Research articles for the 2020-06-01

A Comparative Study of Stock Screening Methodologies in Stock Exchanges of Bangladesh and Malaysia and Lessons to Be Learnt
Jalil, Md. Abdul
The study aims to compare and critically evaluate the stock screening practices between Bangladesh and Malaysia. The specific objectives determined to fulfill the aims are: (i) To review some of the Islamic equity market norms along with juristic views (ii) To review the prevalent practices of stock screening methods used by international index providers (iii) To evaluate critically and compare the stock screening methodology used by Dhaka Stock Exchange (DSE), Chittagong Stock Exchange (CSE), and Bursa Malaysia. The study is descriptive in nature. Secondary data is utilized and collected from the books, standards, journal articles and relevant publications. AAOIFI standards, OIC Fiqh Academy resolutions etc. are referenced as needed.DSE, CSE and Bursa differs in formulating ratios, denominators, numerators and in determining benchmark. The study finds that Bursa uses two thresholds to measure shari’ah non-compliance whereas DSE and CSE use single benchmark, 5% and 4% respectively. For financial screening, DSE uses market value of equity as numerator whereas CSE and Bursa use total assets as numerator. Because of the differences, one company may be included in Shari’ah Index in Bangladesh, but not in Malaysia and vice versa.

A Theory of 'Auction as a Search' in speculative markets
Sudhanshu Pani

The tatonnement process in high frequency order driven markets is modeled as a search by buyers for sellers and vice-versa. We propose a total order book model, comprising limit orders and latent orders, in the absence of a market maker. A zero intelligence approach of agents is employed using a diffusion-drift-reaction model, to explain the trading through continuous auctions (price and volume). The search (levy or brownian) for transaction price is the primary diffusion mechanism with other behavioural dynamics in the model inspired from foraging, chemotaxis and robotic search. Analytic and asymptotic analysis is provided for several scenarios and examples. Numerical simulation of the model extends our understanding of the relative performance between brownian, superdiffusive and ballistic search in the model.

Analysis of the Deposit Resources’ Regional Allocation in Ukraine
Zadorozhna, Ruslana
The intermediary function of financial corporations is embodied in the redistribution of temporarily free funds raised from certain institutional units to those units that have a need for them. A significant part of such borrowings takes the form of deposits placed with commercial banks. Amounts accumulated in the form of deposits are an important component of the resource base of banking institutions. This allows them to conduct assets banking operations to lend the population and enterprises of the economy's real sector and contribute to economic growth in the country.The purpose of the study is to perform a statistical analysis of the regional allocation of deposits held with Ukrainian commercial banks over the period 2010-2018.The conceptual basis of the study is formed by the approaches of the System of National Accounts and Monetary Statistics. The study is based on the National Bank of Ukraine (NBU) information. The results obtained indicate a high degree of heterogeneity of the regions of Ukraine in terms of deposits attracted by commercial banks. Regional variation in deposits amounts is too big. Three regions can be classified as outliers. These are the capital region â€" Kyiv region and the most industrially developed Dnepropetrovsk and Donetsk region. This conclusion is confirmed by the analysis of variation and the form of regions' distribution. The most significant changes in the distribution of regions occurred in 2014 due to the dramatic events of modern Ukrainian history.We also conclude the growing level of deposits' concentration based on the concentration index-3, concentration index-5, Herfindahl-Hirschman Index and Gini coefficient. Since geographical diversification is a necessary prerequisite for reducing the riskiness of deposit operations, appropriate managerial decisions must be taken.

Are the Largest Banking Organizations Operationally More Risky?
Curti, Filippo,Frame, W. Scott, Mihov, Atanas
This study demonstrates that, among large U.S. bank holding companies (BHCs), the largest ones are exposed to more operational risk. Specifically, they have higher operational losses per dollar of total assets, a result largely driven by the BHCs' failure to meet professional obligations to clients and/or faulty product design. Operational risk at the largest U.S. institutions is also found to: (i) be particularly persistent, (ii) have a counter-cyclical component (higher losses occur during economic downturns) and (iii) materialize through more frequent tail-risk events. We illustrate two plausible channels of BHC size that contribute to operational risk â€" institutional complexity and moral hazard incentives arising from “too-big-to-fail." Our findings have important implications for large banking organization performance, risk and supervision.

Asset Pricing with Ambiguous Signals: An Experiment
Bao, Te,Duffy, John,Zhu, Jiahua
This paper explores how ambiguous signals and ambiguity aversion influence individuals' expectations and the pricing of asset in experimental financial markets. In line with the theory of Epstein and Schneider (2008) we find that subjects' degree of ambiguity aversion is positively correlated with their expectations about the variance of ambiguous signals. These signals matter for the determination of asset prices. We find that the distribution of the excess return of the asset exhibits negative skewness, and that price volatility is significantly larger under ambiguous signals. Our findings provide evidence in support of the idea that ambiguous information and ambiguity aversion may be a source of negative skewness and excess volatility in financial markets.

Bankruptcy Process for Sale
Ayotte, Kenneth,Ellias, Jared A.
The lenders that fund Chapter 11 reorganizations exert significant influence over the bankruptcy process through the contract associated with the debtor-in-possession (“DIP”) loan. In this Article, we study a large sample of DIP loan contracts and document a trend: over the past three decades, DIP lenders have steadily increased their contractual control of Chapter 11. In fact, today’s DIP loan agreements routinely go so far as to dictate the very outcome of the restructuring process. When managers sell control over the bankruptcy case to a subset of the creditors in exchange for compensation, we call this transaction a “bankruptcy process sale.” We model two situations where process sales raise bankruptcy policy concerns: (1) when a senior creditor leverages the debtor’s need for financing to lock in a preferred outcome at the outset of the case (“plan protection”); and (2) when a senior creditor steers the case to protect its claim against litigation (“entitlement protection”). We show that both scenarios can lead to bankruptcy outcomes that fail to maximize the value of the firm for creditors as a whole. We study a new dataset that uses the text of 1.5 million court documents to identify creditor conflict over process sales, and our analysis offers evidence consistent with the predictions of the model.

