Research articles for the 2019-12-09

(Debt) Overhang: Evidence from Resource Extraction
Wittry, Michael D.
I study the empirical importance of debt overhang using a unique dataset on resource extraction firms, which provides ex ante measures of investment opportunities and important variation in the terms of a firm's obligations. In particular, unsecured reclamation liabilities create overhang that is costly to resolve and induces firms to forgo and postpone positive NPV investments. Traditional debt, in contrast, imposes few overhang-related investment distortions. These results show that: (i) the overhang problem is potentially large and applies more broadly to a firm's non-debt liabilities; and (ii) overhang problems associated with traditional debt can be avoided through contracting and debt composition.

A percolation model for the emergence of the Bitcoin Lightning Network
Silvia Bartolucci,Fabio Caccioli,Pierpaolo Vivo

The Lightning Network is a so-called second-layer technology built on top of the Bitcoin blockchain to provide "off-chain" fast payment channels between users, which means that not all transactions are settled and stored on the main blockchain. In this paper, we model the emergence of the Lightning Network as a (bond) percolation process and we explore how the distributional properties of the volume and size of transactions per user may impact its feasibility. The agents are all able to reciprocally transfer Bitcoins using the main blockchain and also - if economically convenient - to open a channel on the Lightning Network and transact "off chain". We base our approach on fitness-dependent network models: as in real life, a Lightning channel is opened with a probability that depends on the "fitness" of the concurring nodes, which in turn depends on wealth and volume of transactions. The emergence of a connected component is studied numerically and analytically as a function of the parameters, and the phase transition separating regions in the phase space where the Lightning Network is sustainable or not is elucidated. We characterize the phase diagram determining the minimal volume of transactions that would make the Lightning Network sustainable for a given level of fees or, alternatively, the maximal cost the Lightning ecosystem may impose for a given average volume of transactions. The model includes parameters that could be in principle estimated from publicly available data once the evolution of the Lighting Network will have reached a stationary operable state, and is fairly robust against different choices of the distributions of parameters and fitness kernels.

Adversarial recovery of agent rewards from latent spaces of the limit order book
Jacobo Roa-Vicens,Yuanbo Wang,Virgile Mison,Yarin Gal,Ricardo Silva

Inverse reinforcement learning has proved its ability to explain state-action trajectories of expert agents by recovering their underlying reward functions in increasingly challenging environments. Recent advances in adversarial learning have allowed extending inverse RL to applications with non-stationary environment dynamics unknown to the agents, arbitrary structures of reward functions and improved handling of the ambiguities inherent to the ill-posed nature of inverse RL. This is particularly relevant in real time applications on stochastic environments involving risk, like volatile financial markets. Moreover, recent work on simulation of complex environments enable learning algorithms to engage with real market data through simulations of its latent space representations, avoiding a costly exploration of the original environment. In this paper, we explore whether adversarial inverse RL algorithms can be adapted and trained within such latent space simulations from real market data, while maintaining their ability to recover agent rewards robust to variations in the underlying dynamics, and transfer them to new regimes of the original environment.

An Alternative Formula for the Constant Growth Model
Forsyth, Juan A.
Purpose â€" The traditional one-stage constant growth formula has two main underlying assumptions: a company will be able to maintain its competitive advantage for completed investments in perpetuity, and each year in the future, it will be able to generate new investment opportunities with the same competitive advantage, which will also remain in perpetuity. The purpose of this paper is to develop a model that limits the duration of the competitive advantage.Design/methodology/approach â€" A new model is developed, and it is used to value a public company.Findings â€" In this study, the author introduces an alternative formula considering the duration of the competitive advantage, imposing a restriction on the fact that extraordinary returns cannot be sustained forever, and also separates the part of the value explained by the current investments from the portion of value created by future investments.Originality/value â€" The traditional one-stage constant growth model used to determine the continuing value of a company has limitations regarding the duration of the competitive advantage. The developed formula corrects the problem limiting the time extraordinary returns will remain over time.

An empirical study of neural networks for trend detection in time series
Alexandre Miot,Gilles Drigout

Detecting structure in noisy time series is a difficult task. One intuitive feature is the notion of trend. From theoretical hints and using simulated time series, we empirically investigate the efficiency of standard recurrent neural networks (RNNs) to detect trends. We show the overall superiority and versatility of certain standard RNNs structures over various other estimators. These RNNs could be used as basic blocks to build more complex time series trend estimators.

