Research articles for the 2020-03-02

(Systematic) Investing in Emerging Market Debt
Brooks, Jordan,Richardson, Scott A.,Xu, Zhikai
We extend the analysis of systematic investment approaches to emerging market (EM) fixed income. We focus on hard currency bonds issued by emerging sovereign and quasi-sovereign entities. We find that systematic exposures linked to carry, defensive, momentum and valuation themes are well compensated and lowly correlated in EM markets. A transaction-cost and liquidity aware long-only portfolio generates an Information Ratio above 1. We further show that excess of benchmark returns for a broad set of EM managers are (i) largely explained by passive exposures to EM corporate credit excess returns and EM local currency returns, and (ii) have non-trivial macroeconomic exposures (growth, inflation, volatility and liquidity). A systematic approach to EM debt may be a powerful diversifier.

A Comparison of Global Factor Models
Hanauer, Matthias X.
I compare commonly employed factor models across 47 non-U.S. developed and emerging market countries by ranking them based on their maximum Sharpe ratios. Consistent with the U.S. evidence presented in Barillas, Kan, Robotti, and Shanken (2019), I find that the factor models of Fama and French (2015, 2018), Hou, Xue, and Zhang (2015), and Stambaugh and Yuan (2017) are dominated by a six-factor model that includes cash-based profitability and momentum factors, as well as a value factor that is updated monthly. The result is robust in out-of-sample tests, across subperiods, across global regions, and to methodological changes. The main problem for the dominated factors models is that they do not explain the monthly updated value factor. Hence, I conclude that the value factor is not redundant.

An AGI Modifying Its Utility Function in Violation of the Orthogonality Thesis
James D. Miller,Roman Yampolskiy,Olle Häggström

An artificial general intelligence (AGI) might have an instrumental drive to modify its utility function to improve its ability to cooperate, bargain, promise, threaten, and resist and engage in blackmail. Such an AGI would necessarily have a utility function that was at least partially observable and that was influenced by how other agents chose to interact with it. This instrumental drive would conflict with the orthogonality thesis since the modifications would be influenced by the AGI's intelligence. AGIs in highly competitive environments might converge to having nearly the same utility function, one optimized to favorably influencing other agents through game theory.

Are Frequent Acquirers More Entrenched?
Mishra, Chandra S
We do not find a significant influence of management entrenchment on the firm’s propensity for frequent acquisition, in contrast to the existing studies that show entrenched managers are more likely to become frequent acquirers. We show that entrenched management is less likely to engage in frequent acquisitions because of low strategic managerial ability. Strategic managerial ability is positively associated with the firm’s propensity for frequent acquisition. Entrenched acquirers have lower strategic managerial ability; and lower ability acquirers are more likely to be entrenched. Reducing acquisition frequency exacerbates management entrenchment. Frequent acquisitions further enhance strategic managerial ability, and high-ability management is likely to be more acquisitive. Frequent acquirers are 40 percent less likely to be entrenched compared to non-frequent acquirers. Our results are consistent with the notion that the market for corporate control effectively disciplines frequent acquirers such that their management are less likely to be entrenched. Entrenched acquirers suffer a loss in firm value, which further supports that the market for corporate control is effective in penalizing entrenched management. Frequent acquirers, often being in the market for targets, are disciplined by the market for corporate control. Frequent acquisitions appear to be driven by strategic managerial ability, rather than by management entrenchment.

Ascertaining price formation in cryptocurrency markets with DeepLearning
Fan Fang,Waichung Chung,Carmine Ventre,Michail Basios,Leslie Kanthan,Lingbo Li,Fan Wu

The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world. Unlike traditional markets, such as equities, foreign exchange and commodities, cryptocurrency market is considered to have larger volatility and illiquidity. This paper is inspired by the recent success of using deep learning for stock market prediction. In this work, we analyze and present the characteristics of the cryptocurrency market in a high-frequency setting. In particular, we applied a deep learning approach to predict the direction of the mid-price changes on the upcoming tick. We monitored live tick-level data from $8$ cryptocurrency pairs and applied both statistical and machine learning techniques to provide a live prediction. We reveal that promising results are possible for cryptocurrencies, and in particular, we achieve a consistent $78\%$ accuracy on the prediction of the mid-price movement on live exchange rate of Bitcoins vs US dollars.

Bank Equity Value and Loan Supply
Girotti, Mattia,Horny, Guillaume
We study how bank equity values affect loan supply. We exploit granular balance sheet information on Euro area banks, matched with financial market data. We address endogeneity concerns by considering as an instrument for banks' stock price a shifter derived from each bank's sensitivity to non-financial corporations' equity values. Our results indicate that banks' equity value is positively associated with loan supply to households and firms, and the bank equity stock. These findings suggest that bank managers use stock prices to infer their bank's cost of equity, and increase lending and equity funding when the cost of equity reduces. Overall, this suggests that exogeneous shocks on bank equity values alter the availability of credit for firms and households.

Basis Risk in Variable Annuities
Li, Wenchu,Moenig, Thorsten,Augustyniak, Maciej
Variable annuities (VAs) are highly popular personal savings and investment products with long-term financial guarantees. The hedging of these guarantees is crucial for VA providers, but is complicated by basis risk, i.e. the discrepancy in returns between the underlying mutual fund and suitable hedging instruments. Enhancing fund mapping methods with data analytic techniques for large sets of VA-underlying mutual funds and mapping instruments, we document that --- even under favorable conditions --- over 25% of the volatility of fund returns cannot be eliminated, no matter how sophisticated the hedge. Our findings persist across model specifications, asset classes, and most Lipper Objective Codes.

Behavioral Finance - Asset Prices Predictability, Equity Premium Puzzle, Volatility Puzzle: The Rational Finance Approach
Rachev, Svetlozar T.,Stoyanov, Stoyan V.,Mittnik, Stefan,Fabozzi, Frank J.,Shirvani, Abootaleb
In this paper we address three main objections of behavioral finance to the theory of rational finance, considered as “anomalies” the theory of rational finance cannot explain: (i) Predictability of asset returns; (ii) The Equity Premium; (iii) The Volatility Puzzle. We offer resolutions of those objections within the rational finance. We do not claim that those are the only possible explanations of the “anomalies”, but offer statistical models within the rational theory of finance which can be used without relying on behavioral finance assumptions when searching for explanations of those “anomalies”.

