Research articles for the 2021-03-24

A Dynamic Factor Model Applied to Investor Sentiment in the European Context
Nogueira Reis, Pedro,Pinho, Carlos
This paper proposes an Investor Sentiment Index for the European market and tests its predictability power over returns and volatility. The constructed Investor Sentiment Index for Europe draws upon three well-established and two recent individual sentiment proxies through a novel dynamic factor modeling addressed to behavioral finance. The index is obtained through an extended period of analysis and validated with other sentiment index measures. The work relies on individual sentiment proxies based on a dynamic factor model and tests it using a TGARCH model for volatility and returns. It carries out an in-sample and out-of-sample analysis to examine this sentiment index’s forecasting power over returns sustained on a recursive rolling window prediction against Fama and French’s three-factor model. The findings demonstrate that the proposed index closely predicts STOXX600 variance and returns and confirms a strong spillover effect between European and US stock markets. This study also concludes that the proposed European Sentiment Index is a valid alternative method for investors to monitor and predict market behaviors. The developed sentiment measure is a vital market prediction movement tool for financial information providers, investors, bankers, and financial analysts. The research combines the sentiment index with a TGARCH approach over the extended period of analysis and validates the method with other sentiment index measures. An in-sample and out-of-sample study confirms the predictive power of this work’s sentiment over returns compared to Fama and French’s three-factor model.

A Dynamic Factor Model for Forecasting House Prices in Belgium
Emiris, Marina
The paper forecasts the residential property price index in Belgium with a dynamic factor model (DFM) estimated with a dataset of macro-economic variables describing the Belgian and euro area economy. The model is validated with out-of-sample forecasts which are obtained recursively over an expanding window over the period 2000q1-2012q4. We illustrate how the model reads information from mortgage loans, interest rates, GDP and inflation to revise the residential property price forecast as a result of a change in assumptions for the future paths of these variables.

A New Approach to Minimal Variance Hedging of European Options
Hess, Markus
This paper addresses the following question: How can a financial institution, which has issued a European option, optimally hedge the payoff of this option by investing into the underlying stock and into the option itself? Here, optimality is measured in terms of minimal variance and the associated optimal hedging portfolio is derived by a sufficient stochastic maximum principle. We further obtain a pricing formula for general European options by an application of Fourier transform methods and deduce the time dynamics of the stochastic option price process. We finally apply our theoretical results to several practical examples.

A Research on Cross-sectional Return Dispersion and Volatility of US Stock Market during COVID-19
Jiawei Du

We studied the volatility and cross-sectional return dispersion effect of S&P Health Care Sector under the covid-19 epidemic. We innovatively used the Google index to proxy the impact of the epidemic and modeled the volatility. We also studied the influencing factors of the log-return of S&P Energy Sector and S&P Health Care Sector. We found that volatility is significantly affected by both the epidemic and cross-sectional return dispersion, and the coefficients in front of them are all positive, which means that the herding behaviour did not exist and as the cross-sectional return dispersion increases and the epidemic becomes more severe, the volatility of stock returns is also increasing. We also found that the epidemic has a significant negative impact on the return of the energy sector, and finally we provided our suggestions to investors.

Additional Materials for Macro-Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models
Cheng, Xu,Dou, Winston,Liao, Zhipeng
This note contains additional technical details of Cheng, Dou, and Liao (2020). Section A provides the proofs of several lemmas on the asymptotic convergence of the random components in the test statistic and the conditional critical value. Section B verifies the bounded Lipschitz properties of the test statistic and the conditional critical value, which are used to show their weak convergence in large sample. Section C includes some auxiliary lemmas. Section D derives the Euler equations that serve as the asset pricing moment conditions in the long-run risk model and the disaster risk model. Section E considers the long-run risk model and shows that the Gaussian limit is an innocuous assumption. Section F provides derivations for the time-varying disaster risk model in the empirical application of the paper.The full-text version of this paper can be found at:

Block Diversity and Governance
Israelsen, Ryan D.,Schwartz-Ziv, Miriam,Weston, James
We show that different kinds of blockholders drive different forms of corporate governance. Nonfinancial blockholders are six times more likely to self-identify as active shareholders relative to financial blockholders. Textual analysis of regulatory filings reveal that nonfinancial blocks intend to govern through voice rather than exit. Firms with nonfinancial blockholders are more likely to have corporate governance practices that reflect active governance through shareholder voice rather than the threat of exit. We document a strong positive announcement return for nonfinancial blockholders, especially in small, volatile, and illiquid firms where the marginal benefit of monitoring via voice may be larger.