CEO Influence on Funds from Operations (FFO) Adjustment for Real Estate Investment Trusts (REITs)
Feng, Zhilan,Lin, Zhilu,Wu, Wentao
This paper investigates non-GAAP performance measures of the REIT industry, specifically the difference (FFO adjustment) between concurrent FFO and Net Income (NI). Using the U.S. Equity REIT data from 1993 to 2018, we first find evidence that both NI and FFO are associated with REIT market-adjusted stock returns, suggesting both contain information that is valuable to investors. Second, we document a significant and positive relationship between contemporaneous FFO adjustment and NI, indicating a possible “selective” and “intentional” inclusion and/or omission of the “good” vs. “bad” news in the FFO reporting. Third, we find direct evidence that more powerful CEOs are indeed associated with higher FFO adjustments, suggesting CEOs’ involvement in hiding subpar performance. Finally, we focus our attention in a more recent period, when the National Association of Real Estate Investment Trusts (NAREIT) provides additional clarifications and guidelines, and the U.S. Securities and Exchange Commission (SEC) increases scrutiny on FFO reporting. Our results show a diminished “manipulation” for the majority of the REITs, suggesting these guidelines and scrutiny have achieved the intended purposes. While non-GAAP performance measures might supply additional information to investors, our results indicate that providing continuous guidance and monitoring is essential.

Capital Market Liberalization and Equity Market Interdependence
Fry-McKibbin, Renee,Yan, Ziyu
This paper uses tests drawn from the literature on financial market contagion measured by changes in higher-order comoments to establish the patterns in the interdependence between equity markets in Shanghai and Shenzhen with Hong Kong as mainland China liberalized their capital market. On the announcement of the opening of the Shanghai market correlations rise, but subside by the launch. Following the launch changes in coskewness, cokurtosis and covolatility emerge. The liberalization process is complete by mid-September 2016.

Central Bank Digital Currency: Central Banking for All?
Fernandez-Villaverde, Jesus,Sanches, Daniel,Uhlig, Harald
The introduction of a central bank digital currency (CBDC) allows the central bank to engage in large-scale intermediation by competing with private financial interme-diaries for deposits. Yet, since a central bank is not an investment expert, it cannot invest in long-term projects itself, but relies on investment banks to do so. We derive an equivalence result that shows that absent a banking panic, the set of allocations achieved with private financial intermediation will also be achieved with a CBDC. Dur-ing a panic, however, we show that the rigidity of the central bank’s contract with the investment banks has the capacity to deter runs. Thus, the central bank is more stable than the commercial banking sector. Depositors internalize this feature ex-ante, and the central bank arises as a deposit monopolist, attracting all deposits away from the commercial banking sector. This monopoly might endanger maturity transformation.

Changes in Household Net Financial Assets After the Great Recession: Did Financial Planners Make a Difference?
Joseph W. Goetz,Lance Palmer,Lini Zhang,Swarn Chatterjee

This study utilized the 2007-2009 Survey of Consumer Finances (SCF) panel dataset to examine the impact of financial planner use on household net financial asset level during the Great recession. Data included 3,862 respondents who completed the SCF survey and a follow up interview. The results indicated that starting to use a financial planner during the Great Recession had a positive impact on preserving and increasing the value of households' net financial assets, while curtailing the use of a financial planner during this time had a negative impact on preserving the value of households' financial assets. Thus, study findings indicated that the benefit of using a financial planner maybe particularly high during a major financial downturn.

Contingent Convertible Obligations and Financial Stability
Zachary Feinstein,T. R. Hurd

This paper investigates whether a financial system can be made more stable if financial institutions share risk by exchanging contingent convertible (CoCo) debt obligations. The question is framed in a financial network model of debt and equity interlinkages with the addition of a variant of the CoCo that converts continuously when a bank's equity-debt ratio drops to a trigger level. The main theoretical result is a complete characterization of the clearing problem for the interbank debt and equity at the maturity of the obligations. We then consider a simple setting in which introducing contingent convertible bonds improves financial stability, as well as specific networks for which contingent convertible bonds do not provide uniformly improved system performance. To return to the main question, we examine the EU financial network at the time of the 2011 EBA stress test to do comparative statics to study the implications of CoCo debt on financial stability. It is found that by replacing all unsecured interbank debt by standardized CoCo interbank debt securities, systemic risk in the EU will decrease and bank shareholder value will increase.

Does Spurious Mean Reversion in Basis Changes Still Exist After the Introduction of Exchange Traded Funds
Richie, Nivine,Muthuswamy, Jayaram,Segara, Reuben,Webb, Robert I.
In their seminal Journal of Finance article, Miller, Muthuswamy, and Whaley (MMW) [1994] document that the observed mean reversion of changes in the basis of cash and stock index futures prices is likely illusory. MMW use a simple time-series model to suggest that the apparent mean-reversion in the basis is a spurious artifact of non-synchronous prices between index futures and cash markets â€" rather than an indication of exploitable weak-form market inefficiency. Because the MMW effect is predominantly driven by liquidity differentials between cash and futures prices, the question naturally arises as to whether one would observe the same MMW phenomenon in the behaviour of the “basis” or difference between more actively traded ETF and cash market prices. This study attempts to answer that question by examining the “basis” behavior of the Standard and Poor’s Depository Receipt (SPDR) ETF traded on the American Stock Exchange. Overall, we find that the MMW phenomenon still persists strongly after the advent of Exchange Traded Funds. Moreover, an examination of the spread or “basis” between cash and ETF prices and the spread or “basis” between futures and ETF prices shows that the apparent mean reversion in both is even more pronounced than in the basis between cash and futures prices. This demonstrates that the MMW effect is extremely robust and unlikely to “go-away” soon.