Bond Liquidity Premiums: Evidence from Catastrophe Bonds with Exogenous Default Risk
Herrmann, Markus,Hibbeln, Martin Thomas
In corporate bonds, default risk and liquidity are endogenously linked. Estimating the credit risk premium and the liquidity premium separately remains a major challenge in empirical research. On the contrary, catastrophe bonds are securities where the default risk is strictly exogenous: earthquakes or hurricanes occur in disregard of liquidity. Hence, we are able to identify liquidity effects through observable bid-ask spreads for strictly exogenous default risk. For a TRACE dataset of 3341 dealer-buy and dealer-sell trade pairs from 229 cat bonds, we find a pronounced liquidity premium. Liquidity is high for bonds close to maturity and for low-risk bonds, and liquidity is more strongly priced in high-risk bonds. Almost 20% of the observable yield spread on the cat bond market is attributable to the liquidity premium, with an average liquidity premium of 96 bps.

Bounds on Multi-asset Derivatives via Neural Networks
Luca De Gennaro Aquino,Carole Bernard

Using neural networks, we compute bounds on the prices of multi-asset derivatives given information on prices of related payoffs. As a main example, we focus on European basket options and include information on the prices of other similar options, such as spread options and/or basket options on subindices. We show that, in most cases, adding further constraints gives rise to bounds that are considerably tighter and discuss the maximizing/minimizing copulas achieving such bounds. Our approach follows the literature on constrained optimal transport and, in particular, builds on a recent paper by Eckstein and Kupper (2019, Appl. Math. Optim.).

Can European Electric Utilities Manage Asset Impairments Arising From Net Zero Carbon Targets?
Hickey, Conor,O'Brien, John,Caldecott, Ben,McInerney, Celine M.,O'Gallachoir, Brian
This paper develops methodologies to assess the ability of electric utilities to sustain the forced impairment of carbon emitting power plants and applies those methods to the European market. We present a new method to measure asset impairment, for both the company and the industry, based on a database of power plants. We develop a novel framework to analyse a utility’s ability to transition by investing in renewables through the impact on its credit rating metrics. Finally, we apply our framework to European utilities under scenarios set out by the European Commission to limit global warming by imposing net zero carbon emissions constraints on companies. We conclude that most European utilities have the financial capacity to meet the requirements of net zero carbon emissions under the scenarios with timely action. However, a delay of as little as five years will cause serious financial problems across the sector.

Certainty Equivalent and Utility Indifference Pricing for Incomplete Preferences via Convex Vector Optimization
Birgit Rudloff,Firdevs Ulus

For incomplete preference relations that are represented by multiple priors and/or multiple -- possibly multivariate -- utility functions, we define a certainty equivalent as well as the utility buy and sell prices and indifference price bounds as set-valued functions of the claim. Furthermore, we motivate and introduce the notion of a weak and a strong certainty equivalent. We will show that our definitions contain as special cases some definitions found in the literature so far on complete or special incomplete preferences. We prove monotonicity and convexity properties of utility buy and sell prices that hold in total analogy to the properties of the scalar indifference prices for complete preferences. We show how the (weak and strong) set-valued certainty equivalent as well as the indifference price bounds can be computed or approximated by solving convex vector optimization problems. Numerical examples and their economic interpretations are given for the univariate as well as for the multivariate case.

Cleaner Production in Optimized Multivariate Networks: Operations Management through a Roll of Dice
Amit K Chattopadhyay,Biswajit Debnath,Rihab El-Hassani,Sadhan Kumar Ghosh,Rahul Baidya

The importance of supply chain management in analyzing and later catalyzing economic expectations while simultaneously prioritizing cleaner production aspects is a vital component of modern finance. Such predictions, though, are often known to be less than accurate due to the ubiquitous uncertainty plaguing most business decisions. Starting from a multi-dimensional cost function defining the sustainability of the supply chain (SC) kernel, this article outlines a 4-component SC module - environmental, demand, economic, and social uncertainties - each ranked according to its individual weight. Our mathematical model then assesses the viability of a sustainable business by first ranking the potentially stochastic variables in order of their subjective importance, and then optimizing the cost kernel, defined from a utility function. The model will then identify conditions (as equations) validating the sustainability of a business venture. The ranking is initially obtained from an Analytical Hierarchical Process; the resultant weighted cost function is then optimized to analyze the impact of market uncertainty based on our supply chain model. Model predictions are then ratified against SME data to emphasize the importance of cleaner production in business strategies.

Complete and competitive financial markets in a complex world
Gianluca Cassese

We investigate the possibility of completing financial markets in a model with no exogenous probability measure and market imperfections. A necessary and sufficient condition is obtained for such extension to be possible.

Continuum and thermodynamic limits for a simple random-exchange model
Bertram Düring,Nicos Georgiou,Sara Merino-Aceituno,Enrico Scalas

We discuss various limits of a simple random exchange model that can be used for the distribution of wealth. We start from a discrete state space - discrete time version of this model and, under suitable scaling, we show its functional convergence to a continuous space - discrete time model. Then, we show a thermodynamic limit of the empirical distribution to the solution of a kinetic equation of Boltzmann type. We solve this equation and we show that the solutions coincide with the appropriate limits of the invariant measure for the Markov chain. In this way we complete Boltzmann's program of deriving kinetic equations from random dynamics for this simple model. Three families of invariant measures for the mean field limit are discovered and we show that only two of those families can be obtained as limits of the discrete system and the third is extraneous. Finally, we cast our results in the framework of integer partitions and strengthen some results already available in the literature.

Crypto Wash Trading
Cong, Lin William,Li, Xi,Tang, Ke,Yang, Yang
We investigate whether centralized exchanges in the cryptocurrency markets engage in wash trading. To identify wash trades, we device a set of tests and algorithms to examine patterns in the first significant digits of orders, trade sizes, behavioral regularities, etc., for 3 regulated crypto exchanges and 26 unregulated ones classified by their compliance status. All regulated exchanges feature trades consistent with traditional financial markets and statistical benchmarks. However, the majority of unregulated exchanges exhibit anomalous activities compared to regulated exchanges and statistical benchmarks. The patterns cannot be explained by investor activities but suggest that unregulated exchanges, especially those that are less prominent, are engaged in wash trading. We discuss regulatory implications of such manipulative behaviors in the emerging crypto sector and in financial markets in general.

