Research articles for the 2020-01-23

A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting
Zhengkun Li,Minh-Ngoc Tran,Chao Wang,Richard Gerlach,Junbin Gao
arXiv

Value-at-Risk (VaR) and Expected Shortfall (ES) are widely used in the financial sector to measure the market risk and manage the extreme market movement. The recent link between the quantile score function and the Asymmetric Laplace density has led to a flexible likelihood-based framework for joint modelling of VaR and ES. It is of high interest in financial applications to be able to capture the underlying joint dynamics of these two quantities. We address this problem by developing a hybrid model that is based on the Asymmetric Laplace quasi-likelihood and employs the Long Short-Term Memory (LSTM) time series modelling technique from Machine Learning to capture efficiently the underlying dynamics of VaR and ES. We refer to this model as LSTM-AL. We adopt the adaptive Markov chain Monte Carlo (MCMC) algorithm for Bayesian inference in the LSTM-AL model. Empirical results show that the proposed LSTM-AL model can improve the VaR and ES forecasting accuracy over a range of well-established competing models.



A Comparison among Reinforcement Learning Algorithms in Financial Trading Systems
Corazza, Marco,Fasano, Giovanni,Gusso, Riccardo,Pesenti, Raffaele
SSRN
In this work we analyze and implement different Reinforcement Learning (RL) algorithms in financial trading system applications. RL-based algorithms applied to financial systems aim to find an optimal policy, that is an optimal mapping between the variables describing the state of the system and the actions available to an agent, by interacting with the system itself in order to maximize a cumulative return. In this contribution we compare the results obtained considering different on-policy (SARSA) and off-policy (Q-Learning, Greedy-GQ) RL algorithms applied to daily trading in the Italian stock market. We consider both computational issues related to the implementation of the algorithms, and issues originating from practical application to real stock markets, in an effort to improve previous results while keeping a simple and understandable structure of the used models.

A Three-Country Macroeconomic Model for Portugal
Pienkowski, Alex
SSRN
This paper outlines a simple three-country macroeconomic model designed to focus on the transmission of external shocks to Portugal. Building on the framework developed by Berg et al (2006), this model differentiates between shocks originating from both inside and outside the euro area, as well as domestic shocks, each of which have different implications for Portugal. This framework is also used to consider the dynamics of the Portuguese economy over recent decades. The model, which is designed to guide forecasts and undertake simulations, can easily be modified for use in other small euro area countries.

A growth adjusted price-earnings ratio
Graham Baird,James Dodd,Lawrence Middleton
arXiv

The purpose of this paper is to introduce a new growth adjusted price-earnings measure (GA-P/E) and assess its efficacy as measure of value and predictor of future stock returns. Taking inspiration from the interpretation of the traditional price-earnings ratio as a period of time, the new measure computes the requisite payback period whilst accounting for earnings growth. Having derived the measure, we outline a number of its properties before conducting an extensive empirical study utilising a sorted portfolio methodology. We find that the returns of the low GA-P/E stocks exceed those of the high GA-P/E stocks, both in an absolute sense and also on a risk-adjusted basis. Furthermore, the returns from the low GA-P/E porfolio was found to exceed those of the value portfolio arising from a P/E sort on the same pool of stocks. Finally, the returns of our GA-P/E sorted porfolios were subjected to analysis by conducting regressions against the standard Fama and French risk factors.



Autonomous Factor Forecast Quality: The Case of the Eurosystem
Veyrune, Romain,Guo, Shaoyu
SSRN
The publication of liquidity forecasts can be understood as part of central banks' push toward greater transparency regarding monetary policy implementation. However, the advantages of transparency can only be realized if the information provided is accurate and reliable. This paper (1) provides an overview of the international practice of publishing the forecasts; (2) proposes and implements a framework to evaluate the accuracy and reliability of forecasts using the long history of Eurosystem forecasts as a case study; and (3) analyzes the Eurosystem forecast errors to determine the factors influencing forecast quality. A supporting factor for a high-quality forecast is the contemporaneousness of the information used, whereas money market segmentation can weigh on forecast quality.