AÐ ÞJÃ"NA SÖMU HERRUM EN KEPPA ÞÃ": SAMEIGINLEGT EIGNARHALD Á ÍSLENSKUM HLUTABRÉFAMARKAÐI (Serving the Same Masters While Competing: Common Ownership of Listed Companies in Iceland)
Ã"ladóttir, Ásta Dís,Friðriksson, Friðrik Árni,Magnússon, Gylfi,Þráinsson, Valur
Icelandic Abstract: Tilgangur þessarar greinar er að fjalla um og varpa ljósi á sameiginlegt eignarhald fyrirtækja á skráðum hlutabréfamarkaði á Íslandi og er það borið saman við umfang slíks eignarhalds í Bandaríkjunum. Nokkur umræða hefur verið um hversu fáir aðilar eiga stóra hluti í íslenskum fyrirtækjum sem eru í samkeppni við hvert annað og því er umfang þessa og þróun á íslenskum hlutabréfamarkaði greind. Sjónum er beint að þremur mörkuðum hér á landi þar sem tveir eða þrír keppinautar eru skráðir í Kauphöll Íslands. Það eru trygginga-, fjarskipta, og fasteignamarkaðir. Þá er umfang fjárfestinga lífeyrissjóða á íslenskum hlutabréfamarkaði greint á fjórum mismunandi tímapunktum; árin 2003, 2007, 2014 og 2016.Þótt erfitt sé að bera saman hlutabréfaeign milli tímabila sést að sameiginlegt eignarhald var mun minna fyrir efnahagshrunið árið 2008 en á árunum eftir hrun, bæði hjá öllum stærstu hluthöfum skráðra fyrirtækja og þá einkum lífeyrissjóðum. Um mitt ár 2016 var eign lífeyrissjóða í skráðum hlutafélögum í Kauphöll Íslands orðin umtalsverð eða um 50% af markaðsvirði allra skráðra félaga. Stærstu lífeyrissjóðirnir áttu hlut í nánast öllum hlutafélögum í kauphöllinni. Á þeim mörkuðum sem hér er fjallað um fara lífeyrissjóðirnir með yfir 45% eign í öllum skráðum fasteignafélögum, yfir 35% í öllum skráðum tryggingafélögum og yfir 50% í fjarskiptafyrirtækjum á markaði.Ekki liggur fyrir hvaða afleiðingar þetta sameiginlega eignarhald á íslenskum fyrirtækjum hefur á samkeppni og verð. Engar rannsóknir hafa enn verið gerðar á því. Bandarískar rannsóknir benda þó til þess að slíkt eignarhald hafi skaðleg áhrif á samkeppni. Í ljósi umfangs þess á Íslandi er ástæða til þess að greina áhrif þess hér og mun greinin því varpa betra ljósi á hvernig þróunin hefur verið á Íslandi síðustu tæpu tvo áratugi.English Abstract: The article analyses common or horizontal ownership of shares on the Icelandic Stock Exchange. We compare this to common ownership of listed shares in the U.S. The situation in Iceland has not been subject to much formal research despite clear signs of concentrated ownership. We look at three Icelandic markets where two or three competing firms all have their shares listed on the stock exchange. The markets are for insurance, telecommunications and real estate. We also look at the holdings of shares by Icelandic pension funds at four points in time, the years 2003, 2007, 2014 and 2016. Although the stock market has changed considerably in many respects within that time frame, making direct comparison difficult, we conclude that common ownership was far less prevalent before the crash, both among pension funds and all shareholders. At mid-year 2016, the pension funds dominated holdings of shares in most listed companies in Iceland. The largest pension funds each held shares in almost all listed companies. In the three markets that we analyse the pension funds held over 45% of the shares in real estate companies, 35% in insurance and 50% in telecommunications. We do not analyse the consequences of this concentrated and common ownership on competition and prices. That remains a subject for further study. Based on the results from research into the effects of common ownership in the U.S. this development should though clearly be a cause for concern.

Conditional inference on the asset with maximum Sharpe ratio
Steven E. Pav

We apply the procedure of Lee et al. to the problem of performing inference on the signal-noise ratio of the asset which displays maximum sample Sharpe ratio over a set of possibly correlated assets. We find a multivariate analogue of the commonly used approximate standard error of the Sharpe ratio to use in this conditional estimation procedure. We also consider several alternative procedures, including the simple Bonferroni correction for multiple hypothesis testing, which we fix for the case of positive common correlation among assets, the chi-bar square test against one-sided alternatives, Follman's test, and Hansen's asymptotic adjustments.

Testing indicates the conditional inference procedure achieves nominal type I rate, and does not appear to suffer from non-normality of returns. The conditional estimation test has low power under the alternative where there is little spread in the signal-noise ratios of the assets, and high power under the alternative where a single asset has high signal-noise ratio. Unlike the alternative procedures, it appears to enjoy rejection probabilities montonic in the signal-noise ratio of the selected asset.

Convergence rates of large-time sensitivities with the Hansen--Scheinkman decomposition
Hyungbin Park

This paper investigates the large-time asymptotic behavior of the sensitivities of cash flows. In quantitative finance, the price of a cash flow is expressed in terms of a pricing operator of a Markov diffusion process. We study the extent to which the pricing operator is affected by small changes of the underlying Markov diffusion. The main idea is a partial differential equation (PDE) representation of the pricing operator by incorporating the Hansen--Scheinkman decomposition method. The sensitivities of the cash flows and their large-time convergence rates can be represented via simple expressions in terms of eigenvalues and eigenfunctions of the pricing operator. Furthermore, compared to the work of Park (Finance Stoch. 4:773-825, 2018), more detailed convergence rates are provided. In addition, we discuss the application of our results to three practical problems: utility maximization, entropic risk measures, and bond prices. Finally, as examples, explicit results for several market models such as the Cox--Ingersoll--Ross (CIR) model, 3/2 model and constant elasticity of variance (CEV) model are presented.