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

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

Deep Learning for Asset Bubbles Detection
Bashchenko, Oksana,Marchal, Alexis
We develop a methodology for detecting asset bubbles using a neural network. We rely on the theory of local martingales in continuous-time and use a deep network to estimate the diffusion coefficient of the price process more accurately than the current estimator, obtaining an improved detection of bubbles. We show the outperformance of our algorithm over the existing statistical method in a laboratory created with simulated data. We then apply the network classification to real data and build a zero net exposure trading strategy that exploits the risky arbitrage emanating from the presence of bubbles in the US equity market from 2006 to 2008. The profitability of the strategy provides an estimation of the economical magnitude of bubbles as well as support for the theoretical assumptions relied on.

Determinants of Short-Term Corporate Yield Spreads: Evidence from the Commercial Paper Market
Huang, Jing-Zhi,Liu, Bibo,Shi, Zhan
What drives short-term credit spreads is a crucial but controversial question in credit markets, yet the empirical literature on the determinants of such spreads is rather thin perhaps due to data limitations. Using a unique data set of secondary market transaction prices of Chinese commercial papers, this paper provides a comprehensive study on the determinants of short-term credit spreads within the structural framework of credit risk modeling. Specifically, we propose a model of risky debt pricing with rollover risk, jump risk, and market illiquidity. Among other things, this model allows us to decompose commercial paper yield spreads into a credit component and a liquidity component in a unified manner. We find that both credit and liquidity factors are important determinants of short-term corporate yield spreads and that on average, the proposed structural model can largely match levels of commercial paper spreads in our sample. Especially, our decomposition results indicate that jump risk and market liquidity make equally important contributions to the spreads on commercial papers.

Determination of Latent Dimensionality in International Trade Flow
Duc P. Truong,Erik Skau,Vladimir I. Valtchinov,Boian S. Alexandrov

Currently, high-dimensional data is ubiquitous in data science, which necessitates the development of techniques to decompose and interpret such multidimensional (aka tensor) datasets. Finding a low dimensional representation of the data, that is, its inherent structure, is one of the approaches that can serve to understand the dynamics of low dimensional latent features hidden in the data. Nonnegative RESCAL is one such technique, particularly well suited to analyze self-relational data, such as dynamic networks found in international trade flows. Nonnegative RESCAL computes a low dimensional tensor representation by finding the latent space containing multiple modalities. Estimating the dimensionality of this latent space is crucial for extracting meaningful latent features. Here, to determine the dimensionality of the latent space with nonnegative RESCAL, we propose a latent dimension determination method which is based on clustering of the solutions of multiple realizations of nonnegative RESCAL decompositions. We demonstrate the performance of our model selection method on synthetic data and then we apply our method to decompose a network of international trade flows data from International Monetary Fund and validate the resulting features against empirical facts from economic literature.

Do Firms Seek a Target Board Structure? Evidence from the Post-SOX Period
Chung, Chune Young,Liu, Chang,Paul, Donna L.
We investigate whether firms restructure board composition to align with changes in their contracting environment. Board size and independence increase with firm complexity, consistent with theoretical predictions. However, the hypothesized negative relationship between board independence and information costs is evident only for firms completing acquisitions. Furthermore, board independence increases to offset increases in CEO power in a sample of firms making acquisitions, but decreases when CEO power increases in a large cross-section of firms. We conclude that after the Sarbanes-Oxley Act of 2002, firms face constraints adjusting to target board structure, but these constraints can be mitigated by a shock to the contracting environment via acquisition.

Dynamic Beveridge Curve Accounting
Hie Joo Ahn,Leland D. Crane

We develop a dynamic decomposition of the empirical Beveridge curve, i.e., the level of vacancies conditional on unemployment. Using a standard model, we show that three factors can shift the Beveridge curve: reduced-form matching efficiency, changes in the job separation rate, and out-of-steady-state dynamics. We find that the shift in the Beveridge curve during and after the Great Recession was due to all three factors, and each factor taken separately had a large effect. Comparing the pre-2010 period to the post-2010 period, a fall in matching efficiency and out-of-steady-state dynamics both pushed the curve upward, while the changes in the separation rate pushed the curve downward. The net effect was the observed upward shift in vacancies given unemployment. In previous recessions changes in matching efficiency were relatively unimportant, while dynamics and the separation rate had more impact. Thus, the unusual feature of the Great Recession was the deterioration in matching efficiency, while separations and dynamics have played significant, partially offsetting roles in most downturns. The importance of these latter two margins contrasts with much of the literature, which abstracts from one or both of them. We show that these factors affect the slope of the empirical Beveridge curve, an important quantity in recent welfare analyses estimating the natural rate of unemployment.

Employee Representation and the Risk of Corporate Pension Plans
Heusel, Nicola
We analyze the effect of direct labour representation in supervisory boards on the risk of corporate pension plans.We exploit employee representation requirements mandated by German labour law and find that firms with parity employee representation reduce pension plan risk both in terms of funding as well as in terms of investment risk.

Enhanced Portfolio Optimization
Pedersen, Lasse Heje,Babu, Abhilash,Levine, Ari
We show how to identify the portfolios that cause problems in standard mean-variance optimization (MVO) and develop an enhanced portfolio optimization (EPO) method that addresses the problems. The EPO solution encompasses existing methods such as standard MVO, reverse-MVO, a Bayesian estimator, Black-Litterman, robust optimization, a form of generalized ridge regression used in machine learning, and random matrix theory. Nevertheless, the closed-form EPO is extremely simple. Applying EPO on several realistic datasets, we find significant gains relative to standard benchmarks. In equities, EPO significantly outperforms the market, the 1/N portfolio, and standard asset pricing factors. Similarly in global asset allocation, EPO delivers economically significant increases in the Sharpe ratio and statistically significant alpha to standard time series momentum strategies and other benchmarks.

Entrepreneurial Behavior and Intentions among Bumiputera's Students
Othman, Norasmah ,Asiar, Rafiza Mohd
Objective - Unemployment and marketability among graduates are the country's current issues. This became clear when the unemployment percentage among graduates continued to increase yearly. Therefore, entrepreneurship education has been chosen as an alternative solution. However, currently, student involvement in entrepreneurship is still low. As low involvement occurs among students, especially those in private colleges, students may lack entrepreneurial behavior and intentions. Therefore, this study aims to identify the level of the entrepreneurial behavior and intentions among Bumiputra's students studying in Kuala Lumpur's private colleges.Methodology/Technique - A total of 387 students participated in a quantitative survey. Using a questionnaire as the study's research instrument, the data were analyzed using SPSS version 22.0.Finding - The findings showed that the entrepreneurial behavior and intentions among students are at a moderate level. Pearson correlation coefficients indicated a significantly positive, although moderate, relationship between entrepreneurial behavior and entrepreneurial intentions. The result suggests that to increase the number of entrepreneurs among students in Malaysia, all stakeholders should be involved in inculcating an entrepreneurial culture.Novelty - An innovative and practical-based entrepreneurship curriculum should be developed to encourage students to choose entrepreneurship as a career option upon graduation.Type of Paper - Empirical.