Doubling Down on the Safe(ty) Bet: Bailouts and Risk-Shifting at the Intensive Margin
Eufinger, Christian,Ye, Zhiqiang
Banks have a significant funding-cost advantage since their liabilities are protected by various government safety nets. We construct a corporate finance-style model that shows that banks can exploit this funding-cost advantage by just intermediating funds between investors and ultimate borrowers, thereby earning the spread between their reduced funding rate and the competitive market rate. This mechanism leads to a crowding-out of direct market finance and real effects for bank borrowers through bank risk-shifting at the intensive margin. That is, banks induce their borrowers to leverage excessively, to overinvest, and to conduct inferior high-risk projects.

Egalitarian and Just Digital Currency Networks
Gal Shahaf,Ehud Shapiro,Nimrod Talmon

Cryptocurrencies are a digital medium of exchange with decentralized control that renders the community operating the cryptocurrency its sovereign. Leading cryptocurrencies use proof-of-work or proof-of-stake to reach consensus, thus are inherently plutocratic. This plutocracy is reflected not only in control over execution, but also in the distribution of new wealth, giving rise to ``rich get richer'' phenomena. Here, we explore the possibility of an alternative digital currency that is egalitarian in control and just in the distribution of created wealth. Such currencies can form and grow in grassroots and sybil-resilient way. A single currency community can achieve distributive justice by egalitarian coin minting, where each member mints one coin at every time step. Egalitarian minting results, in the limit, in the dilution of any inherited assets and in each member having an equal share of the minted currency, adjusted by the relative productivity of the members. Our main theorem shows that a currency network, where agents can be members of more than one currency community, can achieve distributive justice globally across the network by \emph{joint egalitarian minting}, where each agent mints one coin in only one community at each timestep. Equality and distributive justice can be achieved among people that own the computational agents of a currency community provided that the agents are genuine (unique and singular). We show that currency networks are sybil-resilient, in the sense that sybils (fake or duplicate agents) affect only the communities that harbour them, and not hamper the ability of genuine (sybil-free)communities in a network to achieve distributed justice.

Evolution of the Chinese Guarantee Network under Financial Crisis and Stimulus Program
Yingli Wang,Qingpeng Zhang,Xiaoguang Yang

Our knowledge about the evolution of guarantee network in downturn period is limited due to the lack of comprehensive data of the whole credit system. Here we analyze the dynamic Chinese guarantee network constructed from a comprehensive bank loan dataset that accounts for nearly 80% total loans in China, during 01/2007-03/2012. The results show that, first, during the 2007-2008 global financial crisis, the guarantee network became smaller, less connected and more stable because of many bankruptcies; second, the stimulus program encouraged mutual guarantee behaviors, resulting in highly reciprocal and fragile network structure; third, the following monetary policy adjustment enhanced the resilience of the guarantee network by reducing mutual guarantees. Interestingly, our work reveals that the financial crisis made the network more resilient, and conversely, the government bailout degenerated network resilience. These counterintuitive findings can provide new insight into the resilience of real-world credit system under external shocks or rescues.

How and Why Do Managers Use Public Forecasts to Guide the Market?
Charoenwong, Ben,Kimura, Yosuke,Kwan, Alan
We compare publicly disclosed forecasts and internal forecasts collected by confidential government surveys using a sample of publicly-listed Japanese firms. Both forecasts are mandatory and meaningfully predict corporate policy but on average public forecasts are pessimistic relative to internal forecasts. Firms with greater shareholder pressure and bonus-related compensation are more pessimistic. Public pessimism likely guides market beliefs down, predicting higher future stock returns, earnings surprises, and executive, but not rank-and-file, compensation. However, it flips to optimism when firms are financially constrained, consistent with an inter-temporal trade-off between benefits from meeting managerial goalposts versus maintaining financial flexibility.

Implied Dividend Yield as a New Stock Market Valuation Measure
Taran Grove,Michael Reyes,Andrey Sarantsev

Long-run total real returns of the USA stock market are approximately equal to long-run real earnings growth plus average dividend yield. However, earnings can be distributed to shareholders in various ways: dividends, stock buybacks, debt payments. Thus the total returns minus earnings growth can be considered as implied dividend yield. This quantity must be stable in the long run. If the converse is true: this quantity is abnormally high in the last few years, then the market is overpriced. A measure of this is (detrended) cumulative sum of differences. We regress next year's implied dividend yield upon this current valuation measure. We simulate future returns, starting from the current market conditions. We reject the conventional wisdom that currently the market is overpriced. In our model the current market is undervalued and is likely to grow faster than historically. We show that this measure has better predictive power than the P/E and CAPE ratios.

Long-range memory test by the burst and inter-burst duration distribution
Vygintas Gontis

It is empirically established that order flow in the financial markets is positively auto-correlated and can serve as an example of a social system with long-range memory. Nevertheless, widely used long-range memory estimators give varying values of the Hurst exponent. We propose the burst and inter-burst duration statistical analysis as one more test of long-range memory and implement it with the limit order book data comparing it with other widely used estimators. This method gives a more reliable evaluation of the Hurst exponent independent of the stock in consideration or time definition used. Results strengthen the expectation that burst and inter-burst duration analysis can serve as a better method to investigate the property of long-range memory.