Bank Capital and the Cost of Equity
Belkhir, Mohamed,Ben Naceur, Sami,Chami, Ralph ,Samet, Anis
SSRN
Using a sample of publicly listed banks from 62 countries over the 1991-2017 period, we investigate the impact of capital on banks' cost of equity. Consistent with the theoretical prediction that more equity in the capital mix leads to a fall in firms' costs of equity, we find that better capitalized banks enjoy lower equity costs. Our baseline estimations indicate that a 1 percentage point increase in a bank's equity-to-assets ratio lowers its cost of equity by about 18 basis points. Our results also suggest that the form of capital that investors value the most is sheer equity capital; other forms of capital, such as Tier 2 regulatory capital, are less (or not at all) valued by investors. Additionally, our main finding that capital has a negative effect on banks' cost of equity holds in both developed and developing countries. The results of this paper provide the missing evidence in the debate on the effects of higher capital requirements on banks' funding costs.

Biases in International Portfolio Allocation and Investor Protection Standards
Kwabi, Frank,Thapa, Chandra,Paudyal, Krishna,Adegbite, Emmanuel
SSRN
Economic reasoning suggests that financial globalization that encourages optimal international portfolio investments should improve investor protection standards (IPS) of a country. In practice, however, investors manifest varying degrees of suboptimal international portfolio allocations. Using a panel dataset covering 44 countries spanning over 15 years we examine whether suboptimal equity portfolio allocation in part is associated with the cross-country variations in IPS. Consistent with economic reasoning we find robust indications that international portfolio allocation may play an important role in the development of IPS. More specifically, the quality of IPS improves with higher degrees of optimal international equity portfolio allocation of domestic and foreign investors.

Capital Flows at Risk: Taming the Ebbs and Flows
Gelos, Gaston,Górnicka, Lucyna,Koepke, Robin,Sahay, Ratna,Sgherri, Silvia
SSRN
The volatility of capital flows to emerging markets continues to pose challenges to policymakers. In this paper, we propose a new framework to answer critical policy questions: What policies and policy frameworks are most effective in dampening sharp capital flow movements in response to global shocks? What are the near- versus medium-term trade-offs of different policies? We tackle these questions using a quantile regression framework to predict the entire future probability distribution of capital flows to emerging markets, based on current domestic structural characteristics, policies, and global financial conditions. This new approach allows policymakers to quantify capital flows risks and evaluate policy tools to mitigate them, thus building the foundation of a risk management framework for capital flows.

Comments are welcome
Asier Minondo
arXiv

Scholars present their new research at seminars and conferences, and send drafts to peers, hoping to receive comments and suggestions that will improve the quality of their work. Using a dataset of papers published in economics journals, this article measures how much peers' individual and collective comments improve the quality of research. Controlling for the quality of the research idea and author, I find that a one standard deviation increase in the number of peers' individual and collective comments increases the quality of the journal in which the research is published by 47%.



Completing the Market: Generating Shadow CDS Spreads by Machine Learning
Hu, Nan,Li, Jian,Mayer Cirkel, Alexis
SSRN
We compared the predictive performance of a series of machine learning and traditional methods for monthly CDS spreads, using firms' accounting-based, market-based and macroeconomics variables for a time period of 2006 to 2016. We find that ensemble machine learning methods (Bagging, Gradient Boosting and Random Forest) strongly outperform other estimators, and Bagging particularly stands out in terms of accuracy. Traditional credit risk models using OLS techniques have the lowest out-of-sample prediction accuracy. The results suggest that the non-linear machine learning methods, especially the ensemble methods, add considerable value to existent credit risk prediction accuracy and enable CDS shadow pricing for companies missing those securities.

Contagion Testing in Embryonic Markets Under Alternative Stressful Us Market Scenarios
R. Mahadeo, Scott M.,Heinlein, Reinhold,Legrenzi, Gabriella Deborah
SSRN
We consolidate alternative ways for identifying stable and stressful scenarios in the S&P 500 market to construct contagion tests for recipient markets vulnerable to disturbances from this source market. The S&P 500 is decomposed into discrete conditions of: (1) Tranquil versus turbulent volatility; (2) Bull versus bear market phases; (3) Normal periods versus asset bubbles and crises. We analyse the relationship between the S&P 500 and major emerging Caribbean stock markets and find that, despite the prominent trade related exposure to the US, financial linkages are much less pronounced than might be expected outside of the Great Recession.