Equilibrium Model of Limit Order Books: A Mean-field Game View
Jin Ma,Eunjung Noh

In this paper we study a continuous time equilibrium model of limit order book (LOB) in which the liquidity dynamics follows a non-local, reflected mean-field stochastic differential equation (SDE) with evolving intensity. Generalizing the basic idea of Ma et al. (2015), we argue that the frontier of the LOB (e.g., the best asking price) is the value function of a mean-field stochastic control problem, as the limiting version of a Bertrand-type competition among the liquidity providers. With a detailed analysis on the $N$-seller static Bertrand game, we formulate a continuous time limiting mean-field control problem of the representative seller. We then validate the dynamic programming principle (DPP), and show that the value function is a viscosity solution of the corresponding Hamilton-Jacobi-Bellman (HJB) equation. We argue that the value function can be used to obtain the equilibrium density function of the LOB, following the idea of Ma et al. (2015).

Facilitating a Win-Win Between Corporate Financial Performance and Corporate Social Responsibility
Miller, Steve,Qiu, Bin,Wang, Bin,Yang, Tina
The societal demand for sustainable investment â€" an investment approach that considers environmental, social, and governance (ESG) factors â€" has grown exponentially. However, academic research has failed to provide theoretical and empirical guidance for a positive relation between ESG and corporate financial performance (CFP). We propose and test a conceptual framework that identifies the attributes of stakeholders who likely facilitate a positive ESG-CFP relation. We focus on the “E” component of ESG for a more stringent test and argue that local institutional investors (LIIs) possess the attributes to facilitate a positive relation between CFP and corporate environmental performance. The findings are consistent with our hypothesis and are robust to endogeneity concerns. We also find that LIIs add value through the monitoring channel and the consulting channel.

Financial Contagion and the Wealth Effect: An Experimental Study
Bayona, Anna,Peia, Oana
We design a laboratory experiment to test the importance of wealth as a channel for financial contagion across markets with unrelated fundamentals. Specifically, in a sequential global game, we analyze the decisions of a group of investors that hold assets in two markets. We consider two treatments that vary the level of diversification of these assets across markets, which allows us to disentangle the wealth effect from other sources of financial contagion. We provide evidence of contagion due to a wealth effect when investors have completely diversified portfolios. In this treatment, for certain ranges of fundamentals, we show that a coordination failure in the first market reduces investors’ wealth, which makes them more likely to withdraw their investments in the second market, thereby increasing the probability of a crisis.

Financial Inclusion and Achievements of Sustainable Development Goals (SDGs) in ASEAN
Ma’ruf, Ahmad ,Aryani, Febriyana
Objective - Financial Inclusion is an essential agenda at the ASEAN level. Increasing financial inclusion aims to develop the economic capacity of the population to reduce poverty and encourage income distribution. This study aims to analyze the relationship of financial inclusion to the achievement of Sustainable Development Goals (SDGs) in the aspect of poverty alleviation in ASEAN.Methodology/Technique - This study uses a quantitative approach. The data used is secondary data in the period between 2010 and 2018. Data processing uses multiple regression. The financial inclusion dimensions analyzed are the socioeconomic dimension and the infrastructure dimension.Findings - Financial Inclusion has a negative and significant relationship with the achievement of sustainable development goals (SGDs) in the aspect of poverty alleviation in ASEAN.Novelty - The statement that the development of countries in ASEAN to realize SDGs on poverty eradication becomes very important. This study is essential for policymakers regarding poverty alleviation and financial inclusion development. This study contributes to the financial inclusion literature in ASEAN with an emphasis on the socioeconomic dimension.Type of Paper - Empirical.

Financial Liberalization in East Asia: Lessons from Financial Crises and the Chinese Experience of Controlled Liberalization
Wang, Jiangyu
This paper studies the experiences of East Asian countries in conducting financial liberalization. Financial liberalization has two components, which are capital account liberalization and financial services liberalization. It is important to stress that the two components should not be confused, so are their respective consequences on a country's economic growth and financial stability. Both the theoretical and empirical studies have established that premature capital account liberalization was the direct cause of various financial crises, including the 1997-98 Asian Crisis. It is highly advisable that countries delay capital account liberalization or maintain capital controls before they put into place effective domestic regulatory framework and financial infrastructure. Based on the experiences of Malaysia and China in managing the Asian crisis, the paper argues that, in addition to having appropriately sequenced, gradualist reforms on capital account liberalization, a country should keep certain regulatory space for itself and maintain independently the financial policy-making power. However, financial services liberalization should not be retarded by these factors. An analysis of the four modes of GATT's services supplies suggests that trade in financial services does not necessarily involve massive capital flows and that financial services liberalization does not require abandonment of capital controls. Financial services liberalization improves the capabilities of a country's financial sector, enhances efficient capital reallocation, and brings tremendous benefits to consumers. Moreover, unlike capital account liberalization, trade liberalization in financial services will not contribute to financial instability and crises. The paper surveys the liberalization measures of financial services in selected Asian countries and concludes that more broad-based liberalization should be promoted. The paper argues that, however, it is understandable that a country wishes to provide certain protection to its domestic financial services sector at the initial stage of its development. After all, no country is born with a strong financial industry. However, the government providing protection should be wise enough to know at which point the protection should be terminated. In this regard, Singapore's experience of developing into a leading international financial center is an illustrating example.