Machine Learning Fund Categorizations
Dhagash Mehta,Dhruv Desai,Jithin Pradeep

Given the surge in popularity of mutual funds (including exchange-traded funds (ETFs)) as a diversified financial investment, a vast variety of mutual funds from various investment management firms and diversification strategies have become available in the market. Identifying similar mutual funds among such a wide landscape of mutual funds has become more important than ever because of many applications ranging from sales and marketing to portfolio replication, portfolio diversification and tax loss harvesting. The current best method is data-vendor provided categorization which usually relies on curation by human experts with the help of available data. In this work, we establish that an industry wide well-regarded categorization system is learnable using machine learning and largely reproducible, and in turn constructing a truly data-driven categorization. We discuss the intellectual challenges in learning this man-made system, our results and their implications.

Macro-Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models
Cheng, Xu,Dou, Winston Wei,Liao, Zhipeng
This paper shows that robust inference under weak identification is important to the evaluation of many influential macro asset pricing models, including long-run risk models, disaster risk models, and multifactor linear asset pricing models. Building on recent developments in the conditional inference literature, we provide a new specification test by simulating the critical value conditional on a sufficient statistic. This sufficient statistic can be intuitively interpreted as a measure capturing the macroeconomic information decoupled from the underlying content of asset pricing theories. Macro-finance decoupling is an effective way to improve the power of our specification test when asset pricing theories are difficult to refute due to an imbalance in the information content about the key model parameters between macroeconomic moment restrictions and asset pricing cross-equation restrictions.

Measuring and Visualizing Place-Based Space-Time Job Accessibility
Yujie Hu,Joni Downs

Place-based accessibility measures, such as the gravity-based model, are widely applied to study the spatial accessibility of workers to job opportunities in cities. However, gravity-based measures often suffer from three main limitations: (1) they are sensitive to the spatial configuration and scale of the units of analysis, which are not specifically designed for capturing job accessibility patterns and are often too coarse; (2) they omit the temporal dynamics of job opportunities and workers in the calculation, instead assuming that they remain stable over time; and (3) they do not lend themselves to dynamic geovisualization techniques. In this paper, a new methodological framework for measuring and visualizing place-based job accessibility in space and time is presented that overcomes these three limitations. First, discretization and dasymetric mapping approaches are used to disaggregate counts of jobs and workers over specific time intervals to a fine-scale grid. Second, Shen (1998) gravity-based accessibility measure is modified to account for temporal fluctuations in the spatial distributions of the supply of jobs and the demand of workers and is used to estimate hourly job accessibility at each cell. Third, a four-dimensional volumetric rendering approach is employed to integrate the hourly job access estimates into a space-time cube environment, which enables the users to interactively visualize the space-time job accessibility patterns. The integrated framework is demonstrated in the context of a case study of the Tampa Bay region of Florida. The findings demonstrate the value of the proposed methodology in job accessibility analysis and the policy-making process.

Mixing LSMC and PDE Methods to Price Bermudan Options
David Farahany,Kenneth Jackson,Sebastian Jaimungal

We develop a mixed least squares Monte Carlo-partial differential equation (LSMC-PDE) method for pricing Bermudan style options on assets whose volatility is stochastic. The algorithm is formulated for an arbitrary number of assets and volatility processes and we prove the algorithm converges almost surely for a class of models. We also discuss two methods to improve the algorithm's computational complexity. Our numerical examples focus on the single ($2d$) and multi-dimensional ($4d$) Heston models and we compare our hybrid algorithm with classical LSMC approaches. In each case, we find that the hybrid algorithm outperforms standard LSMC in terms of estimating prices and optimal exercise boundaries.

Moment Approximations of Displaced Forward-LIBOR Rates with Application to Swaptions
van Appel, Jacques,McWalter, Thomas
We present an algorithm to approximate moments for forward rates under a displaced lognormal forward-LIBOR model (DLFM). Since the joint distribution of rates is unknown, we use a multi-dimensional full weak order 2.0 Ito-Taylor expansion in combination with a second-order Delta method. This more accurately accounts for state dependence in the drift terms, improving upon previous approaches. To verify this improvement we conduct quasi-Monte Carlo simulations. We use the new mean approximation to provide an improved swaption volatility approximation, and compare this to the approaches of Rebonato, Hull-White and Kawai, adapted to price swaptions under the DLFM. Rebonato and Hull-White are found to be the least accurate. While Kawai is the most accurate, it is computationally inefficient. Numerical results show that our approach strikes a balance between accuracy and efficiency.

Mortality containment vs. economics opening: optimal policies in a SEIARD model
Andrea Aspri,Elena Beretta,Alberto Gandolfi,Etienne Wasmer

We adapt a SEIRD differential model with asymptomatic population and Covid deaths, which we call SEAIRD, to simulate the evolution of COVID-19, and add a control function affecting both the diffusion of the virus and GDP, featuring all direct and indirect containment policies; to model feasibility, the control is assumed to be a piece-wise linear function satisfying additional constraints. We describe the joint dynamics of infection and the economy and discuss the trade-off between production and fatalities. In particular, we carefully study the conditions for the existence of the optimal policy response and its uniqueness. Uniqueness crucially depends on the marginal rate of substitution between the statistical value of a human life and GDP; we show an example with a phase transition: above a certain threshold, there is a unique optimal containment policy; below the threshold, it is optimal to abstain from any containment; and at the threshold itself there are two optimal policies. We then explore and evaluate various profiles of various control policies dependent on a small number of parameters.