Credit Information Sharing and Loan Default in Developing Countries: The Moderating Effect of Banking Market Concentration and National Governance Quality
Fosu, Samuel,Danso, Albert,Agyei-Boapeah, Henry,Ntim, Collins G.,Adegbite, Emmanuel
SSRN
Departing from the existing literature, which associates credit information sharing with improved access to credit in advanced economies, we examine whether credit information sharing can also reduce loan default rate for banks domiciled in developing countries. Using a large dataset covering 879 unique banks from 87 developing countries from every continent, over a nine-year period (i.e., over 6,300 observations), we uncover three new findings. First, we find that credit information sharing reduces loan default rate. Second, we show that the relationship between credit information sharing and loan default rate is conditional on banking market concentration. Third, our findings suggest that governance quality at the country level does not have a strong moderating role on the effect of credit information sharing on loan default rate.

Cross-Border Currency Exposures
Juvenal, Luciana,Gautam, Deepali,Bénétrix, Agustín S.,Schmitz, Martin
SSRN
This paper provides a dataset on the currency composition of the international investment position for a group of 50 countries for the period 1990-2017. It improves available data based on estimates by incorporating actual data reported by statistical authorities and refining estimation methods. The paper illustrates current and new uses of these data, with particular focus on the evolution of currency exposures of cross-border positions.

Cyber Risk and the U.S. Financial System: A Pre-Mortem Analysis
Eisenbach, Thomas M.,Kovner, Anna,Lee, Michael Junho
SSRN
We model how a cyber attack may be amplified through the U.S. financial system, focusing on the wholesale payments network. We estimate that the impairment of any of the five most active U.S. banks will result in significant spillovers to other banks, with 38 percent of the network affected on average. The impact varies and can be larger on particular days and in geographies with concentrated banking markets. When banks respond to uncertainty by liquidity hoarding, the potential impact in forgone payment activity is dramatic, reaching more than 2.5 times daily GDP. In a reverse stress test, interruptions originating from banks with less than $10 billion in assets are sufficient to impair a significant amount of the system. Additional risk emerges from third-party providers, which connect otherwise unrelated banks.

Debt is Not Free
Moreno Badia, Marialuz,Ohnsorge, Franziska,Gupta, Pranav,Xiang, Yuan
SSRN
With public debt soaring across the world, a growing concern is whether current debt levels are a harbinger of fiscal crises, thereby restricting the policy space in a downturn. The empirical evidence to date is however inconclusive, and the true cost of debt may be overstated if interest rates remain low. To shed light into this debate, this paper re-examines the importance of public debt as a leading indicator of fiscal crises using machine learning techniques to account for complex interactions previously ignored in the literature. We find that public debt is the most important predictor of crises, showing strong non-linearities. Moreover, beyond certain debt levels, the likelihood of crises increases sharply regardless of the interest-growth differential. Our analysis also reveals that the interactions of public debt with inflation and external imbalances can be as important as debt levels. These results, while not necessarily implying causality, show governments should be wary of high public debt even when borrowing costs seem low.

DeepLOB: Deep Convolutional Neural Networks for Limit Order Books
Zihao Zhang,Stefan Zohren,Stephen Roberts
arXiv

We develop a large-scale deep learning model to predict price movements from limit order book (LOB) data of cash equities. The architecture utilises convolutional filters to capture the spatial structure of the limit order books as well as LSTM modules to capture longer time dependencies. The proposed network outperforms all existing state-of-the-art algorithms on the benchmark LOB dataset [1]. In a more realistic setting, we test our model by using one year market quotes from the London Stock Exchange and the model delivers a remarkably stable out-of-sample prediction accuracy for a variety of instruments. Importantly, our model translates well to instruments which were not part of the training set, indicating the model's ability to extract universal features. In order to better understand these features and to go beyond a "black box" model, we perform a sensitivity analysis to understand the rationale behind the model predictions and reveal the components of LOBs that are most relevant. The ability to extract robust features which translate well to other instruments is an important property of our model which has many other applications.



Effects of the institutional change based on democratization on origin and diffusion of technological innovation
Mario Coccia
arXiv

Political systems shape institutions and govern institutional change supporting economic performance, production and diffusion of technological innovation. This study shows, using global data of countries, that institutional change, based on a progressive democratization of countries, is a driving force of inventions, adoption and diffusion of innovations in society. The relation between technological innovation and level of democracy can be explained with following factors: higher economic freedom in society, effective regulation, higher economic and political stability, higher investments in R&D and higher education, good economic governance and higher level of education system for training high-skilled human resources. Overall, then, the positive associations between institutional change, based on a process of democratization, and paths of technological innovation can sustain best practices of political economy for the development of economies in the presence of globalization and geographical expansion of markets.