Financial replicator dynamics: emergence of systemic-risk-averting strategies
Indrajit Saha,Veeraruna Kavitha

We consider a random financial network with a large number of agents. The agents connect through credit instruments borrowed from each other or through direct lending, and these create the liabilities. The settlement of the debts of various agents at the end of the contract period can be expressed as solutions of random fixed point equations. Our first step is to derive these solutions (asymptotically), using a recent result on random fixed point equations. We consider a large population in which agents adapt one of the two available strategies, risky or risk-free investments, with an aim to maximize their expected returns (or surplus). We aim to study the emerging strategies when different types of replicator dynamics capture inter-agent interactions. We theoretically reduced the analysis of the complex system to that of an appropriate ordinary differential equation (ODE). We proved that the equilibrium strategies converge almost surely to that of an attractor of the ODE. We also derived the conditions under which a mixed evolutionary stable strategy (ESS) emerges; in these scenarios the replicator dynamics converges to an equilibrium at which the expected returns of both the populations are equal. Further the average dynamics (choices based on large observation sample) always averts systemic risk events (events with large fraction of defaults). We verified through Monte Carlo simulations that the equilibrium suggested by the ODE method indeed represents the limit of the dynamics.

Hedge Funds as International Liquidity Providers: Evidence from Convertible Bond Arbitrage in Canada
Gatev, Evan,Li, Mingxin
We examine the impact of Canadian convertible bond issuance on equity market liquidity. Using issuance event dates between April 2002 and March 2011, we analyze the change in short interest and stock liquidity during a 1-year event window. We consider mainstream liquidity measures, including turnover, dollar volume, dollar spread, percentage spread, and the ratio of daily absolute stock return to dollar volume. We find that after convertible bond issuances, there are significant increases in short interest, but minimal overall improvements in liquidity. The change in liquidity is not significantly related to the change in short interest, except for the firms with large change in short interest. Interpreting increased short interest after issuance as a proxy for convertible bond arbitrage activity, the results suggest that there is limited positive liquidity externality of hedge fund activity in Canada.

Hedging Non-Tradable Risks with Transaction Costs and Price Impact
Alvaro Cartea,Ryan Donnelly,Sebastian Jaimungal

A risk-averse agent hedges her exposure to a non-tradable risk factor $U$ using a correlated traded asset $S$ and accounts for the impact of her trades on both factors. The effect of the agent's trades on $U$ is referred to as cross-impact. By solving the agent's stochastic control problem, we obtain a closed-form expression for the optimal strategy when the agent holds a linear position in $U$. When the exposure to the non-tradable risk factor $\psi(U_T)$ is non-linear, we provide an approximation to the optimal strategy in closed-form, and prove that the value function is correctly approximated by this strategy when cross-impact and risk-aversion are small. We further prove that when $\psi(U_T)$ is non-linear, the approximate optimal strategy can be written in terms of the optimal strategy for a linear exposure with the size of the position changing dynamically according to the exposure's "Delta" under a particular probability measure.

Illiquidity and the Cross-Section of International Stock Returns
Cakici, Nusret,Zaremba, Adam
We perform a comprehensive investigation of the illiquidity premium in international stock markets. We examine several established liquidity measures in 23 developed countries for the years 1991â€"2019. The evidence for the premium is fragile, limited to certain global regions, and dependent on measurement approaches and methodological choices. Most importantly, the out-performance of illiquid stocks is driven by the smallest firms in the market with negligible economic significance. Outside the micro-cap universe, virtually no cross-sectional return pattern related to liquidity is observed.

Illiquidity and the Cross-Section of Stock Returns in Emerging Markets
Cakici, Nusret,Zaremba, Adam
We comprehensively examine the illiquidity premium in emerging stock markets. Using several different liquidity proxies, we study the performance of firms from 23 countries for the years 1994 to 2019. Contrary to a widely held belief, we demonstrate that the illiquidity premium in emerging markets is weak, varies across geographical regions, and strongly depends on the liquidity measures and testing methods employed. In particular, the effect of illiquidity in the cross-section of stock returns is largely driven by microcaps with no meaningful economic importance. Outside the universe of the smallest firms, the illiquidity premium can hardly be detected.

Large-Maturity Smiles for an Affine Jump-Diffusion Model
Nian Yao,Zhiqiu Li,Zhichao Ling,Junfeng Lin

In this paper, we study the asymptotic behaviors of implied volatility of an affine jump-diffusion model. Let log stock price under risk-neutral measure follow an affine jump-diffusion model, we show that an explicit form of moment generating function for log stock price can be obtained by solving a set of ordinary differential equations. A large-time large deviation principle for log stock price is derived by applying the G\"{a}rtner-Ellis theorem. We characterize the asymptotic behaviors of the implied volatility in the large-maturity and large-strike regime using rate function in the large deviation principle. The asymptotics of the Black-Scholes implied volatility for fixed-maturity, large-strike and fixed-maturity, small-strike regimes are studied. Numerical results are provided to validate the theoretical work.

Learning to Deal With Repeated Shocks Under Strategic Complementarity: An Experiment
Bulutay, Muhammed,Cornand, Camille,Zylbersztejn, Adam
Experimental evidence shows that the rational expectations hypothesis fails to characterize the path to equilibrium after an exogenous shock when actions are strategic complements. Under identical shocks, however, repetition allows adaptive learning, so that inertia in adjustment should fade away with experience. If this finding proves to be robust, inertia in adjustment may be irrelevant among experienced agents. The conjecture in the literature is that inertia would still persist, perhaps indefinitely, in the presence of real-world complications such as nonidentical shocks. Herein, we empirically test the conjecture that the inertia in adjustment is more persistent if the shocks are nonidentical. For both identical and nonidentical shocks, we find persistent inertia and similar patterns of adjustment that can be explained by backward-looking expectation rules. A reformulation of naive expectations with similarity-based learning approach is found to have a higher predictive power than rational and trend-following rules.

Machine Learning Portfolio Allocation
Michael Pinelis,David Ruppert

We find economically and statistically significant gains from using machine learning to dynamically allocate between the market index and the risk-free asset. We model the market price of risk to determine the optimal weights in the portfolio: reward-risk market timing. This involves forecasting the direction of next month's excess return, which gives the reward, and constructing a dynamic volatility estimator that is optimized with a machine learning model, which gives the risk. Reward-risk timing with machine learning provides substantial improvements in investor utility, alphas, Sharpe ratios, and maximum drawdowns, after accounting for transaction costs, leverage constraints, and on a new out-of-sample test set. This paper provides a unifying framework for machine learning applied to both return- and volatility-timing.