Corporate Governance and Stock Market Liquidity
Outa, Erick Rading,Waweru, Nelson,Ozili, Peterson K
The purpose of this paper is to examine the capital market effects of corporate governance (CG) practices of “comply or explain” on stock market liquidity in a frontier market. Using secondary data from Nairobi Securities Exchange (NSE) liquidity position is analyzed using panel data random effects regression against CG guidelines. The results show a negative and significant relationship between CG compliance and stock market liquidity suggesting that regulated CG practices improves market liquidity in Kenya. The results are remarkably robust to different measures of liquidity and supports agency and signaling theory. We provide evidence that security regulation improves stock market liquidity in a frontier market whose characteristics are thought not to favor regulation. Therefore the regulators and stakeholders could be motivated by the benefits of regulation and this could lead to renewed effort to improve the current compliance from the current 61.4%, to higher levels. Our finding shows that security market regulation through CG guidelines can improve stock market liquidity in frontier markets. This offers regulators and policy makers a strong motivation to enhance security regulation to strengthen capital market confidence.

Decision Making under Uncertainty: An Experimental Study in Market Settings
Federico Echenique,Taisuke Imai,Kota Saito

We design and implement a novel experimental test of subjective expected utility theory and its generalizations. Our experiments are implemented in the laboratory with a student population and pushed out through a large-scale panel to a general sample of the U.S.\ population. We find that a majority of subjects' choices are consistent with the maximization of {\em some} utility function, but not with subjective utility theory. The theory is tested by gauging how subjects respond to price changes. A majority of subjects respond to price changes in the direction predicted by the theory, but not to a degree that makes them fully consistent with subjective expected utility. Surprisingly, maxmin expected utility adds no explanatory power to subjective expected utility.

Our findings remain the same regardless of whether we look at laboratory data or the panel survey, even though the two subject populations are very different. The degree of violations of subjective expected utility theory is not affected by age nor cognitive ability, but it is correlated with financial literacy.

Deep Option Pricing - Term Structure Models
Kienitz, Joerg,Acar, Sarp Kaya,Liang, Qian,Nowaczyk, Nikolai
This paper proposes a data-driven approach, by means of an Artificial Neural Network (ANN), to value financial options within the setting of interest rate term structure models. This aims to accelerate existing numerical methods which is important for applications like historical VaR or exposure calculation being used in financial institutions. With ANNs being a universal function approximation method, this method trains an ANN on synthetically generated data including term structures of yield and volatility. Then, within an VaR or exposure calculation instead of applying costly numerical methods for the financial model, the engine runs the trained ANN. This is faster and more efficient and allows (a) considering term structures of yields, (b) term structures of volatilities and (c) trade interpolation. We outline the generation of the training data, the neural net selection and propose further methods for optimization. In particular we consider a control variate method and the application of no-arbitrage conditions and regularization to the cost function used for learning and calibration. Finally, we test our approach on the Hull-White model with time-dependent term structure for volatility and the the Trolle-Schwartz model. The latter adds an un-spanned stochastic volatility to the rates dynamic. The numerical results show that the ANN solution, especially the one with the control variate, is accurate and reduces the computing time significantly.

Do Local and Global Factors Impact the Emerging Markets’s Sovereign Yield Curves? Evidence from a Data-Rich Environment
Cepni, Oguzhan,Guney, Ibrahim,Kucuksarac, Doruk,Yilmaz, Muhammed Hasan
This paper investigates the relationship between the yield curve and macroeconomic factors for ten emerging sovereign bond markets using the sample from January 2006 to April 2019. To this end, the diffusion indices obtained under four categories (global variables, inflation, domestic financial variables, and economic activity) are incorporated by estimating dynamic panel data regressions together with the yield curve factors. Besides, in order to capture dynamic interaction between the yield curve and macroeconomic/financial factors, a panel VAR analysis based on the system GMM approach is utilized. Empirical results suggest that the level factor responds to shocks originated from inflation, domestic financial variables, and global variables. Furthermore, the slope factor is affected by shocks in global variables, and the curvature factor appears to be influenced by domestic financial variables. We also show that macroeconomic/financial factors captures significant predictive information over yield curve factors by running individual country factor-augmented predictive regressions and variable selection algorithms such as ridge regression, LASSO, and Elastic Net. Our findings have important implications for policymakers and fund managers by explaining the underlying forces of movements in the yield curve and forecasting accurately dynamics of yield curve factors.

Does IFRS Convergence Really Increase Accounting Qualities? Emerging Market Evidence
Fuad, Fuad,Juliarto, Agung,Harto, Puji
Purpose â€" This study aims to examine whether International Financial Reporting Standards (IFRS) convergence process adds value to the accounting quality dimensions, including accruals quality, earnings smoothing, timely loss recognition and earnings persistence.Design/methodology/approach â€" It analyzes the hypothesis of accounting quality changes in post-IFRS convergence by using the univariate and multivariate statistics. Particularly, the authors rely on panel data analyses using industrial companies’ data from 2008 until 2014, comprising 3,861 firm-years observations, in Indonesia.Findings â€" The results indicate that there is no conclusive evidence that all accounting quality dimensions including accruals quality,earnings smoothing, timely loss recognition and earnings persistence increased in post-IFRS convergence.Practical implications â€" The findings of this study may help regulators and standard setters to consider future adoption of IFRS, mostly to figure out the best “formula” to increase the usefulness of accounting information in post-IFRS convergence.Originality/value â€" Rather than doing piecemeal work, the current study focuses on IFRS convergence on a broader aspect of accounting quality dimensions. It also focuses on the convergence process of IFRS as an alternative of full adoption, which has been the focus of many research studies.