Exporting Through Intermediaries: Impact on Export Dynamics and Welfare
Kamali, Parisa
SSRN
In many countries, a sizable share of international trade is carried out by intermediaries. While large firms tend to export to foreign markets directly, smaller firms typically export via intermediaries (indirect exporting). I document a set of facts that characterize the dynamic nature of indirect exporting using firm-level data from Vietnam and develop a dynamic trade model with both direct and indirect exporting modes and customer accumulation. The model is calibrated to match the dynamic moments of the data. The calibration yields fixed costs of indirect exporting that are less than a third of those of direct exporting, the variable costs of indirect exporting are twice higher, and demand for the indirectly exported products grows more slowly. Decomposing the gains from indirect and direct exporting, I find that 18 percent of the gains from trade in Vietnam are generated by indirect exporters. Finally, I demonstrate that a dynamic model that excludes the indirect exporting channel will overstate the welfare gains associated with trade liberalization by a factor of two.

Factor Investing in Credit
Henke, Harald,Kaufmann, Hendrik,Messow, Philip,Fang-Klingler, Jieyan
SSRN
This paper investigates the application of factor investing in corporate bonds. Our results show that proficiency in the drivers of risk and return, the factors, should be used for bottom-up corporate bond selection. We analyze five different factors (Value, Equity Momentum, Carry, Quality, Size) and their combinations within the USD investment grade (IG) and high yield (HY) markets. These factors have positive risk-adjusted returns and explain a significant portion of the cross-sectional variation in corporate bond excess returns. We find evidence that factor combinations are superior to single factors in risk-adjusted terms. Multifactor as a signal blending strategy is particularly suitable for active approaches targeting high alpha, while portfolio blending is better aligned with more passive strategies, targeting low turnover and low tracking error.

Firm-Level Data and Monetary Policy: The Case of a Middle Income Country
Bounader, Lahcen,Doukali, Mohamed
SSRN
We test the existence of the balance sheet channel of monetary policy in a middle-income country. Firm-level data scarcity and quality, in such a context, make the identification of this channel a steep challenge. To circumvent this challenge, we use panel instrumental variables estimation with measurement error to analyze the financial statements of 58 500 Moroccan firms over the period 2010-2016. Our analysis confirms the existence of this channel. It shows that monetary policy has a significant impact on small and medium enterprises' access to banks' financing, and that firm-specific variables are key determinants of firms' financing decisions.

Foreign Currency Loans and Credit Risk: Evidence from U.S. Banks
Niepmann, Friederike,Schmidt-Eisenlohr, Tim
SSRN
When firms borrow in foreign currency but collect revenues in local currency, exchange rate changes can affect their ability to repay their debt. Using loan-level data from U.S. banks’ regulatory filings, this paper studies the effect of exchange rate changes on firms’ loan payments. A 10 percent depreciation of the local currency makes a firm with foreign currency debt 69 basis points more likely to become past due on its loans than a firm with local currency debt. This result implies that firms do not perfectly hedge against exchange rate risk and that this risk translates into credit risk for banks. The findings lend support to both the balance sheet channel and the financial channel of exchange rates.

Hidden Treasure: The Impact of Automatic Exchange of Information on Cross-Border Tax Evasion
Beer, Sebastian,Coelho, Maria,Leduc, Seb
SSRN
We analyze the impact of exchange of information in tax matters in reducing international tax evasion between 1995 and 2018. Based on bilateral deposit data for 39 reporting countries and more than 200 counterparty jurisdictions, we find that recent automatic exchange of information frameworks reduced foreign-owned deposits in offshore jurisdictions by an average of 25 percent. This effect is statistically significant and, as expected, much larger than the effect of information exchange upon request, which is not significant. Furthermore, to test the sensitivity of our findings, we estimate countries' offshore status and the impact of information exchange simultaneously using a finite mixture model. The results confirm that automatic (and not upon request) exchange of information impacts cross-border deposits in offshore jurisdictions, which are characterized by low income tax rates and strong financial secrecy.

How Do Banks Interact with Fintech Startups?
Hornuf, Lars,Klus, Milan,Lohwasser, Todor,Schwienbacher, Armin
SSRN
The increasing pervasiveness of technology-driven firms that offer banking services has led to a growing pressure on traditional banks to modernize their core business activities. Many banks tackle the challenges of digitalization by cooperating with startup firms that offer technology-driven financial services (fintechs). In this paper, we examine which banks typically collaborate with fintechs, how intensely they do so, and which form of alliance they prefer. Using hand-collected data covering the largest banks from Canada, France, Germany, and the United Kingdom, we provide detailed evidence on the different forms of alliances occurring in practice. We show that banks are significantly more likely to form alliances with fintechs when they pursue a well-defined digital strategy and/or employ a chief digital officer. Moreover, in line with incomplete contract theory, we find that banks more frequently invest in small fintechs but often build product-related collaborations with larger fintechs.

