Research articles for the 2019-09-26

A Comparative Intermediary and Operational Efficiency Study of Private and Government Banking System in Iran Applying Data Envelopment Analysis (DEA)
Asgari Alouj, Hosein ,Nia, Nahid Maleki,Pireivatlou, Ayyoub Sarafraz
This study evaluated efficiency of private and government banks using Data Envelopment Analysis with Assumption of a constant and variable return to scale. The statistical study included nine government and six private banks taken from the period of 2006-2010. Total expenditures and deposits as inputs and total credit facilities and revenues as outputs were chosen because of both operational and intermediary approach were used in this study. The results implied the condition of inputs and outputs of the governments was not optimized with compared the private banks and also, the same of the commercial banks was not optimized with compared the specialized banks and their effectiveness could be increased. Also the BCC output centered model was more meaningful than CCR modelused to express the efficiency score of government and private banks that respectively were 93.82%, 94.52% and thus the weighted average of efficiency for whole banks would be 94.1%

An Endogenous Mechanism of Business Cycles
Dimitri Kroujiline,Maxim Gusev,Dmitry Ushanov,Sergey V. Sharov,Boris Govorkov

This paper suggests that business cycles may be a manifestation of coupled real economy and stock market dynamics and describes a mechanism that can generate economic fluctuations consistent with observed business cycles. To this end, we seek to incorporate into the macroeconomic framework a dynamic stock market model based on opinion interactions (Gusev et al., 2015). We derive this model from microfoundations, provide its empirical verification, demonstrate that it contains the efficient market as a particular regime and establish a link through which macroeconomic models can be attached for the study of real economy and stock market interaction. To examine key effects, we link it with a simple macroeconomic model (Blanchard, 1981). The coupled system generates nontrivial endogenous dynamics, which exhibit deterministic and stochastic features, producing quasiperiodic fluctuations (business cycles). We also inspect this system's behavior in the phase space. The real economy and the stock market coevolve dynamically along the path governed by a stochastically-forced dynamical system with two stable equilibria, one where the economy expands and the other where it contracts, resulting in business cycles identified as the coherence resonance phenomenon. Thus, the incorporation of stock market dynamics into the macroeconomic framework, as presented here, allows the derivation of realistic behaviors in a tractable setting.

Anomalous diffusions in option prices: connecting trade duration and the volatility term structure
Antoine Jacquier,Lorenzo Torricelli

Anomalous diffusions arise as scaling limits of continuous-time random walks (CTRWs) whose innovation times are distributed according to a power law. The impact of a non-exponential waiting time does not vanish with time and leads to different distribution spread rates compared to standard models. In financial modelling this has been used to accommodate for random trade duration in the tick-by-tick price process. We show here that anomalous diffusions are able to reproduce the market behaviour of the implied volatility more consistently than usual L\'evy or stochastic volatility models. We focus on two distinct classes of underlying asset models, one with independent price innovations and waiting times, and one allowing dependence between these two components. These two models capture the well-known paradigm according to which shorter trade duration is associated with higher return impact of individual trades. We fully describe these processes in a semimartingale setting leading no-arbitrage pricing formulae, and study their statistical properties. We observe that skewness and kurtosis of the asset returns do not tend to zero as time goes by. We also characterize the large-maturity asymptotics of Call option prices, and find that the convergence rate is slower than in standard L\'evy regimes, which in turn yields a declining implied volatility term structure and a slower decay of the skew.

Artificial Intelligence BlockCloud (AIBC) Technical Whitepaper
Qi Deng

The AIBC is an Artificial Intelligence and blockchain technology based large-scale decentralized ecosystem that allows system-wide low-cost sharing of computing and storage resources. The AIBC consists of four layers: a fundamental layer, a resource layer, an application layer, and an ecosystem layer. The AIBC implements a two-consensus scheme to enforce upper-layer economic policies and achieve fundamental layer performance and robustness: the DPoEV incentive consensus on the application and resource layers, and the DABFT distributed consensus on the fundamental layer. The DABFT uses deep learning techniques to predict and select the most suitable BFT algorithm in order to achieve the best balance of performance, robustness, and security. The DPoEV uses the knowledge map algorithm to accurately assess the economic value of digital assets.