EINIGE ASPEKTE DER ESTNISCHEN GEHALTSPOLITIK (Certain Aspects of the Estonian Wages Policy)
Raudjärv, Matti
German Abstract: Zusammenfassung Als Folgerungen und Zusammenfassung kann behauptet werden â€" viele in der estnischen Gesellschaft lebende Menschen, die die Situation in unserer Wirtschaft und im Bildungswesen kennen, stehen auf dem sicheren Standpunkt, dass ohne eine zusätzliche Finanzierung der Hochschulbildung und ohne Anhebung der Gehälter der Beschäftigten es für uns nicht möglich ist, gleichwertige Partner für Hochschulen anderer Staaten zu sein. Dieser Standpunkt wird geteilt von Leitern der estnischen Hochschulen und natürlich auch von akademischen Beschäftigten und Stützpersonal.Politiker, so scheint es, verstehen die Sachlage nicht und haben kein ernsthaftes Interesse gegenüber diesen Problemen (ihre Gehälter und sonstige Vorteile sind ja genügend hoch!). Darüber hinaus, die meisten von denen, die gewählt wurden, können jetzt fast vier Jahre lang ein relativ ruhiges Leben führen. Leider richtet man den Blick nicht weitsichtig und strategisch in die Ferne, sondern lediglich bis zu den nächsten Wahlen â€" vielleicht gelingt es ja wieder!? Das hat uns die bisherige Praxis in Estland gezeigt, und dies hat sich immer weiter vertieft. Auch der Unter-schreibende, der ein Wähler ist, kann eine solche Meinung nur bestätigen.Es sollten womöglich auch die Gewerkschaften des Bildungsbereiches erheblich kraftvoller in der Gesellschaft auftreten, um ihren Platz zu rechtfertigen.Diese Untersuchung sollte unbedingt weiterentwickelt werden (bis dahin sollte aber in Bezug auf Gehälter alles Mögliche unternommen werden!), denn Vorhandensein und Erreichbarkeit vergleichbarer statistischer Angaben ließ im Laufe der Untersuchung viel zu wünschen übrig.English Abstract: The objective of the paper is to bring up again the important issue â€" the fact that the academic staff, researchers and support staff of universities have low salaries in Estonia and their work is not highly valued or appreciated in the society, and to assess the situation. Unless changes are made soon in this area, qualified persons will gradually move from universities and establishments of higher education to other areas/sectors of national economy (some of them probably also to other countries) and the quality, competitiveness and standards of teaching and research activities will decline. Development of the whole Estonian national economy would suffer. This is the opinion of both the heads of the universities and many practical experts of the economy who are familiar with the situation.The research tasks of the paper are: to identify and highlight positions on the problem of salaries in Estonian higher education; to present, study and assess salary levels in Estonia; to examine the positions of Estonian politicians in the issue of salaries; to draw conclusions.Instead of theoretical thoughts/positions and comparisons between them and their synthesis, the author of the paper above all relies on practical opinions and the required trends/changes arising from them.

Finance Without Brownian Motions: An Introduction To Simplified Stochastic Calculus
Aleš Černý,Johannes Ruf

The paper introduces a simple way of recording and manipulating stochastic processes without explicit reference to a probability measure. In the new calculus, operations traditionally presented in a measure-specific way are instead captured by tracing the behaviour of jumps (also when no jumps are physically present). The new calculus is thus intuitive and compact. The calculus is also fail-safe in that, under minimal assumptions, all formal calculations are guaranteed to yield mathematically well-defined stochastic processes. Several illustrative examples of the new concept are given, among them a novel result on the Margrabe option to exchange one defaultable asset for another.

Financial Performance Trends of United States Hockey Inc: A Resource-Dependency Approach
Omondi-Ochieng, Peter
Purpose â€" The purpose of this paper is to examine the 2009 to 2016 financial performance of the US Hockey Inc., using financial effectiveness indicators and financial efficiency ratios.Design/methodology/approach â€" With the assistance of financial trend analysis, archival data were used to examine the financial performance (evaluated by net income), financial effectiveness (indicated by total assets and total revenues) and financial efficiency (examined by programme services ratios and return on assets) of US Hockey Inc.Findings â€" On average, the financial performance of the organization was positive ($30,895 net income per year). Financial effectiveness was steady with increases in assets and revenues. Financial efficiency was poor with 79% of revenues spent on programme services and 1.45%average return on asset.Research limitations/implications â€" The results can be generalized to similar national non-profit sports federations but not corporate sports entities with dissimilar financial goals.Practical implications â€" The results revealed that national non-profit sports federations can boost their financial performance by maintaining a double strategically focus on both financial effectiveness and financial efficiency.Originality/value â€" The study used both financial effectiveness and financial efficiency measures to evaluate the financial performances of a national non-profit sports federation â€" a neglected approach similar studies.

From Generalized Linear Models to Neural Networks, and Back
Wuthrich, Mario V.
We present how to enhance classical generalized linear models by neural network features. On the way to get there, we highlight the traps and pitfalls that need to be avoided to get good statistical models. This includes the non-uniqueness of sufficiently good regression models, the balance property, and representation learning, which brings us back to the concept of the good old generalized linear models.