Inflation and Public Debt Reversals in Advanced Economies
Fukunaga, Ichiro,Komatsuzaki, Takuji,Matsuoka, Hideaki
SSRN
This paper quantitatively assesses the effects of inflation shocks on the public debt-to-GDP ratio in 19 advanced economies using simulation and estimation approaches. The simulations based on the debt dynamics equation and estimations of impulse responses by local projections both suggest that a 1 percentage point shock to inflation rate reduces the debt-to-GDP ratio by about 0.5 to 1 percentage points. The results also suggest that the impact is larger and more persistent when the debt maturity is longer, but the difference from the benchmark case is not significant. These results imply that modestly higher inflation, even if accompanied by some financial repression, could reduce public debt burden only marginally in many advanced economies.

International Equity Portfolio Investment and Enforcement of Insider Trading Laws: A Cross-Country Analysis
Kwabi, Frank,Boateng, Agyenim,Adegbite, Emmanuel
SSRN
In this study, we examine the effects of stringent insider trading laws’ enforcement, institutions and stock market development on international equity portfolio allocation using data from 44 countries over the period 2001-2015. Our results suggest that stringent insider trading laws and their enforcement exert a positive and significant impact on international portfolio investment allocation. Further analysis indicates that the interaction between a country’s institutional quality, stock market development and enforcement of insider trading laws have a positive and significant effect on international equity portfolio allocation. The findings of this study have implications for the design of portfolio investment trading strategies and contribute to the literature on foreign equity investment decisions.

Is the Public Investment Multiplier Higher in Developing Countries? An Empirical Exploration
Izquierdo, Alejandro,Lama, Ruy,Medina, Juan,Puig, Jorge,Riera-Crichton, Daniel,Vegh, Carlos A.,Vuletin, Guillermo Javier
SSRN
Over the last decade, empirical studies analyzing macroeconomic conditions that may affect the size of government spending multipliers have flourished. Yet, in spite of their obvious public policy importance, little is known about public investment multipliers. In particular, the clear theoretical implication that public investment multipliers should be higher (lower) the lower (higher) is the initial stock of public capital has not, to the best of our knowledge, been tested. This paper tackles this empirical challenge and finds robust evidence in favor of the above hypothesis: countries with a low initial stock of public capital (as a proportion of GDP) have significantly higher public investment multipliers than countries with a high initial stock of public capital. This key finding seems robust to the sample (European countries, U.S. states, and Argentine provinces) and to the identification method (Blanchard-Perotti, forecast errors, and instrumental variables). Our results thus suggest that public investment in developing countries would carry high returns.

Knowledge Graphs for Innovation Ecosystems
Alberto Tejero,Victor Rodriguez-Doncel,Ivan Pau
arXiv

Innovation ecosystems can be naturally described as a collection of networked entities, such as experts, institutions, projects, technologies and products. Representing in a machine-readable form these entities and their relations is not entirely attainable, due to the existence of abstract concepts such as knowledge and due to the confidential, non-public nature of this information, but even its partial depiction is of strong interest. The representation of innovation ecosystems incarnated as knowledge graphs would enable the generation of reports with new insights, the execution of advanced data analysis tasks. An ontology to capture the essential entities and relations is presented, as well as the description of data sources, which can be used to populate innovation knowledge graphs. Finally, the application case of the Universidad Politecnica de Madrid is presented, as well as an insight of future applications.



Liquidity Choice and Misallocation of Credit
Ebrahimy, Ehsan
SSRN
This paper studies a novel type of misallocation of credit between investments of varying liquidity. One type of investment is more liquid, i.e., its return is more pledgeable, and the other is more productive. Low liquidities of both investment types imply that the allocation of credit is constrained inefficient and that there is overinvestment in the liquid type. Constrained inefficient equilibria feature non-positive, i.e., one less than or equal the economy's growth rate, and yet too high interest rate, too much investment and too little consumption. Financial development can reduce long-term welfare and output in a constrained inefficient equilibrium if it raises the liquidity of the liquid type. I show a maximum liquid asset ratio or a simple debt tax can achieve constrained efficiency. Introducing government bonds can make Pareto improvement whenever it does not raise the interest rate.