On Policy Evaluation with Aggregate Time-Series Shocks
Dmitry Arkhangelsky,Vasily Korovkin

We propose a general strategy for estimating treatment effects, in contexts where the only source of exogenous variation is a sequence of aggregate time-series shocks. We start by arguing that commonly used estimation procedures tend to ignore crucial time-series aspects of the data. Next, we develop a graphical tool and a formal test to illustrate the issues of the design using data from prominent studies in development economics and macroeconomic. Motivated by these studies, we construct a new IV estimator, which is based on the time-series model for the aggregate shock. We analyze the statistical properties of our estimator in a practically relevant case, where both cross-sectional and time-series dimensions are of similar size. Finally, to provide a causal interpretation for our estimator, we analyze a new causal model that allows taking into account both rich unobserved heterogeneity in potential outcomes and unobserved aggregate shocks.

On the optimality of joint periodic and extraordinary dividend strategies
Benjamin Avanzi,Hayden Lau,Bernard Wong

In this paper, we model the cash surplus (or equity) of a risky business with a Brownian motion. Owners can take cash out of the surplus in the form of ``dividends'', subject to transaction costs. However, if the surplus hits 0 then ruin occurs and the business cannot operate any more.

We consider two types of dividend distributions: (i) periodic, regular ones (that is, dividends can be paid only at countable many points in time, according to a specific arrival process); and (ii) extraordinary dividend payments that can be made immediately at any time (that is, the dividend decision time space is continuous and matches that of the surplus process). Both types of dividends attract proportional transaction costs, and extraordinary distributions also attracts fixed transaction costs, a realistic feature. A dividend strategy that involves both types of distributions (periodic and extraordinary) is qualified as ``hybrid''.

We determine which strategies (either periodic, immediate, or hybrid) are optimal, that is, we show which are the strategies that maximise the expected present value of dividends paid until ruin, net of transaction costs. Sometimes, a liquidation strategy (which pays out all monies and stops the process) is optimal. Which strategy is optimal depends on the profitability of the business, and the level of (proportional and fixed) transaction costs. Results are illustrated.

Optimal Equilibria for Multi-dimensional Time-inconsistent Stopping Problems
Yu-Jui Huang,Zhenhua Wang

We study an optimal stopping problem under non-exponential discounting, where the state process is a multi-dimensional continuous strong Markov process. The discount function is taken to be log sub-additive, capturing decreasing impatience in behavioral economics. On strength of probabilistic potential theory, we establish the existence of an optimal equilibrium among a sufficiently large collection of equilibria, consisting of finely closed equilibria satisfying a boundary condition. This generalizes the existence of optimal equilibria for one-dimensional stopping problems in prior literature.

Optimal Investing after Retirement Under Time-Varying Risk Capacity Constraint
Weidong Tian,Zimu Zhu

This paper studies an optimal investing problem for a retiree facing longevity risk and living standard risk. We formulate the investing problem as a portfolio choice problem under a time-varying risk capacity constraint. We derive the optimal investment strategy under the specific condition on model parameters in terms of second-order ordinary differential equations. We demonstrate an endogenous number that measures the expected value to sustain the spending post-retirement. The optimal portfolio is nearly neutral to the stock market movement if the portfolio's value is higher than this number; but, if the portfolio is not worth enough to sustain the retirement spending, the retiree actively invests in the stock market for the higher expected return. Besides, we solve an optimal portfolio choice problem under a leverage constraint and show that the optimal portfolio would lose significantly in stressed markets. This paper shows that the time-varying risk capacity constraint has important implications for asset allocation in retirement.

Power Trades and Network Congestion Externalities
Nayara Aguiar,Indraneel Chakraborty,Vijay Gupta

As power generation by renewable sources increases, power transmission patterns over the electric grid change. We show that due to physical laws, these new transmission patterns lead to non-intuitive grid congestion externalities. We derive the conditions under which network externalities due to power trades occur. Calibration shows that each additional unit of power traded between northern and western Europe reduces transmission capacity for the southern and eastern regions by 27% per unit traded. Given such externalities, new investments in the electric grid infrastructure cannot be made piecemeal. Power transit fares can help finance investment in regions facing network congestion externalities.

Reserves and Risk: Evidence from China
Fatum, Rasmus,Hattori, Takahiro,Yamamoto, Yohei
We consider if the Chinese accumulation of reserves is associated with unintended consequences in the form of increased private sector risk taking. Using sovereign credit default swap spreads and stock index prices as indicators of risk taking, we provide evidence to suggest that as reserve holdings increase, so does the willingness of the private sector to take on more risk. This is an important finding that adds credence to the suggestion that insurance through costly reserves, to be used in the event of a crisis, may lead to private sector actions that in and of themselves make it more likely that this insurance will be used.

Scenes from a Monopoly: Renewable Resources and Quickest Detection of Regime Shifts
Neha Deopa,Daniele Rinaldo

We study the stochastic dynamics of a renewable resource harvested by a monopolist facing a downward sloping demand curve. We introduce a framework where harvesting sequentially affects the resource's potential to regenerate, resulting in an endogenous ecological regime shift. In a multi-period setting, the firm's objective is to find the profit-maximizing harvesting policy while simultaneously detecting in the quickest time possible the change in regime. Solving analytically, we show that a negative regime shift induces an aggressive extraction behaviour due to shorter detection periods, creating a sense of urgency, and higher markup in prices. Precautionary behaviour can result due to decreasing resource rent. We study the probability of extinction and show the emergence of catastrophe risk which can be both reversible and irreversible.

Shadow Banking in China Compared to Other Countries
Allen, Franklin,Gu, Xian
China’s shadow banking has been rising rapidly in the last decade, mainly driven by regulations for banks, the Fiscal Stimulus Plan in 2008, and credit constraints in restrictive industries. This sector has continued growing although the regulators repeatedly attempted to impose new regulations on banks and non-banks. The existence of shadow banking fulfills the high demand for funding. The standard view is that it poses risks to financial stability. However, in China this is not necessarily the case. Entrusted loans, implicit guarantees from non-banks, banks or government may provide a second-best arrangement in funding risky projects and improving welfare.