Macro-Financial Spillovers
Cotter, John,Hallam, Mark,Yilmaz, Kamil
We analyse spillovers between the real and financial sides of the US economy allowing for differences in sampling frequency between financial and macroeconomic data. We show that financial markets are typically net transmitters of shocks to the real side of the economy, particularly during turbulent market conditions. Our macro-financial spillover measures are found to have significant predictive ability for future US macroeconomic conditions in both in-sample and out-of-sample forecasting en- vironments. Furthermore, the predictive ability of our macro-financial measures frequently exceeds that of purely financial systemic risk measures previously employed in the literature for the same task.

Multi-market Trading and Liquidity: Evidence from Cross-listed Companies
Atanasova, Christina V.,Li, Mingxin
We examine the relationship between stock liquidity and the difference in domestic and foreign market prices for a sample of 650 international firms cross-listed on a U.S. stock exchange through either an American Depository Receipt (ADR) or an ordinary shares program. We exploit the 2001 change to decimalization pricing and the 2003 U.S. dividend tax cut as quasi natural experiments and find that ADR liquidity decreases the absolute value of the ADR premium. We document a positive relationship between liquidity and price discovery as well as a liquidity effect on the price convergence between the ADRs and their underlying shares. The effect of liquidity on convergence is stronger for stocks with high holding costs and low institutional ownership.

Omnigraph: Rich Representation and Graph Kernel Learning
Xie, Boyi,Passonneau, Rebecca
OmniGraph, a novel representation to support a range of NLP classification tasks, integrates lexical items, syntactic dependencies and frame semantic parses into graphs. Feature engineering is folded into the learning through convolution graph kernel learning to explore different extents of the graph. A high-dimensional space of features includes individual nodes to complex networks. In experiments on a text-forecasting problem that predicts stock price change from news for company mentions, OmniGraph beats several benchmarks based on bag-of-words, syntactic dependencies, and semantic trees. The highly expressive features OmniGraph discovers provide insights into the semantics across distinct market sectors. To demonstrate the method’s generality, we also report its high performance results on a fine-grained sentiment corpus.

On the Inflation Risks Embedded in Sovereign Bond Yields: A Revisit
Camba-Mendez, Gonzalo
We revisit the concept of the cost of hedging inflation risks put forward in Bodie (1976). When doing so, we employ a time-varying vector autoregressive model to describe the dynamics of asset returns. We estimate this model by means of the kernel-based methods discussed in \cite{gir2018}, but relying on the estimation approach put forward in \cite{mor1978}, which enforces the stability of the estimated VAR. Our modelling framework allows to disentangle the time-varying compensation for expected and unexpected inflation shocks embedded in the sovereign bond yields of Germany, France, Japan and the United States. Our empirical results suggest that the current environment of very low nominal sovereign bond yields, is a reflection of a low real risk-free rate, low inflation expectations and a low cost for hedging inflation risks. We have not encountered similar past episodes in the sample under study. We have tentatively searched for a similar pattern in episodes characterised by recessionary phases of the business cycle coupled with low inflation expectations. However, we failed to robustly associate those episodes with either low real risk-free rates, or with low costs for hedging inflation risks.

Optimal Iterative Threshold-Kernel Estimation of Jump Diffusion Processes
José E. Figueroa-López,Cheng Li,Jeffrey Nisen

In this paper, we propose a new threshold-kernel jump-detection method for jump-diffusion processes, which iteratively applies thresholding and kernel methods in an approximately optimal way to achieve improved finite-sample performance. We use the expected number of jump misclassifications as the objective function to optimally select the threshold parameter of the jump detection scheme. We prove that the objective function is quasi-convex and obtain a new second-order infill approximation of the optimal threshold in closed form. The approximate optimal threshold depends not only on the spot volatility, but also the jump intensity and the value of the jump density at the origin. Estimation methods for these quantities are then developed, where the spot volatility is estimated by a kernel estimator with thresholding and the value of the jump density at the origin is estimated by a density kernel estimator applied to those increments deemed to contain jumps by the chosen thresholding criterion. Due to the interdependency between the model parameters and the approximate optimal estimators built to estimate them, a type of iterative fixed-point algorithm is developed to implement them. Simulation studies for a prototypical stochastic volatility model show that it is not only feasible to implement the higher-order local optimal threshold scheme but also that this is superior to those based only on the first order approximation and/or on average values of the parameters over the estimation time period.

Option Spreads and the Uncertain Cost of Equity Liquidity: Evidence from the Knight Capital Trading Glitch
Kapadia, Nikunj,Linn, Matthew
High frequency liquidity provision in equity markets accompanied by low latency quote volatility results in uncertainty with respect to the execution of a marketable order. We show that such quote volatility increases trading costs of participants in the market of the option on the underlying equity because of a negative externality. Uninformed liquidity traders in option markets face higher adverse selection costs than their counterparts in equity markets. To show the causal impact of the underlying equity's liquidity on option spreads, we consider an incident where a large broker dealer erroneously executed millions of small orders in the stock market. While the glitch increases uninformed order flow, it also results in persistent liquidity-related uncertainty. We show that option spreads widen among impacted stocks and remained wide for a quarter of an hour after the broker dealer fixed the glitch in their computer system. Trading costs of option market participants increase by 18-24% relative to trading costs in the underlying stock.

Personal Financial Incentives and Corporate Campaign Contributions
Fedaseyeu, Viktar,Lvovskiy, Lev
Despite the well-documented benefits of political participation, few firms engage in politics. We argue that low levels of corporate political participation can be rationalized by financial incentives of employees and shareholders who are the ultimate source of corporate contributions. Since even large firm-level benefits are trivial for individuals with small equity-stakes, few people have sufficient incentives to contribute. This logic explains why corporate political contributions are relatively small and why firms seek alternative channels of political influence. Empirically, we document that corporate PACs are financially constrained and that financial incentives of individual contributors are a strong determinant of campaign contributions.

Private Debt Renegotiation and Financial Institutions’ Network
Godlewski, Christophe J.,Sanditov, Bulat
We study the influence of financial institutions’ network on private debt renegotiation outside of distress. Lenders with a network-central position have access to superior private information, are more experienced and trustworthy and have a greater reputational capital. Using a large sample of more than 10.000 loans issued in 25 European countries we find that network-central lenders have a significant influence on the renegotiation process. Such lenders increase the likelihood of renegotiation, the number of renegotiation rounds, and the number of amendments to the loan agreement. Our findings survive multiple robustness checks and confirm that access to superior information, greater experience, reputation, and trust encourages private debt renegotiation.