Autonomous Driving and Residential Location Preferences: Evidence from a Stated Choice Survey
Rico Krueger,Taha H. Rashidi,Vinayak V. Dixit

The literature suggests that autonomous vehicles (AVs) may drastically change the user experience of private automobile travel by allowing users to engage in productive or relaxing activities while travelling. As a consequence, the generalised cost of car travel may decrease, and car users may become less sensitive to travel time. By facilitating private motorised mobility, AVs may eventually impact land use and households' residential location choices. This paper seeks to advance the understanding of the potential impacts of AVs on travel behaviour and land use by investigating stated preferences for combinations of residential locations and travel options for the commute in the context of autonomous automobile travel. Our analysis draws from a stated preference survey, which was completed by 512 commuters from the Sydney metropolitan area in Australia and provides insights into travel time valuations in a long-term decision-making context. For the analysis of the stated choice data, mixed logit models are estimated. Based on the empirical results, no changes in the valuation of travel time due to the advent of AVs should be expected. However, given the hypothetical nature of the stated preference survey, the results may be affected by methodological limitations.

Building FinTech Ecosystems: Regulatory Sandboxes, Innovation Hubs and Beyond
Buckley, Ross P.,Arner, Douglas W.,Veidt, Robin,Zetzsche, Dirk A.
Around the world, regulators and policymakers are working to support the development of financial technology (FinTech) ecosystems. As one example, over 50 jurisdictions have now established or announced “financial regulatory sandboxes”. Others have announced or established “innovation hubs”, sometimes incorporating a regulatory sandbox as one element. This article argues that innovation hubs provide all the benefits that the policy discussion associates with regulatory sandboxes, while avoiding most downsides of regulatory sandboxes, and that many benefits typically attributed to sandboxes are the result of inconsistent terminology, and actually accrue from the work of innovation hubs. The paper presents, as the first contribution of its kind, data on regulatory sandboxes and innovation hubs and argues that the data so far available on sandboxes does not justify the statement that regulatory sandboxes are the most effective approach to building FinTech ecosystems. Given that regulatory sandboxes require significant financial contributions, sometimes new legislation, and intense regulatory risk management, and that sandboxes do not work as well on a stand-alone basis (i.e. without an innovation hub), while innovation hubs alone can provide more significant benefits in supporting the development of a FinTech ecosystem, regulators should focus their resources on developing effective innovation hubs, including in appropriate cases a sandbox as one possible element.

Contractual Complexity in Debt Agreements: The Case of EBITDA
Badawi, Adam B.,de Fontenay, Elisabeth
The definition of EBITDA is among the most important parts of a credit agreement. This concept matters to borrowers and creditors because it frequently determines whether a borrower is in breach of its covenants in the loan, and it matters to regulators because it determines the amount of leverage a loan entails. While credit analysts and debt lawyers have commented on the differences in the definition of EBITDA, existing research on debt agreements has almost entirely ignored this variation and the consequences it has for understanding how debt agreements operate. We use supervised learning of income definitions in thousands of credit agreements to show that there is, indeed, massive variation in the definition of EBITDA and that a substantial proportion of these agreements inflate EBITDA by adding back income. In further analysis we show that expansive EBITDA definitions are more common among private equity borrowers and that banks appear to have allowed more permissive EBITDA definitions for non-private equity borrowers in the wake of the Federal Reserve’s restrictive guidance on lending leverage. We show that there is a negative relationship between the permissiveness of EBITDA definitions and the amount of covenant slack in loans and that more permissive definitions are associated with higher loan spreads. Finally, we demonstrate that the best predictors of the content of income definitions are the past credit agreements of the borrower.

Does Financial Statement Comparability Mitigate Delayed Trading Volume Before Earnings Announcements?
Kim, Junwoo,Kim, Robert,Kim, Sangwan
This paper examines the role of financial statement comparability in shaping trading volume prior to earnings announcements. We find that the degree of delayed trading volume prior to earnings announcements is less pronounced for firms with more comparable financial statements. In addition, the effect of financial statement comparability on pre-announcement trading volume is stronger in more opaque information environments. Our findings are incrementally significant after controlling for a comprehensive set of within-firm earnings attributes and robust to various research design choices including alternative comparability models with differing peer group selection. Collectively, our results show that financial statement comparability serves an integral mechanism facilitating a firm’s pre-existing information environment. In sum, this paper constitutes the first, volume-based evidence which lends support to the usefulness of financial statement comparability in investors’ trading activity.

Finance and Carbon Emissions
De Haas, Ralph,Popov, Alexander A.
We study the relation between the structure of financial systems and carbon emissions in a large panel of countries and industries over the period 1990-2013. We find that for given levels of economic and financial development and environmental regulation, CO2 emissions per capita are lower in economies that are relatively more equity-funded. Industry-level analysis reveals two distinct channels. First, stock markets reallocate investment towards less polluting sectors. Second, they also push carbon-intensive sectors to develop and implement greener technologies. In line with this second effect, we show that carbon-intensive sectors produce more green patents as stock markets deepen. We also document an increase in carbon emissions associated with the production of imported goods equal to around one-tenth of the reduction in domestic carbon emissions.