Shining a Light in a Dark Corner: EDGAR Search Activity Reveals the Strategically Leaked Plans of Activist Investors
Flugum, Ryan,Lee, Choonsik,Souther, Matthew E.
We document a network of information flow between activists and other investors during the 10 days prior to the announcement of a campaign. We use EDGAR search activity matched to institutional investor IP addresses to identify investors who persistently download information on an individual activist’s campaign targets in the days prior to that activist’s 13D disclosures. This pattern of informed EDGAR access suggests leaked information from the activist to the unaffiliated institutional investor, who is not named in the 13D filing. We find that the presence of these informed investors is associated with higher pre-13D turnover, higher post-13D returns, and an increased likelihood of the activist pursuing and winning a proxy fight.

Sig-SDEs model for quantitative finance
Imanol Perez Arribas,Cristopher Salvi,Lukasz Szpruch

Mathematical models, calibrated to data, have become ubiquitous to make key decision processes in modern quantitative finance. In this work, we propose a novel framework for data-driven model selection by integrating a classical quantitative setup with a generative modelling approach. Leveraging the properties of the signature, a well-known path-transform from stochastic analysis that recently emerged as leading machine learning technology for learning time-series data, we develop the Sig-SDE model. Sig-SDE provides a new perspective on neural SDEs and can be calibrated to exotic financial products that depend, in a non-linear way, on the whole trajectory of asset prices. Furthermore, we our approach enables to consistently calibrate under the pricing measure $\mathbb Q$ and real-world measure $\mathbb P$. Finally, we demonstrate the ability of Sig-SDE to simulate future possible market scenarios needed for computing risk profiles or hedging strategies. Importantly, this new model is underpinned by rigorous mathematical analysis, that under appropriate conditions provides theoretical guarantees for convergence of the presented algorithms.

Stress Testing as a Tool for Monitoring and Modelling the Dynamics of Business Activity of Manufacturing Enterprises in Russia in the Face of Market Shocks: Short-term Scenarios of Industry Tendencies
Lola, Inna,Manukov, Anton,Bakeev, Murat
The article proposes a methodology for using macro-level stress testing based on the results of business tendency surveys to study possible scenarios for the development of crisis dynamics triggered by external unforeseen supply and demand shocks, as in the case of the COVID-19 pandemic, as well as a review of existing approaches in the field of stress testing and building stress indices with an emphasis on methods based on vector autoregressive models and their various modifications.The basis for empirical calculations is data from business tendency surveys of the leaders of Russian manufacturing enterprises, reflecting their combined estimates of the current state of business activity. Based on the results of business tendency surveys, four composite indices were formed reflecting various aspects of business activity of enterprises: demand index, production index, finance index and employment index. Index values calculated monthly from 2008 to March 2020 were used to build the Bayesian vector autoregressive model (BVAR). This model was used to predict the dynamics of indices under the condition of four possible shock scenarios: short-term shock, V-shaped shock, W-shaped shock and U-shaped shock. Moreover, for each of the scenarios, cases of a shock of demand, a shock of production, and a simultaneous shock of demand and production were separately considered.The results indicated the key role of demand in the dynamics of all the indices under consideration, the W-shaped shock, as the worst of the considered scenarios, as well as the relatively greater sensitivity of the employment index to the demand index and the finance index to the production index.

Tail Granger Causalities and Where to Find Them: Extreme Risk Spillovers vs Spurious Linkages
Mazzarisi, Piero,Zaoli, Silvia,Campajola, Carlo,Lillo, Fabrizio
Identifying risk spillovers in financial markets is of great importance for assessing systemic risk and portfolio management. Granger causality in tail (or in risk) tests whether past extreme events of a time series help predicting future extreme events of another time series. The topology and connectedness of networks built with Granger causality in tail can be used to measure systemic risk and to identify risk transmitters. Here we introduce a novel test of Granger causality in tail which adopts the likelihood ratio statistic and is based on the multivariate generalization of a discrete autoregressive process for binary time series describing the sequence of extreme events of the underlying price dynamics. The proposed test has very good size and power in finite samples, especially for large sample size, allows inferring the correct time scale at which the causal interaction takes place, and it is flexible enough for multivariate extension when more than two time series are considered in order to decrease false detections as spurious effect of neglected variables. An extensive simulation study shows the performances of the proposed method with a large variety of data generating processes and it introduces also the comparison with the test of Granger causality in tail by [Hong et al., 2009]. We report both advantages and drawbacks of the different approaches, pointing out some crucial aspects related to the false detections of Granger causality for tail events. An empirical application to high frequency data of a portfolio of US stocks highlights the merits of our novel approach.

Tail Risk Transmission: A Study of Iran Food Industry
Mojtahedi, Fatemeh,Mojaverian, Seyed Mojtaba,Ahelegbey, Daniel Felix,Giudici, Paolo
This paper extends the extreme downside correlations and hedge (EDC and EDH) methodology of Harris et al. (2019) to model the tail risk co-movement of financial assets under severe firm-level and market conditions. The model is applied to analyze both systematic and systemic exposures in the Iranian food industry. The empirical application address the following questions: 1) which food company is the safest for investors to diversify their investment, and 2) which companies are the risk ``transmitters'' and ``receivers'', especially in turbulent times. To this end, we sampled the time series of 11 manufacturing companies and proxy the market indicator with the food industry index, all of which are publicly listed on the Tehran Stock Exchange (TSE). The data covers daily close prices from October 5, 2015, to January 15, 2020. The systematic analysis reveals a positive and statistically significant relationship between the tail risk of the companies and the market index. The centrality analysis of the systemic exposures reveals Mahram Manufacturing as the safest and Behshahr Industries as the riskiest company. We also find evidence that W.Azar.Pegah is the main ``transmitter'' of tail risk, while Pegah.Fars.Co is the main ``receiver'' of risk.