Secured Credit Spreads
Benmelech, Efraim,Kumar, Nitish,Rajan, Raghuram G.
Lenders are unwilling to accept lower credit spreads for secured debt relative to unsecured debt when a firm is healthy. However, they accept significantly lower credit spreads for secured debt when a firm’s credit quality deteriorates, the economy slows, or average credit spreads widen. This contingent valuation of collateral or security, coupled with the borrower perceiving a loss of operational and financial flexibility when issuing secured debt, may explain why firms issue secured debt on a contingent basis; they issue more when their credit quality deteriorates, the economy slows, and average credit spreads widen.

Stress Testing for Commercial, Investment and Custody Banks
Cope, Daniel Patrick,Hsu, Carey,Lively, Clinton,Morgan, James,Schuermann, Til,Sekeris, Evangelos
In this chapter we describe stress testing at banks covering the major products and businesses in which banks engage. This includes commercial and retail lending, capital markets (investment banking, sales and trading), and trust and custody. We cover loss and net income modeling and thus balance sheet and P&L (income statement) evolution, including noninterest expense items in the form of operational losses.

Technological interdependencies predict innovation dynamics
Anton Pichler,François Lafond,J. Doyne Farmer

We propose a simple model where the innovation rate of a technological domain depends on the innovation rate of the technological domains it relies on. Using data on US patents from 1836 to 2017, we make out-of-sample predictions and find that the predictability of innovation rates can be boosted substantially when network effects are taken into account. In the case where a technology$'$s neighborhood future innovation rates are known, the average predictability gain is 28$\%$ compared to simpler time series model which do not incorporate network effects. Even when nothing is known about the future, we find positive average predictability gains of 20$\%$. The results have important policy implications, suggesting that the effective support of a given technology must take into account the technological ecosystem surrounding the targeted technology.

The Collateral Channel of Monetary Policy: Evidence from China
Fang, Hanming,Wang, Yongqin,Wu, Xian
Collateral-based monetary policy tools have been used extensively by major central banks. Lack of proper policy counterfactuals, however, makes it difficult to empirically identify their causal effects on the financial market and the real economy. We exploit a quasi-natural experiment in China, where dual-listed bonds are traded in two mostly segmented markets: the interbank market regulated by the Central Bank, and the exchange market regulated by the securities regulator. During a policy shift in our study period, China's Central Bank included a class of previously ineligible bonds in the interbank market to become eligible collateral for financial institutions to borrow money from its Medium-Term Lending Facility (MLF). This policy shift allows us to implement a triple-difference strategy to estimate the causal impact of the collateral-based unconventional monetary policy. We find that in the secondary market the policy reduced the spreads of the newly collateralizable bonds in the treatment market (the interbank market) by 42-62 basis points. We also find that there is a pass-through effect from the secondary market to the primary market: the spreads of the treated bonds newly issued in the interbank market were reduced by 54 basis points.

The Data Reporting Challenge: U.S. Swap Data Reporting and Financial Market Infrastructure
Berner, Richard,Doyle, Robin,Lamar, Kenneth
This chapter describes the past and present regulatory reporting landscape for U.S. swap data and financial market infrastructures (FMIs). It argues that standards are essential to ensure that both the data and the technology supporting the reporting process are fit for purpose and are dynamic enough that changing data needs are available quickly in times of stress. It contends that U.S. regulators must accelerate their work to harmonize U.S. reporting requirements at home and work with those abroad to align them globally. The chapter builds on the lessons learned from current swap and FMI data reporting regimes to inform the rethinking of financial reporting generally and the process of financial regulation to make them more effective and efficient. To realize those goals, regulators and industry must learn to rely on data rather than reports and must collaborate to align their use of these data and standardize them to make them interoperable.

The Determinants and Effects of Board Committees
Lee, Wei-Ming
The governance reforms of 2003 require corporate boards to set up various committees. This paper studies how these committees are structured and their impacts. I find that independent directors with long tenures and multiple board seats tend to multitask and sit on more committees. Firms that multitask their independent directors are associated with lower CEO compensation and higher ROA. These results support the hypothesis that firms structure their committees to utilize the expertise of the independent directors. I contribute to the literature by showing that board performance depends not only on directors' identity, but also on their task assignment.

The Fundamental Relation Between Firm Market and Accounting Values Is a Multiplicative Power Law
Lubberink, Martien Jan Peter,Willett, Roger J.
We provide a solution that may offer closure to the question of how to best measure the empirical relation between stock market values and accounting numbers. The models that dominate studies of the relevance of accounting numbers produce coefficient estimates that are hard to interpret and exhibit high volatility. We present a theory that demonstrates a multiplicative power law describes the long-run relation between market values and ac-counting values. Consequently, the correct forms for estimating the most basic market-accounting relations are log-linear and the relevant response coefficients are elasticities. We estimate these elasticities for the years 1971-2016, comparing them to response coefficients of traditional, additive-linear models that relate market and accounting values. Our results demonstrate the superiority of using elasticities to measure the empirical relation between market values and accounting numbers.

The Impact of Air Pollution on Attributable Risks and Economic Costs of Hospitalization for Mental Disorders
Wu, Ziting,Chen, Xi,Li, Guoxing,Tian, Lin,Wang, Zhan,Xiong, Xiuqin,Yang, Chuan,zhou, zijun,Pan, Xiaochuan
This study aims to fill the gap in our understanding about exposure to particulate matters with diameter less than 2.5 μm (PM2.5) and attributable risks and economic costs of mental disorders (MDs). We identify the relationship between PM2.5 and risk of hospital admissions (HAs) for MDs in Beijing and measure the attributable risk and economic cost. We apply a generalized additive model (GAM) with controls for time trend, meteorological conditions, holidays and day of the week. Stratified analyses are performed by age, gender and season.We further estimate health and economic burden of HAs for MDs attributable to PM2.5. A total of 17,252 HAs for MDs are collected. We show that PM2.5 accounts for substantial morbidity and economic burden of MDs. Specifically, a 10 μg/m3 daily increase in PM2.5 is associated with a 3.55% increase in the risk of HAs for MDs, and the effect is more pronounced for older males in colder weather. According to the WHO's air quality guidelines, 15.12 percent of HAs and 16.19 percent of related medical expenses for MDs are respectively attributable to PM2.5.