Global Well-posedness of Non-Markovian Mutidimensional Superquadratic BSDE
Kihun Nam

Using purely probabilistic argument, we prove the global well-posedness of multidimensional superquadratic backward stochastic differential equations (BSDEs) without Markovian assumption. The key technique is the interplay between the local well-posedness of fully coupled path-dependent forward backward stochastic differential equations and backward iterations of the superquadratic BSDE. The superquadratic BSDE in this article includes quadratic BSDEs appear in stochastic differential game and price impact model. Our result also provides the well-posedness of a system of path-dependent quasilinear PDE that generalizes Ladyzhenskaia and Uraltseva (1968).

How much is optimal reinsurance degraded by error?
Yinzhi Wang,Erik Bølviken

The literature on optimal reinsurance does not deal with how much the effectiveness of such solutions is degraded by errors in parameters and models. The issue is investigated through both asymptotics and numerical studies. It is shown that the rate of degradation is often $O(1/n)$ as the sample size $n$ of historical observations becomes infinite. Criteria based on Value at Risk are exceptions that may achieve only $O(1/\sqrt{n})$. These theoretical results are supported by numerical studies. A Bayesian perspective on how to integrate risk caused by parameter error is offered as well.

Impact of Geopolitical Risk on Foreign Remittances
Oad Rajput, Suresh Kumar,Bajaj, Namarta Kumari,Siyal, Tariq Aziz
This study seeks to examine the hidden-cointegration among Geopolitical Risk (GPR) and foreign remittances. The suitable models for this study are Nonlinear Autoregressive Distributed Lag (NARDL) model to find the nature of impact (symmetric or asymmetric), and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to examine the volatility of foreign remittances using data for BRIC economies. The findings from NARDL suggests that in short-run geopolitical risk is asymmetric to foreign remittances in BRIC economies. Whereas, in long-run geopolitical risk is asymmetric to foreign remittances in the case of Brazil, Russia and India. We find volatility in GPR transmits to volatility in foreign remittances in the case of Brazil, Russia, and India. Remittances in China are found to be least volatile during geopolitical risk. The policymakers, migrants, and recipients should consider the asymmetric and volatile nature of geopolitical risk while making decisions about policies and transfer of remittances respectively.

Improving Evaluation Techniques for Credit Risky Securities
Letizia, Aldo
The present value of bonds and loans is commonly calculated as a sum of contractual cash flows discounted by default-free interest rates added by an appropriate credit spread. The evidence that investors require higher nominal returns for credit risky securities is commonly invoked as the main argument in support of this approach. However, although it is widely applied in the common practice, it remains a quick-fix solution for several reasons. First, it does not properly account for the probability of collecting contractual cash flows. Second, it leads to the wrong conclusion that the present value of financial instruments remains unchanged when fluctuations of risk-free rates are perfectly balanced by opposite changes in the relevant credit spread. Third, it makes the more risky bonds appear more profitable because credit spread, when included into discount rates, inevitably leads to calculate internal rates of return inversely correlated to the borrower’s creditworthiness. This work shows how refined cash-flow mapping techniques may be used in order to design a double-leg approach which properly accounts for expected credit losses and credit survival probabilities. This approach leads to an accurate evaluation of traded bonds on the sole basis of market information. In addition, it defines complete non-arbitrage conditions and overcomes the flaws of the most common pricing models for credit risky securities.

Internet Financial Reporting Adoption: Exploring the Influence of Board Role Performance and Isomorphic Forces
Bananuka, Juma,Night, Sadress,Ngoma, Muhammed,Najjemba, Grace Muganga
Purpose â€" This study aims to examine the contribution of board role performance and isomorphic forces on internet financial reporting.Design/methodology/approach â€" This study is cross-sectional and correlational. Data were collected through a questionnaire survey of 40 financial services firms. The study’s unit of analysis was a firm. Chief Internal Auditors and Chief Finance Officers were the study’s unit of inquiry. Data were analyzed through correlation coefficients and linear regression using Statistical Package for Social Sciences.Findings â€" The results suggest that board role performance and isomorphic forces are significant predictors of internet financial reporting. However, board role performance is not a significant predictor of internet financial reporting in the presence of isomorphic forces. The control and strategic roles of the board are positively and significantly associated with internet financial reporting unlike the service role. Only the coercive isomorphism is positively and significantly associated with internet financial reporting unlike the normative and mimetic isomorphism.Originality/value â€" This study provides initial empirical evidence on the contribution of board role performance and isomorphic forces on internet financial reporting using evidence from Uganda’s financial service firms. To the researcher’s knowledge, this is the first perception-based study on internet financial reporting.

Investigating the Investment Behaviors in Cryptocurrency
Dingli Xi,Timothy Ian O'Brien,Elnaz Irannezhad

This study investigates the socio-demographic characteristics that individual cryptocurrency investors exhibit and the factors which go into their investment decisions in different Initial Coin Offerings. A web based revealed preference survey was conducted among Australian and Chinese blockchain and cryptocurrency followers, and a Multinomial Logit model was applied to inferentially analyze the characteristics of cryptocurrency investors and the determinants of the choice of investment in cryptocurrency coins versus other types of ICO tokens. The results show a difference between the determinant of these two choices among Australian and Chinese cryptocurrency folks. The significant factors of these two choices include age, gender, education, occupation, and investment experience, and they align well with the behavioural literature. Furthermore, alongside differences in how they rank the attributes of ICOs, there is further variance between how Chinese and Australian investors rank deterrence factors and investment strategies.