Marked point processes and intensity ratios for limit order book modeling
Ioane Muni Toke,Nakahiro Yoshida
arXiv

This paper extends the analysis of Muni Toke and Yoshida (2020) to the case of marked point processes. We consider multiple marked point processes with intensities defined by three multiplicative components, namely a common baseline intensity, a state-dependent component specific to each process, and a state-dependent component specific to each mark within each process. We show that for specific mark distributions, this model is a combination of the ratio models defined in Muni Toke and Yoshida (2020). We prove convergence results for the quasi-maximum and quasi-Bayesian likelihood estimators of this model and provide numerical illustrations of the asymptotic variances. We use these ratio processes in order to model transactions occuring in a limit order book. Model flexibility allows us to investigate both state-dependency (emphasizing the role of imbalance and spread as significant signals) and clustering. Calibration, model selection and prediction results are reported for high-frequency trading data on multiple stocks traded on Euronext Paris. We show that the marked ratio model outperforms other intensity-based methods (such as "pure" Hawkes-based methods) in predicting the sign and aggressiveness of market orders on financial markets.



Medicare and the Geography of Financial Health
Goldsmith-Pinkham, Paul,Pinkovskiy, Maxim,Wallace, Jacob
SSRN
We use a five percent sample of Americans’ credit bureau data to study the effects of public health insurance on the geography of consumer financial health. Exploiting the nearly universal eligibility for Medicare at age 65, we find a 30 percent reduction in the level of debts in collections with limited effects on other financial outcomes. Medicare reduces the geographic variation in collections by two-thirds at age 65 and halves the geographic correlation between collections and demographics like race and education. Areas that experienced the largest gains in financial health at age 65 had higher shares of black residents, people with disabilities, and for-profit hospitals.

Network Determinants of Cross-Border Merger and Acquisition Decisions
Didier, Tatiana,Herrador, Sebastian,Pinat, Magali
SSRN
This paper assesses whether cross-border M&A decisions exhibit network effects. We estimate exponential random graph models (ERGM) and temporal exponential random graph models (TERGM) to evaluate the determinants of cross-country M&A investments at the sectoral level. The results show that transitivity matters: a country is more likely to invest in a new destination if one of its existing partners has already made some investments there. In line with the literature on export platforms and informational barriers, we find a sizable impact of third country effects on the creation of new investments. This effect is sizable and larger than some of the more traditional M&A determinants, such as trade openness.

On the Drivers of Persistence in Stock Market Volatility in China
Darby, Julia,Zhang, Jinkai
SSRN
We demonstrate that volatility in China’s stock markets tends to be higher and persist for longer than is typical in ‘western markets’, both at the level of composite market indices, and at company level. We provide persuasive arguments and evidence in support of the view that volatility persistence in part reflects the opacity of the information environment the majority of investors operate within. We go on to show that continuing reforms of state ownership and control, along with growth in the proportion of shares held by active institutional investors, look to be promising ways to mitigate the persistence in China’s stock market volatility going forward.

On the Preferences of CoCo Bond Buyers and Sellers: A Logistic Regression Analysis
Caporale, Guglielmo Maria,Kang, Woo-Young
SSRN
This paper estimates the preference scores of CoCo bond buyers and sellers by running logistic regressions taking into account both bond and issuing bank’s characteristics, and also considers the role of countryâˆ'specific CoCo bond market competitiveness. Buyers are defined as having a preference for CoCo bonds if their return-to-risk is higher than the corresponding 25th, 50th and 75th annual percentile values; the preferences of buyers and sellers are assumed to be mutually exclusive. Differences in the degree of risk aversion of buyers and sellers and in the determinants of their preferences are found across percentiles. Further, coupon payment, conversion mechanism, credit rating and P/B ratio appear to be the strongest global determinants of CoCo bond trading between buyers and sellers, these being very responsive to CoCo bond and issuing bank’s characteristics in most European countries, Brazil, Mexico and China (especially in the UK and China).