The Influence of Growth, Asset Tangibility, Cost of Debt, Profitability and Business Risk on Debt Capital
Arilyn, Erika Jimena,, Beny
Objective - The aims to identify the significant factors that influence a company's decision to use debt capital.Methodology/Technique - This study uses 5 independent variables namely; firm growth (growth rate in total gross assets), asset tangibility (ratio of net fixed assets to total assets), cost of debt (interest before tax / long term debt), profitability (Earnings Before Interest and Taxes (EBIT) / Total Asset), and business risk (standard deviation of EBIT to total assets). The dependent variable in this study, debt capital, is measured by the ratio of long-term debt to total assets. A purposive sampling method is used to select 11 out of 18 textile and garment companies listed on the Indonesian Stock Exchange between 2014 and 2018 that report their annual financial positions. A quantitative method, panel data analysis technique and SPSS tools were also used in this study.Finding - The results show that debt capital is influenced by profitability, while the remaining factors do not influence debt capital.Novelty - This study adds to the existing literature on internal factors, market condition as an external factors, and debt capital in developed countries. The benefit of this study is to explore the potential capabilities of the industry in using its profit to minimize the use of debt as a source of capital to decrease business risk.Type of Paper - Empirical.

The Long Rise and Quick Fall of Appraisal Arbitrage
Jiang, Wei,Li, Tao,Thomas, Randall S.
Appraisal is a legislatively created right for shareholders to seek a judicial determination of the fair value of their stock in certain transactions. For many decades, appraisal was a little used, frequently maligned, corporate law remedy. Beginning at the turn of the 21st century, this all changed when a group of financial investors, including several hedge funds, began filing appraisal cases. Appraisal arbitrage, as it became known, grew rapidly in popularity.

The Overnight Drift
Boyarchenko, Nina,Larsen, Lars Christian,Whelan, Paul
Since the advent of electronic trading in the mid-1990s, U.S. equities have traded (almost) twenty-four hours a day through equity index futures. This allows new information to be incorporated continuously into asset prices, yet we show that almost 100 percent of the U.S. equity premium is earned during a one-hour window between 2:00 a.m. and 3:00 a.m. (EST), which we dub the “overnight drift.” We study explanations for this finding within a framework à la Grossman and Miller (1988) and derive testable predictions linking dealer inventory shocks to high-frequency return predictability. Consistent with the predictions of the model, we document a strong negative relationship between endâ€"of-day order imbalance, arising from market sell-offs, and the overnight drift occurring at the opening of European financial markets. Further, we show that in recent years dealers have increasingly offloaded inventory shocks at the opening of Asian markets, and we exploit a natural experiment based on daylight saving time to show that Asian offloading shifts by one hour between summer and winter.

The Perils of Private Provision of Public Goods
Gurun, Umit,Nickerson, Jordan,Solomon, David H.
In May 2018, in response to protests, Starbucks changed its policies nationwide to allow anybody to sit in their stores and use the bathroom without making a purchase. Using a large panel of anonymized cellphone location data, we estimate that the policy led to a 7.3% decline in store attendance at Starbucks locations relative to other nearby coffee shops and restaurants. This decline cannot be calculated from Starbucks’ public disclosures, which lack the comparison group of other coffee shops. The decline in visits is around 84% larger for stores located near homeless shelters. The policy also affected the intensive margin of demand: remaining customers spent 4.1% less time in Starbucks relative to nearby coffee shops after the policy enactment. Wealthier customers reduced their visits more, but black and white customers were equally deterred. The policy led to fewer citations for public urination near Starbucks locations, but had no effect on other similar public order crimes. These results show the difficulties of companies attempting to provide public goods, as potential customers are crowded out by non-paying members of the public.

The Role of Future Economic Conditions in the Cross-Section of Stock Returns: Evidence From the US and UK
Zhu, Sheng,Gao, Jun ,Sherman , Meadhbh
Our study investigates the explanatory power of future economic conditions on individual stock returns in the US and UK equity markets. We analyse a new trading strategy that is based on rational forecasts of future real activity. In addition, we specifically examine the performance of this trading strategy applied to two different classifications of stocks â€" procyclical stocks and countercyclical stocks. Our findings indicate a strong persistence in the relationship between returns on pro-cyclical stocks and the business cycle. However, such persistence is not present when moving to counter-cyclical stocks in the US and the UK. From this we suggest that US and UK equity investors who predict future real activity accurately can improve their investment profitability by longing pro-cyclical stocks when they expect future economic conditions to be above the long-run trend and shorting those stocks when future activity is anticipated to be below the steady state.

Transformers for Limit Order Books
James Wallbridge

We introduce a new deep learning architecture for predicting price movements from limit order books. This architecture uses a causal convolutional network for feature extraction in combination with masked self-attention to update features based on relevant contextual information. This architecture is shown to significantly outperform existing architectures such as those using convolutional networks (CNN) and Long-Short Term Memory (LSTM) establishing a new state-of-the-art benchmark for the FI-2010 dataset.

Ultra-Low Interest Rates: Risk Measurement/Assessment and Macroprudential Political Economy
Masera, Rainer
After recalling the quantitative relevance as of end-2019 of “new normal” ultra-low interest rates at world level, a brief discussion is offered of key areas of economic analysis and policy critically impacted by negative nominal interest rates. Specific reference is made to the following points. Risk modelling/measurement and the Basel risk-weighted capital framework. The operational viability of banks and insurance companies and the growth of leveraged loans. The liquidity trap revisited and the risk of illiquidity. Secular stagnation and the savings glut: the role of monetary policy. Political economy in the EA: a macro-prudential network perspective to prevent systemic risk. The case for infrastructure investment. On the basis of the arguments presented, it is argued, in the concluding remarks, that the costs of prolonged primary reliance on monetary expansion and sub-zero interest rates outweigh the benefits. A more balanced policy approach is outlined, with a view to improving the functioning of the Eurozone, enlarging the policy space, and reducing financial vulnerabilities.

Who Benefited from the Lending Boom to Poor and Minority Neighborhoods Leading to the Housing Crisis?
Rojas, Alejandro
The dramatic growth in home purchase mortgage lending leading to the housing crisis of the mid-2000s was concentrated in neighborhoods with lower incomes and higher minority concentrations. However, this relative growth in lending in lower-income and higher-minority neighborhoods benefited all types of households within these neighborhoods. In fact, relative growth in lending was strongest for the higher-income and non-minority households in these neighborhoods. This evidence is consistent with the “credit supply view” that there was an expansion in the supply of mortgage credit, but suggests that the expansion had a strong geographic concentration.