Leakage of rank-dependent functionally generated trading strategies
Kangjianan Xie

This paper investigates the so-called leakage effect of trading strategies generated functionally from rank-dependent portfolio generating functions. This effect measures the loss in wealth of trading strategies due to renewing the portfolio constituent stocks. Theoretically, the leakage effect of a trading strategy is expressed explicitly by a finite-variation term. The computation of the leakage is different from what previous research has suggested. The method to estimate leakage in discrete time is then introduced with some practical considerations. An empirical example illustrates the leakage of the corresponding trading strategies under different constituent list sizes.

Limitations in an Imitation Game: Lessons from another Bitcoin Copycat
Cahill, Daniel,Liu, Zhangxin Frank
We find strong evidence that imitation to the leader in an uncertain environment provides short-term early success without enhancing long-term survival. Using a unique setting in cryptocurrencies where Bitcoin has been the centre focus, we define copycats as cryptocurrencies that have a name similar to Bitcoin. Our results show copycats earn higher returns in the first four weeks of trading but have a lower survival rate comparing to non-copycats. Our results are robust to an alternative definition of copycat and an instrumental variable.

Management Forecasts of Volatility
Ellahie, Atif,Peng, Xiaoxia
Forecasting volatility is important but inherently difficult. We examine the predictive information content of management forecasts of stock return volatility (i.e., expected volatility) disclosed in annual reports. We find that expected volatility predicts near-term and longer-term stock return volatility and earnings volatility incremental to historical volatility, implied volatility, firm characteristics, and alternative measures of uncertainty. We also find that expected volatility reflects private information of managers about future investment activities, such as mergers and acquisitions, and R&D intensity. Finally, we find that the predictive power of expected volatility is lower when managers have stronger incentives to bias these forecasts in order to manage earnings. Overall, we provide novel evidence that management forecasts of volatility contain private information about future uncertainty that can be useful for forecasting volatility.

On Utility Maximisation Under Model Uncertainty in Discrete-Time Markets
Miklós Rásonyi,Andrea Meireles-Rodrigues

We study the problem of maximising terminal utility for an agent facing model uncertainty, in a frictionless discrete-time market with one safe asset and finitely many risky assets. We show that an optimal investment strategy exists if the utility function, defined either over the positive real line or over the whole real line, is bounded from above. We further find that the boundedness assumption can be dropped provided that we impose suitable integrability conditions, related to some strengthened form of no-arbitrage. These results are obtained in an alternative framework for model uncertainty, where all possible dynamics of the stock prices are represented by a collection of stochastic processes on the same filtered probability space, rather than by a family of probability measures.

Ownership and Governance Style: New Evidence from Nonfinancial Blockholders
Israelsen, Ryan D.,Schwartz-Ziv, Miriam,Weston, James
Different types of blockholders govern differently. Committed (non-financial) blockholders are 6 times more likely to self-identify as active, and the language of their filings reflects governance through voice rather than exit. These differences in governance persist over a firm’s life cycle. We also find that governance by committed blocks may contaminate previous studies’ economic interpretation about governance by passive investors around index thresholds. Finally, the performance of firms with a committed block is similar to firms with a financial block, consistent with dynamic equilibrium models of optimal ownership. Firms with committed blockholders appear to have lower agency costs.

SDG Bonds: An Exploration, via a Case Study, of the Key Attributes of a Novel Financial Instrument That May Help Achieve Agenda 2030’s Sustainable Development Goals
Bina, Michele
The launch by the United Nations of Agenda 2030 with its 17 Sustainable Development Goals (SDGs) is creating new paradigms for business, capital markets, society, and many other fields of human endeavor. Financing the SDGs is an important part of the solution. While Green bonds have taken a prominent role over the last decade in financing sustainability projects, their application remains a capital markets niche. The SDGs, because of their multiplicity, shift the paradigm from a focus on single “green” projects to a holistic concept of sustainability which goes beyond the single project or asset typically financed with Green bonds. As a result of the growing evidence of the significant business opportunities the SDGs offer, corporations are now increasingly embracing this holistic approach to sustainability and are deeply embedding the SDGs into their long term corporate strategies. Consequently corporations have been looking for a financial instrument that better caters to this holistic, rather than ad-hoc, approach to sustainability.SDG Bonds have been proposed as an answer to this need. The general-purpose SDG Bonds in particular offer the required flexibility to achieve broader goals beyond single project financing and importantly, provide an unambigous signal of this intention to investors who are increasingly seeking opportunities in this space. There are three cornerstones that underpin SDG Bond transactions:1. A clear link to the sustainability strategy of the issuer, through pre-determined sustainability targets2. An upfront discount in the pricing of the SDG Bond issue, that reflects the economic value of the sustainability strategy of the issuer3. The assurance provided by external auditors on the achievement of the predetermined sustainability targets.The successful launch in September 2019 of the first ever general-purpose SDG Bond by ENEL, a multinational corporation, is a milestone in the financing of Agenda 2030. Potentially this expands opportunities to finance Agenda 2030, and indeed could be the beginning of a paradigm shift in debt and, perhaps in future, equity capital markets as holistic approaches to sustainability increasingly define corporate missions and investors’ perspectives. This behavioral shift by corporations and investors, and the creation by capital markets of new financial instruments to accommodate these aspirations may have another consequence. They may also represent further evidence of the declining relevance of economic theories based on “rational economic man”, and much of the microeconomic foundations of neo-classical economics.This paper examines the rationale that has led a major global corporation to issue SDG Bonds and how these differentiate themselves from Green bonds in significant ways. There are some, unexpected, consequences stemming from this event which are also briefly explored in this paper. Market pricing of SDG Bonds is analysed; it points to potential market failures in a number of areas. This, as well as other themes explored here, suggest several avenues of further research in what promises to become a rich new segment of study both for academics and practitioners in the capital markets.

