restriction in terms of state-prices vectors and obtain a characterization to it.

Time-consistent conditional expectation under probability distortion
Jin Ma,Ting-Kam Leonard Wong,Jianfeng Zhang
arXiv

We introduce a new notion of conditional nonlinear expectation under probability distortion. Such a distorted nonlinear expectation is not sub-additive in general, so is beyond the scope of Peng's framework of nonlinear expectations. A more fundamental problem when extending the distorted expectation to a dynamic setting is time-inconsistency, that is, the usual "tower property" fails. By localizing the probability distortion and restricting to a smaller class of random variables, we introduce a so-called distorted probability and construct a conditional expectation in such a way that it coincides with the original nonlinear expectation at time zero, but has a time-consistent dynamics in the sense that the tower property remains valid. Furthermore, we show that in the continuous time model this conditional expectation corresponds to a parabolic differential equation whose coefficient involves the law of the underlying diffusion. This work is the first step towards a new understanding of nonlinear expectations under probability distortion, and will potentially be a helpful tool for solving time-inconsistent stochastic optimization problems.

Venezuela: Where Bitcoin Trading Reflects Survival Rather than Choice
Johnson, Jackie
SSRN
An analyse of bolivar/bitcoin trading activity indicates that Bitcoin trading in Venezuela is more a reflection of a survival technique rather than an investment strategy with the median transactions price significantly smaller than the medians in the Argentine peso, the Brazilian real and the UK pound. A large number of very small trades point to the practice of exchanging only as many bitcoins as is necessary for immediate use, with inflation as high as 3-4%/day. An analysis of the size of transactions in bitcoins also points to much smaller bitcoin transactions in the bolivar compared to the peso, real and pound. While Bitcoin transactions in the real and the pound indicate a range of trading opportunities from small to large transactions, peso/bitcoin transactions indicate a currency that may be at the start of a journey not dissimilar to the bolivar as transactions start to get smaller in 2018. This analysis supports the anecdotal evidence that bolivar/bitcoin trading is used as a survival technique in a country with a failing economy and worthless fiat currency

Voting power of political parties in the Senate of Chile during the whole binomial system period: 1990-2017
Fabián Riquelme,Pablo González-Cantergiani,Gabriel Godoy
arXiv

The binomial system is an electoral system unique in the world. It was used to elect the senators and deputies of Chile during 27 years, from the return of democracy in 1990 until 2017. In this paper we study the real voting power of the different political parties in the Senate of Chile during the whole binomial period. We not only consider the different legislative periods, but also any party changes between one period and the next. The real voting power is measured by considering power indices from cooperative game theory, which are based on the capability of the political parties to form winning coalitions. With this approach, we can do an analysis that goes beyond the simple count of parliamentary seats.

Workplace Inequality in Pay Growth: A First Look
He, Jie,Li, Lei,Shu, Tao
SSRN
While previous literature of within-firm pay inequality exclusively focuses on the difference in pay levels between executives and employees, we study the difference in pay growth between the two groups (i.e., â€œpay growth gapâ€), especially its relation with a firmâ€™s past idiosyncratic stock return, the â€œskillâ€ component of stock performance. Using granular, individual-level compensation data for US public companies, we find a negative relation between pay growth gap and past performance, suggesting that executives enjoy higher relative pay growth when firms perform worse. This â€œreverse incentive alignmentâ€ exists in firms with poor performance but not those with good performance. Further, it is driven by the pay growth of executives, especially higher-ranked ones, rather than that of employees. Among poorly performing firms, turnover rates of executives relative to employees are also lower upon worse past performance. Our evidence is more consistent with managerial rent extraction than with other explanations such as differential talent or labor market conditions across the corporate hierarchy.

Worrying About Climate Change: Evidence from Mortgage Lending
Duan, Tinghua,Li, Frank Weikai
SSRN
We document a strong negative effect of local temperature anomaly on mortgage credit origination at the U.S county level. A 1Â°F increase in the past 36-month average temperature anomaly in a county reduces the mortgage approval rate by about 0.9% and loan amount by 6.9%. This result is robust to a host of empirical specifications that account for time-varying local demand for mortgage credit. The effect is stronger for counties with strong prior beliefs in climate change, counties more exposed to the risks of sea-level rise and during periods of elevated media attention. Our findings suggest that agentsâ€™ heightened beliefs about climate change induced by unusually warm weather affect their real decision-making and adaption behaviour.