Post-Crisis Changes in Global Bank Business Models: A New Taxonomy
Caparusso, John,Chen, Yingyuan,Dattels, Peter,Goel, Rohit,Hiebert, Paul
SSRN
The Global Financial Crisis unleashed changes in the operating and regulatory environments for large international banks. This paper proposes a novel taxonomy to identify and track business model evolution for the 30 Global Systemically Important Banks (G-SIBs). Drawing from banks' reporting, it identifies strategies along four dimensions-consolidated lines of business and geographic orientation, and the funding models and legal entity structures of international operations. G-SIBs have adjusted their business models, especially by reducing market intensity. While G-SIBs have maintained international orientation, pressures on funding models and entity structures could affect the efficiency of capital flows through the bank channel.

Risk Management Maturity Assessment at Central Banks
Chamoun, E,Denewet, Nicolas,Manzanera, Antonio,Matai, Sanjeev
SSRN
Effective risk management at central banks is best enabled by a sound framework embedded throughout the organization that supports the design and execution of risk management activities. To evaluate the risk management practices at a central bank, the Safeguards Assessments Division of the IMF's Finance Department developed a tool that facilitates stocktaking of elements that are present and categorizes the function based on its maturity. Tailored recommendations are then provided to the central bank which provide a roadmap to advance the risk management function.

Statistical mechanics of time series
Riccardo Marcaccioli,Giacomo Livan
arXiv

Natural and social multivariate systems are commonly studied through sets of simultaneous and time-spaced measurements of the observables that drive their dynamics, i.e., through sets of time series. Typically, this is done via hypothesis testing: the statistical properties of the empirical time series are tested against those expected under a suitable null hypothesis. This is a very challenging task in complex interacting systems, where statistical stability is often poor due to lack of stationarity and ergodicity. Here, we describe an unsupervised, data-driven framework to perform hypothesis testing in such situations. This consists of a statistical mechanical theory - derived from the Maximum Entropy principle - for ensembles of time series designed to preserve, on average, some of the statistical properties observed on an empirical set of time series. We showcase its possible applications on a set of stock market returns from the NYSE.



Stranded Assets in the Transition to a Carbon-Free Economy
van der Ploeg, Rick,Rezai, Armon
SSRN
Assets in the fossil fuel industries are at risk of losing market value due to anticipated breakthroughs in renewable technology and governments stepping up climate policies in the light of the Paris commitments to limit global warming to 1.5 or 2 degrees Celsius. Stranded assets arise due to uncertainty about the future timing of these two types of events and substantial intertemporal and intersectoral investment adjustment costs. Stranding of assets mostly affects the 20 biggest oil, gas and coal companies who have been responsible for at least a third of global warming since 1965, but also carbon-intensive industries such as steel, aluminium, cement, plastics and greenhouse horticulture. A disorderly transition to the carbon-free economy will lead to stranded assets and legal claims. Institutional investors should be aware of these financial risks. A broader definition of stranded assets also includes countries reliant on fossil fuel exports and workers with technology-specific skills.

The Impact of Margin Changes on Commodity Futures Markets: Evidence From India
Thota, Nagaraju,Shah, Neel
SSRN
Using 14 major commodity (bullion, base metal, agricultural and energy) futures contracts of Multi Commodity Exchange (MCX) from July 2009 to December 2018, we examine the effects of margin changes on commodity futures markets in India. Our empirical results indicate that all commodity futures except Aluminium, Copper and Brent Crude, net margin is maximum for the quartile closet to the maturity. Similarly, volatility of margin imposition is the highest for the quartile closet to maturity. The increasing margin has a negative effect for all non-agricultural futures contracts except Aluminium and Brent Crude. The impact of a margin decrease on volume is weaker compared to a margin increase except for Natural Gas and Crude Oil which show that volume increased on days when margin reduced. On the other hand, both increase and decrease in margins have negative impact on open interest in all the commodity futures contracts.

The Impact of Profit Shifting on Economic Activity and Tax Competition
Klemm, Alexander,Liu, Li
SSRN
A growing empirical literature has documented significant profit shifting activities by multinationals. This paper looks at the impact of such profit shifting on real activity and tax competition. Real activity can be affected as profit shifting changes-and theoretically most likely reduces-the cost of capital. Tax competition, even over real capital, is affected, because a permissive attitude toward profit shifting can be seen as a selective tax reduction for multinationals. Tightening profit shifting rules in turn can affect tax competition through the main rate. This paper discusses these issues theoretically and with the help of a simulation to assess the impact of profit-shifting on investment, revenues, and government behavior. Using the theoretical framework, it also provides a brief overview of the related empirical literature.