The Effects of Board Structure on Corporate Performance: Evidence from East African Frontier Markets
Guney, Yilmaz,Karpuz, Ahmet,Komba, Gabriel
The effectiveness of the well-known corporate governance practices may not be universal due to fundamental differences in the environments under which firms operate. By using hand-collected data from all the non-financial firms listed on the unexplored East African frontier markets (i.e., Kenya, Tanzania and Uganda), we examine the effect of board characteristics on the performance of firms. Our results show that board size has a negative and significant effect on firm performance. The presences of foreigners and civil servants on the board play positive roles on financial performance, where the agency and resource dependence theories apply. Further, we find that board members with higher education also contribute to firm performance. These findings still hold when we consider the 2008-2009 financial crisis period. Overall, we show that in a business climate where ownership is largely dominated by few shareholders, the conventional governance mechanisms do not work effectively.

The Hyperbolic Geometry of Financial Networks
Keller-Ressel, Martin,Nargang, Stephanie
Based on data from the European banking stress tests of 2014, 2016 and the transparency exercise of 2018 we demonstrate for the first time that the latent geometry of financial networks can be well-represented by geometry of negative curvature, i.e., by hyperbolic geometry. This allows us to connect the network structure to the popularity-vs-similarity model of Papdopoulos et al., which is based on the Poincaré disc model of hyperbolic geometry. We show that the latent dimensions of `popularity' and `similarity' in this model are strongly associated to systemic importance and to geographic subdivisions of the banking system. In a longitudinal analysis over the time span from 2014 to 2018 we find that the systemic importance of individual banks has remained rather stable, while the peripheral community structure exhibits more (but still moderate) variability.

The Impact of M&A on Performance: Alternative Measures of Rates of Profit
Meeks, Geoff,Meeks, Jaqueline
Previous studies of the impact of M&A on performance have employed a range of measures of “profitability” or “rate of return”. Sometimes they have provided little in the way of rationalization; and sometimes the most appropriate measures have not been deployed for testing the chosen hypothesis, or supporting the final inferences. Here we explore a range of measures, their relation one to another, and caveats to their use in assessing operating efficiency or in monitoring the gains to shareholders. We discuss the profit margin, the return on net assets, the return on equity, earnings per share, and the total shareholder return.We show that the reported change in margin following M&A will, other things equal, overstate any improvement in operating performance where the M&A increases vertical integration. We analyse the difference between the accounting return on net assets and the accounting return on equity, examining the impact of associated changes in capital structure and/or tax arrangements: we report a consequent tendency for the return on equity (and earnings per share, but not the return on net assets) to overstate any improvement in operating performance after M&A. We describe the difference between the accounting return on equity and the total shareholder return, exploring the impact on the latter of changes in stock market perceptions of the combination’s prospects.

The Impact of Naked Short Selling on the Securities Lending and Equity Market
Lecce, Steven,Lepone, Andrew,McKenzie, Michael D.,Segara, Reuben
This paper examines the impact of naked short selling on equity markets where it is restricted to securities on an approved list. Consistent with Miller's (1977) intuition, stocks with the highest dispersion of opinions and short sale constraints are the only stocks to exhibit significant and negative abnormal returns in the post-event period. We also find slightly higher stock return volatility and a small reduction in liquidity when naked short sales are allowed. Overall, it impairs market quality (liquidity and volatility), although there appears to be some improvement in price efficiency in stocks with high short sale constraints.

The Impact of Trading Halts on Liquidity and Price Volatility: Evidence From the Australian Stock Exchange
Frino, Alex,Lecce, Steven,Segara, Reuben
This study examines market behaviour around trading halts associated with information releases on the Australian Stock Exchange, which operates an open electronic limit order book. Using the Lee, Ready and Seguin (1994) pseudo-halt methodology, we find trading halts increase both volume and price volatility. Trading halts also increase bid-ask spreads and reduce market depth at the best-quotes in the immediate post-halt period. The results of this study imply that trading halts impair rather than improve market quality in markets that operate open electronic limit order books.

The Importance of Cognitive Domains and the Returns to Schooling in South Africa: Evidence from Two Labor Surveys
Plamen Nikolov,Nusrat Jimi

Numerous studies have considered the important role of cognition in estimating the returns to schooling. How cognitive abilities affect schooling may have important policy implications, especially in developing countries during periods of increasing educational attainment. Using two longitudinal labor surveys that collect direct proxy measures of cognitive skills, we study the importance of specific cognitive domains for the returns to schooling in two samples. We instrument for schooling levels and we find that each additional year of schooling leads to an increase in earnings by approximately 18-20 percent. Furthermore, we estimate and demonstrate the importance of specific cognitive domains in the classical Mincer equation. We find that executive functioning skills are important drivers of earnings in the rural sample, whereas higher-order cognitive skills are more important for determining earnings in the urban sample.

The Information Content of NAV Estimates
Chacon, Ryan,French, Dan,Pukthuanthong, Kuntara
This paper investigates whether analysts’ estimates of firm fundamental value transmit unique information to security markets. Previous work has not studied analyst value estimates because of the scarcity of the release of such data. This study circumvents that limitation by considering the one type of firm for which a large sample of value estimates, known as the net asset value (NAV), exists: Real Estate Investment Trusts (REITs). Using a sample of 200 Equity REITs from 2001 to 2015, we document significant abnormal returns and share turnover on the announcement date of NAV revisions. This response is consistent with market reactions to announcements of other types of analysts’ estimates: earnings forecasts, price targets, and buy/sell recommendations. Our findings remain significant after controlling for these, suggesting the information contained in NAV revisions is incremental to that contained in other analyst estimates. Consistent with efficient information transmission, the market absorbs this new information quickly and completely.