Sanction or Financial Crisis? An Artificial Neural Network-Based Approach to model the impact of oil price volatility on Stock and industry indices
Somayeh Kokabisaghi,Mohammadesmaeil Ezazi,Reza Tehrani,Nourmohammad Yaghoubi

Financial market in oil-dependent countries has been always influenced by any changes in international energy market, In particular, oil price.It is therefore of considerable interest to investigate the impact of oil price on financial markets. The aim of this paper is to model the impact of oil price volatility on stock and industry indices by considering gas and gold price,exchange rate and trading volume as explanatory variables. We also propose Feed-forward networks as an accurate method to model non-linearity. we use data from 2009 to 2018 that is split in two periods during international energy sanction and post-sanction. The results show that Feed-forward networks perform well in predicting variables and oil price volatility has a significant impact on stock and industry market indices. The result is more robust in the post-sanction period and global financial crisis in 2014. Herein, it is important for financial market analysts and policy makers to note which factors and when influence the financial market, especially in an oil-dependent country such as Iran with uncertainty in the international politics. This research analyses the results in two different periods, which is important in the terms of oil price shock and international energy sanction. Also, using neural networks in methodology gives more accurate and reliable results. Keywords: Feed-forward networks,Industry index,International energy sanction,Oil price volatility

Seasonal Anomalies in the Market for American Depository Receipts
Lobão, Júlio
Purpose â€" The literature provides extensive evidence for seasonality in stock market returns, but is almost non-existent concerning the potential seasonality in American depository receipts (ADRs). To fill this gap, this paper aims to examine a number of seasonal effects in the market for ADRs.Design/methodology/approach â€" The paper examines four ADRs for the period from April 1999 to March 2017 to look for signs of eight important seasonal anomalies. The authors follow the standard methodology of using dummy variables for the time period of interest to capture excess returns. For comparison, the same analysis on two US stock market indices is conducted.Findings â€" The results show the presence of a highly significant pre-holiday effect in all return series, which does not seem to be justified by risk. Moreover, turn-of-the-month effects, monthly effects and day-of-the-week effects were detected in some of the ADRs. The seasonality patterns under analysis tended to be stronger in emerging market-based ADRs.Research limitations/implications â€" Overall, the results show that significant seasonal patterns were present in the price dynamics of ADRs. Moreover, the findings lend support to the idea that emerging markets are less efficient than developed stock markets.Originality/value â€" This is the most comprehensive study to date for indication of seasonal anomalies in the market for ADRs. The authors use an extensive sample that includes recent significant financial events such as the 2007/2008 financial crisis and consider ADRs with different characteristics, which allows to draw comparisons between the differential price dynamics arising in developed market-based ADRs and in the ADRs whose underlying securities are traded in emerging markets.

The Global Competitiveness Index: A Comparative Analysis between Turkey and G8 Nations
Taskinsoy, John
The Basel Committee on Banking Supervision (i.e. Basel I, II & III), the International Monetary Fund and the World Bank (i.e. Financial Sector Assessment Program), the World Trade Organization, the Bank for International Settlements, the US Federal Reserve, the European Central Bank, the European Banking Authority (EBA), Committee of European Banking Supervisors (CEBS), the Financial Services Authority of the UK, the Bank of Japan, the supervisory community and regulators (i.e. domestic and international), practitioners, and bank executives gravely failed to strengthen the global financial stability. On the contrary, financial authorities in many of the advance nations (particularly, the Fed’s expansive policies and the ECB’s reluctance to admit its blindness to the severity of risks that caused near global financial meltdown in 2008) have directly or indirectly contributed to global financial instability. The Global Competitive Index through its twelve pillars is a more complete measurement of financial stability in each country and globally. Analyses throughout this study compared Turkey’s competitiveness rankings with those of the G8 countries. The results show that Turkey’s mean overall ranking is significantly higher than that of Canada, France, Germany, Japan, and the UK; the difference in means was statistically significant. However, even though Turkey’s mean overall ranking was slightly higher than that of Italy, and lower than that of the Russian Federation, nevertheless the difference in means was not statistically significant.