The Impact of Stringent Insider Trading Laws and Institutional Quality on the Cost of Capital
Kwabi, Frank,Boateng, Agyenim,Adegbite, Emmanuel
SSRN
This paper examines the effects of interaction between stringent insider trading laws, institutional quality and equity portfolio allocation on the cost of capital. Using a dataset drawn from 44 countries over the period from 2001-2015, we find that stringent insider trading laws interact with institutional quality and foreign equity portfolio allocation to reduce the country-level cost of capital. Further analysis from a quasi-natural experiment based on the 2008-2009 global financial crisis suggests that the findings are robust to endogeneity. Our results imply that the enactment of stringent insider trading laws and their interplay with the quality of institutions are not only important to portfolio investment allocation decisions but reduce the country-level cost of capital.

The Interdependence of Bank Capital and Liquidity
Carletti, Elena,Goldstein, Itay,Leonello, Agnese
SSRN
This paper analyzes the role of liquidity regulation and its interaction with capital requirements. We first introduce costly capital in a bank run model with endogenous bank portfolio choice and run probability, and show that capital regulation is the only way to restore the efficient allocation. We then enrich the model to include fire sales, and show that capital and liquidity regulation are complements. The key implications of our analysis are that the optimal regulatory mix should be designed considering both sides of banks' balance sheet, and that its effectiveness depend on the costs of both capital and liquidity.

The Role of Board Oversight in Central Bank Governance: Key Legal Design Issues
Bossu, Wouter,Rossi, Arthur
SSRN
This paper discusses key legal issues in the design of Board Oversight in central banks. Central banks are complex and sophisticated organizations that are challenging to manage. While most economic literature focuses on decision-making in the context of monetary policy formulation, this paper focuses on the Board oversight of central banks-a central feature of sound governance. This form of oversight is the decision-making responsibility through which an internal body of the central bank-the Oversight Board-ensures that the central bank is well-managed. First, the paper will contextualize the role of Board oversight into the broader legal structure for central bank governance by considering this form of oversight as one of the core decision-making responsibilities of central banks. Secondly, the paper will focus on a number of important legal design issues for Board Oversight, by contrasting the current practices of the IMF membership's 174 central banks with staff's advisory practice developed over the past 50 years.

The Social Enterprise Company in Europe: Policy, Theory and Isomorphism
Liptrap, J S
SSRN
The last decade or so has witnessed a proliferation in the introduction of corporate organisational constructs to facilitate social enterprise across many European jurisdictions. The purpose of this paper is to investigate this phenomenon, and provide an (initial) analytical framework through which the social enterprise company can be understood, both on its own terms and with respect to the traditional business organisation. The paper begins by laying out policymakers’ collective intentions for designing the social enterprise company. From this departure point, the discussion then turns to theorising the social enterprise company’s organisational architecture. The social enterprise company is a hybrid organisational construct, which combines specific legal mechanisms and institutional logics of public, private and social economy organisations together. The social enterprise company is designed to create social value. For this reason it operates according to the principle of publicness. The intention was also for the social enterprise company to be resource flexible and attract altruistic investors and managers. The paper then further extends the theoretical discussion by examining the social enterprise company’s isomorphic prevention mechanisms, which encourage impact fidelity in the context of a conversion or a winding up. The paper concludes with some criticisms and suggestions for improvement.

Toward a Positive Regulatory Enforcement Theory of Financial Reporting
Xue, Wenjie
SSRN
This paper develops a theory of regulatory enforcement in which enforcement and investments are jointly determined by economic fundamentals. Enforcement disciplines misreporting of investment outcomes, which reduces reporting biases as well as market discounts, benefiting entrepreneurship. However, a government is unable to commit to any long-term enforcement policy but discretionarily chooses an enforcement level that is positively associated with the market size. As a result, entrepreneurs collectively have incentives to overinvest to induce excessive enforcement as a public good. However, a large market requires them to coordinately invest more. If the economic environment is not conducive to the coordination, the market can be under-sized and under-regulated.

U.S. Monetary Policy Spillovers to GCC Countries: Do Oil Prices Matter?
Adedeji, Olumuyiwa,Roos, Erik,Shahid, Sohaib,Zhu, Ling
SSRN
This paper provides empirical evidence that the size of the spillovers from U.S. monetarypolicy to non-oil GDP growth in the GCC countries depends on the level of oil prices. Thepotential channels through which oil prices could affect the effectiveness of monetary policyare discussed. We find that the level of oil prices tends to dampen or amplify the growthimpact of changes in U.S. monetary policy on the non-oil economies in the GCC.