The Sectoral Effects of Value-Added Tax: Evidence from UAE Stock Markets
Gopakumar, Anagha Ann
This paper investigates the impact of 19 announcements relating to the introduction of value-added tax (VAT) in the United Arab Emirates (UAE), on the equities listed on Abu Dhabi Stock Exchange (ADX). Using a well-established event study methodology applied on daily data over the period from 2016 to 2018, a sector-wise assessment of the value constructiveness or destructiveness of these announcements is conducted. Significant sectoral differences in abnormal returns are expected, with industries like insurance and retail showing higher sensitivity. Some announcements are also expected to have a more substantial impact than the rest, irrespective of sectors. These results are highly valuable as a source of information regarding the sectoral effects of VAT in the UAE, as well as a reference for the possible impact of VAT introduction in other countries in the Gulf region and the rest of the world.

The impact of COVID-19 on the UK fresh food supply chain
Rebecca Mitchell,Roger Maull,Simon Pearson,Steve Brewer,Martin Collison

The resilience of the food supply chain is a matter of critical importance, both for national security and broader societal well bring. COVID19 has presented a test to the current system, as well as means by which to explore whether the UK's food supply chain will be resilient to future disruptions. In the face of a growing need to ensure that food supply is more environmentally sustainable and socially just, COVOD19 also represents an opportunity to consider the ability of the system to innovative, and its capacity for change. The purpose of this case based study is to explore the response and resilience of the UK fruit and vegetable food supply chain to COVID19, and to assess this empirical evidence in the context of a resilience framework based on the adaptive cycle. To achieve this we reviewed secondary data associated with changes to retail demand, conducted interviews with 23 organisations associated with supply to this market, and conducted four video workshops with 80 organisations representing half of the UK fresh produce community. The results highlight that, despite significant disruption, the retail dominated fresh food supply chain has demonstrated a high degree of resilience. In the context of the adaptive cycle, the system has shown signs of being stuck in a rigidity trap, as yet unable to exploit more radical innovations that may also assist in addressing other drivers for change. This has highlighted the significant role that innovation and R&D communities will need to play in enabling the supply chain to imagine and implement alternative future states post COVID.

The impacts of asymmetry on modeling and forecasting realized volatility in Japanese stock markets
Daiki Maki,Yasushi Ota

This study investigates the impacts of asymmetry on the modeling and forecasting of realized volatility in the Japanese futures and spot stock markets. We employ heterogeneous autoregressive (HAR) models allowing for three types of asymmetry: positive and negative realized semivariance (RSV), asymmetric jumps, and leverage effects. The estimation results show that leverage effects clearly influence the modeling of realized volatility models. Leverage effects exist for both the spot and futures markets in the Nikkei 225. Although realized semivariance aids better modeling, the estimations of RSV models depend on whether these models have leverage effects. Asymmetric jump components do not have a clear influence on realized volatility models. While leverage effects and realized semivariance also improve the out-of-sample forecast performance of volatility models, asymmetric jumps are not useful for predictive ability. The empirical results of this study indicate that asymmetric information, in particular, leverage effects and realized semivariance, yield better modeling and more accurate forecast performance. Accordingly, asymmetric information should be included when we model and forecast the realized volatility of Japanese stock markets.

Toxic Hedging
Nimalendran, Mahendrarajah,Rzayev, Khaladdin,Sagade, Satchit
We investigate the role of high-frequency traders (HFTs) in option market making. We show that, overall, HFTs in the underlying market increase the spread and reduce liquidity in option markets through their liquidity-demanding orders. By contrast, the option spread is not impacted by the additional hedging opportunities stemming from HFTs’ liquidity-providing orders because they impose on the option market maker the risk of trading at stale prices in a cross-market setting.

Volatility Forecasts Embedded in the Prices of Crude-Oil Options
Gilder, Dudley,Tsiaras, Leonidas
This paper evaluates and compares the ability of alternative option-implied volatility measures to forecast the monthly realized volatility of crude-oil returns. We find that a corridor implied volatility measure that aggregates information from a narrow range of option contracts consistently outperforms forecasts obtained by the popular Black-Scholes and model-free volatility expectations, as well as those generated by a high-frequency realized volatility model. In particular, this measure ranks favorably in all regression-based tests, delivers the lowest forecast errors under either symmetric or asymmetric loss functions, and generates economically significant gains in volatility timing exercises. Our results also show that the CBOE's "oil-VIX" (OVX) index performs poorly, as it routinely produces the least accurate forecasts.

When to sell an asset amid anxiety about drawdowns
Neofytos Rodosthenous,Hongzhong Zhang

We consider risk averse investors with different levels of anxiety about asset price drawdowns. The latter is defined as the distance of the current price away from its best performance since inception. These drawdowns can increase either continuously or by jumps, and will contribute towards the investor's overall impatience when breaching the investor's private tolerance level. We investigate the unusual reactions of investors when aiming to sell an asset under such adverse market conditions. Mathematically, we study the optimal stopping of the utility of an asset sale with a random discounting that captures the investor's overall impatience. The random discounting is given by the cumulative amount of time spent by the drawdowns in an undesirable high region, fine tuned by the investor's personal tolerance and anxiety about drawdowns. We prove that in addition to the traditional take-profit sales, the real-life employed stop-loss orders and trailing stops may become part of the optimal selling strategy, depending on different personal characteristics. This paper thus provides insights on the effect of anxiety and its distinction with traditional risk aversion on decision making.