The Impact of Transaction Costs in Portfolio Optimization: A Comparative Analysis Between the Cost of Trading in Peru and the United States
Chavalle, Luc,Chavez-Bedoya, Luis
Purpose â€" This paper aims to analyze the impact of transaction costs in portfolio optimization in Peru. The study aims to compare the transaction costs structure applied in Peru with respect to the ones applied in the USA, and over a few dimensions.Design/methodology/approach â€" The paper opted for an empirical study analyzing the cost of rebalancing portfolios over a set period and dimensions. Stocks have been carefully selected using Bloomberg terminals, and portfolio designed then rebalanced using VBA programming. Over a few dimensions as type and number of stocks, holding period and trading strategy, the behavior of these different transaction costs has been compared. The analysis has been done for four different portfolios.Findings â€" The paper provides empirical insights about how a retail investor actively trading in Peru can pay up to 14 times more in transaction costs than trading the same portfolio in the USA. These comparatively high transaction costs prevent retail investors to trade in the Peruvian stock market while fueling illiquidity to this market.Research limitations/implications â€" The paper deals with a limited amount of Peruvian stocks. Researchers are encouraged to test the proposition further, including other dimensions.Practical implications â€" The paper includes implications for any retail investor that wants to invest in Peruvian stocks, giving an insight about how expensive it is to actively rebalance a portfolio in Peru.Originality/value â€" This paper fulfils an identified need to study how much it costs to actively invest on the stock market in Peru.

To snipe or not to snipe, that is the question! Transitions in sniping behaviour among competing algorithmic traders
Somayeh Kokabisaghi,Eric J Pauwels,Andre B Dorsman

In this paper we re-analyse the transition from sure to probabilistic sniping as explored in Menkveld and Zoican [14]. In that paper, the authors introduce a stylized version of a competitive game in which high frequency traders (HFTs) interact with each other and liquidity traders. The authors show that risk aversion plays an important role in the transition from sure to mixed (or probabilistic) sniping. In this paper, we re-interpret and extend these conclusions in the context of repeated games and highlight some differences in results. In particular, we identify situations in which probabilistic sniping is genuinely profitable that are qualitatively different from the ones obtained in [14]. Keywords: algorithmic trading,sniping, electronic exchange,high-frequency traders,Nash equilibrium,repeated games,bandits, subgame-perfect equilibrium,transition

Understanding the dual formulation for the hedging of path-dependent options with price impact
Bruno Bouchard,Xiaolu Tan

We consider a general path-dependent version of the hedging problem with price impact of Bouchard et al. (2019), in which a dual formulation for the super-hedging price is obtained by means of PDE arguments, in a Markovian setting and under strong regularity conditions. Using only probabilistic arguments, we prove, in a path-dependent setting and under weak regularity conditions, that any solution to this dual problem actually allows one to construct explicitly a perfect hedging portfolio. From a pure probabilistic point of view, our approach also allows one to exhibit solutions to a specific class of second order forward backward stochastic differential equations, in the sense of Cheridito et al. (2007). Existence of a solution to the dual optimal control problem is also addressed in particular settings. As a by-product of our arguments, we prove a version of It{\^o}'s Lemma for path-dependent functionals that are only C^{0,1} in the sense of Dupire.

Using the Z-Score to Analyze the Financial Soundness of Insurance Firms
Moreno, Ignacio,Parrado-Martínez, Purificación,Trujillo‐Ponce, Antonio
This paper compares six different approaches to calculate Z-score using a final dataset of 183 insurers (1,382 observations) operating in the Spanish insurance sector during the period 2010-2017. This measure of risk has widely been used in the banking literature, and it has recently been applied to the insurance sector as an indicator of financial soundness. Using different methodologies (root mean squared error, ordinary least square and system-GMM regressions), we find that the best formula for calculating Z-score is the one that combines the current value of the return on assets and capitalization with the standard deviation of the returns calculated over the full period.

VAT tax gap prediction: a 2-steps Gradient Boosting approach
Giovanna Tagliaferri,Daria Scacciatelli,Pierfrancesco Alaimo Di Loro

Tax evasion is the illegal non-payment of taxes by individuals, corporations, and trusts. It results in a loss of state revenue that can undermine the effectiveness of government policies. One measure of tax evasion is the so-called tax gap: the difference between the income that should be reported to the tax authorities and the amount actually reported. However, economists lack a robust method for estimating the tax gap through a bottom-up approach based on fiscal audits. This is difficult because the declared tax base is available on the whole population but the income reported to the tax authorities is generally available only on a small, non-random sample of audited units. This induces a selection bias which invalidates standard statistical methods. Here, we use machine learning based on a 2-steps Gradient Boosting model, to correct for the selection bias without requiring any strong assumption on the distribution. We use our method to estimate the Italian VAT Gap related to individual firms based on information gathered from administrative sources. Our algorithm estimates the potential VAT turnover of Italian individual firms for the fiscal year 2011 and suggests that the tax gap is about 30% of the total potential tax base. Comparisons with other methods show our technique offers a significant improvement in predictive performance.

q-Factors and Investment CAPM
Zhang, Lu
The q-factor model shows strong explanatory power and largely summarizes the cross section of average stock returns. In particular, the q-factor model fully subsumes the Fama-French (2018) 6-factor model in head-to-head factor spanning tests. The q-factor model is an empirical implementation of the investment CAPM. The basic philosophy is to price risky assets from the perspective of their suppliers (firms), as opposed to their buyers (investors). As a disruptive innovation, the investment CAPM has broad-ranging implications for academic finance and asset management practice.