Guidance on Strategic Information: Investor-Management Disagreement and Firm Intrinsic Value
Agapova, Anna,Volkov, Nikanor
We investigate the decision by corporate management to voluntarily disclose information that pertains to a firm’s strategy. We find the likelihood of disclosure to be a tradeoff between the benefit of reducing information asymmetry and the cost of investors disagreeing with the strategy; this cost varies with the firm’s intrinsic value. Higher levels of investor-management disagreement and of information asymmetry increase the likelihood that managers will disclose strategic information; those at firms with higher intrinsic value, however, are less likely to do so. Our results vary in statistical significance across different proxy specifications, but hold qualitatively. They are robust to the use of exogenous shocks to investor-management disagreement and information asymmetry. The evidence supports a causal link between investor-management disagreement and strategic disclosure.

Has the New Bail-In Framework Increased the Yield Spread between Subordinated and Senior Bonds?
Pablos, Irene
This paper investigates the impact of the introduction and implementation of the new EU bail-in framework on the banks subordinated bond yield spreads over senior unsecured bonds, and links the bond yields developments with the characteristics of the issuing entities and the economic and financial environment. The analysis does not show evidence of a significant and generalized increase in the spreads as a result of a higher risk perception in the sample under review. The results reinforce the relevance of the Tier 1 capital ratio for making subordinated debt safer, while markets price the higher risk of banks with less stable sources of funding in their liability/capital structures. Market conditions and economic environment variables also play a key role in explaining bond spreads. Interestingly, after the introduction of the new bail-in framework, there is a convergence between the bond yields of the GSIBs and the non-GSIBs, which could point out to a reduction in the market perception of the so called “too big to fail” public implicit guarantee. Nonetheless, this convergence is mostly driven by the reduction of the yields of bonds issued by banks not categorized as GSIBs, and not by significant increases in the GSIBs’ bond yields.

How the network properties of shareholders vary with investor type and country
Qing Yao,Tim Evans,Kim Christensen

We construct two examples of shareholder networks in which shareholders are connected if they have shares in the same company. We do this for the shareholders in Turkish companies and we compare this against the network formed from the shareholdings in Dutch companies. We analyse the properties of these two networks in terms of the different types of shareholder. We create a suitable randomised version of these networks to enable us to find significant features in our networks. For that we find the roles played by different types of shareholder in these networks, and also show how these roles differ in the two countries we study.

Intraday Pattern in the US Corporate Bond Market
Yang, Lu
In this paper, we employ the Trace Enhanced database to investigate the intraday pattern in the US corporate bond market. We find that there is intraday reversal in the cross-sections of bond returns based on half-hour intervals. Regardless of the volume, order imbalance, ratings, and liquidity, the pattern only changes its strength. Specifically, high volume, high liquidity, and low order imbalance enhance this pattern. Moreover, we also identify the daily return continuation effect lasting for at least 4 days based on the first half-hour return. The overreaction to the security-specific component of bond returns may primarily explain this phenomenon while common risk factors only change its degree.

Investor Sentiment and Microstructure Information in Index Futures Markets
Li, Weiping,Wen, Liu Wen
We show how specific features of the microstructure information from VPIN and DPIN can volatile the futures market and can link with the price discover and investor sentiment. We develop an investor (institutional, noise, and both) sentiment index for the Shanghai StockExchange 50 (SSE 50) Index Futures, and analyze relations among the index futures return, the investor sentiment, VPIN and DPIN, illiquidity, and volatility. We first specify the informed investor sentiment index for traders who invest based on market information and uninformed investor sentiment index for irrational noise traders who provide market liquidity. Empirically, the VPIN and the investor sentiment can predict the SSE 50 futures returns in a low frequency environment, and there is a significantly negative correlation between the informed transaction and the next level of liquidity in a high frequency environment. We also show that the futures market is relatively stable under moderate investor sentiment, and the trading volume can correspond to both investor sentiment and liquidity levels.

Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations
Takaaki Koike,Marius Hofert

We propose a novel framework of estimating systemic risk measures and risk allocations based on a Markov chain Monte Carlo (MCMC) method. We consider a class of allocations whose j-th component can be written as some risk measure of the j-th conditional marginal loss distribution given the so-called crisis event. By considering a crisis event as an intersection of linear constraints, this class of allocations covers, for example, conditional Value-at-Risk (CoVaR), conditional expected shortfall (CoES), VaR contributions, and range VaR (RVaR) contributions as special cases. For this class of allocations, analytical calculations are rarely available, and numerical computations based on Monte Carlo methods often provide inefficient estimates due to the rare-event character of crisis events. We propose an MCMC estimator constructed from a sample path of a Markov chain whose stationary distribution is the conditional distribution given the crisis event. Efficient constructions of Markov chains, such as Hamiltonian Monte Carlo and Gibbs sampler, are suggested and studied depending on the crisis event and the underlying loss distribution. Efficiency of the MCMC estimators are demonstrated in a series of numerical experiments.

McDonald's: A Sustainable Finance Case Study
Schramade, Willem
This is the third in a series of RSM case studies on sustainable finance. Using a list of questions, we show how to integrate sustainability into investment analysis by connecting sustainability to business models, competitive position, strategy and value drivers. Here the questions are answered for McDonald’s, a company that faces substantial sustainability challenges, on both the social (health) and environmental (footprint) dimensions. Our findings suggest that McDonald’s is not as well positioned as Philips, but much better than Air France-KLM. Unlike the latter, McDonald’s does have significant options to deal with its sustainability issues. However, our ability to properly assess its transition preparedness is hampered due to the absence of essential data: McDonald’s sustainability reporting is limited and lacks targets and numbers. Unfortunately, this is typical of current reporting practices.

Optimal Incentive Contract with Endogenous Monitoring Technology
Anqi Li,Ming Yang

Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer's strategic planning. In otherwise standard principal-agent models with moral hazard, we allow the principal to partition agents' performance data into any finite categories and to pay for the amount of information that the output signal carries. Through analysis of the trade-off between giving incentives to agents and saving the monitoring cost, we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to rising monitoring costs, and assessing multiple task performances according to agents' endogenous tendencies to shirk. We examine the implications of these results for workforce management and firms' internal organizations.

Propaganda, Conspiracy Theories, and Accountability in Fragile Democracies
Anqi Li,Davin Raiha,Kenneth W. Shotts

We develop a model of electoral selection and accountability in the presence of mainstream and alternative media outlets. In addition to standard high and low competence types, the incumbent may be an aspiring autocrat, who controls the mainstream media and will cause substantial harm if not removed from office. Alternative media can help voters identify and remove aspiring autocrats and can enable voters to focus on honest mainstream media assessments of incumbents' competence. But malicious alternative media that peddle false conspiracy theories about the incumbent and the mainstream media can induce voters to mistakenly remove nonautocratic incumbents, which in turn demotivates incumbent effort and undermines accountability. The alternative media is most dangerous when it is sufficiently credible that voters pay attention to it, but sufficiently likely to be malicious that it undermines accountability.

Stock Return Comovement in the New Millennium
Vivero, Maria G.
Long run dynamics in stock return comovement, their causes and consequences, are hotly debated topics in Financial Economics. Average return correlation, or comovement, is a widely used market efficiency indicator. I study the times series characteristics in US comovement during the 1926- 2010 period and find a significant break in the series’ trend in January of 1997. After the break, the negative comovement trend previously documented for most of the 20th century reverts to strongly positive. In addition, I find a decline in the importance of firm-specific volatility after the break and no evidence of a trend reversal in the correlation structure of firm cash flows. This suggests that higher return comovement is the result of correlated trading unrelated to firm fundamentals. I discuss several potential explanations for this increase, cause by technological change in the financial sector.

The Cross-Section of Volatility and Expected Returns: Then and Now
Detzel, Andrew L.,Duarte, Jefferson,Kamara, Avraham,Siegel, Stephan,Sun, Celine
We successfully replicate the main results of Ang, Hodrick, Xing, and Zhang (2006): Aggregate-volatility risk and idiosyncratic volatility (IV) are each priced in the cross-section of stock returns from 1963 to 2000. We also examine the pricing of volatility outside the original time period and under more recent asset-pricing models. With the exception of NASDAQ stocks, aggregate-volatility risk continues to be priced in the years following the Ang et al. (2006) sample period, and none of the more recent asset-pricing models we consider consistently accounts for the pricing of aggregate-volatility risk. The difference in abnormal returns between stocks with high and low IV decreases but remains significant out-of-sample. More recent asset-pricing models do not resolve the IV anomaly for the Ang et al. (2006) sample, but the four-factor model of Stambaugh and Yuan (2017) and the six-factor model of Barillas and Shanken (2018) resolve the anomaly out-of-sample and over the extended period of 1967 to 2016. Finally, both models eliminate the arbitrage asymmetry that Stambaugh, Yu, and Yuan (2015) propose as an explanation of the IV anomaly.