CEO Inside Debt and Innovation
Nguyen, Ha,Lu, Helen,Marsden, Alastair
This study examines the effect of CEO inside debt compensation on firm innovation. CEO inside debt compensation comprises deferred compensation and pension benefits. We find that CEO pension benefits negatively and significantly impact the number of patent applications in the following year and the number of patents and citations over a three-year time horizon. CEO pension benefits are also significantly and negatively associated with future innovation efficiency, which is measured by the firm’s research quotient (Knott, 2008). The negative association between CEO inside debt compensation and the firm’s future innovation is robust to endogeneity concerns.

Characterisation of honest times and optional semimartingales of class-($\Sigma$)
Libo Li

Given a finite honest time, we first derive representations of the additive and the multiplicative decomposition of its Azema optional supermartingale in terms of the drawdown and the relative drawdown of some optional supermartingales with continuous running supremum. The multiplicative representation then allows us to give a characterisation of finite honest times using a family of non-negative optional supermartingales with continuous running supremum which converges to zero at infinity. Then we extend the notion of semimartingales of class-($\Sigma$) by allowing for jumps in its finite variation part of the semimartingale decomposition. This allows one to establish the Madan-Roynette-Yor option pricing formula for a larger class of processes, and we apply the extended formula to the construction of finite honest times.

Climate Change, Analyst Forecasts, and Market Behavior
Cuculiza, Carina,Kumar, Alok,Xin, Wei ,Zhang, Chendi
This study examines whether sell-side equity analysts help the market assimilate information contained in global climate change. Using a new measure of firm sensitivity to climate change, we show that analysts located in states where firms exhibit greater sensitivity to abnormal temperature changes issue relatively less optimistic and more accurate forecasts in periods following large temperature increases. These effects are stronger for firms that are more sensitive to temperature changes. High temperature sensitivity firms also have lower consensus forecasts and higher earnings surprises, which generate higher stock market reaction following earnings announcements. Collectively, the evidence suggests that certain sell-side equity analysts incorporate news about climate change in their earnings forecasts and, consequently, earnings information is incorporated into prices quicker.

Co-Creation of Innovative Gamification Based Learning: A Case of Synchronous Partnership
Nicholas Dacre,Vasilis Gkogkidis,Peter Jenkins

In higher education, gamification offers the prospect of providing a pivotal shift from traditional asynchronous forms of engagement, to developing methods to foster greater levels of synchronous interactivity and partnership between and amongst teaching and learning stakeholders. The small vein of research that focuses on gamification in teaching and learning contexts, has mainly focused on the implementation of pre-determined game elements. This approach reflects a largely asynchronous approach to the development of learning practices in educational settings, thereby limiting stakeholder engagement in their design and adoption. Therefore, we draw on the theory of co-creation to examine the development process of gamification-based learning as a synchronous partnership between and amongst teaching and learning stakeholders. Empirical insights suggest that students gain a greater sense of partnership and inclusivity as part of a synchronous co-creation gamification-based learning development and implementation process.

Digital Finance, Green Finance and Social Finance: Is There a Link?
Ozili, Peterson K
Identifying the intersection between digital finance, green finance and social finance is important for promoting sustainable financial, social and environmental development. This paper suggests a link between digital finance, green finance and social finance. Using a simple conceptual model, I show that digital finance offers a smooth, efficient and seamless channel for individuals and corporations to fund social projects that deliver a social dividend, and green projects that promote a sustainable environment. The implication is that digital finance is both an enabler and a channel for efficient green financing and social financing.

Do Required Minimum Distribution 401(k) Rules Matter, and for Whom? Insights from a Lifecylce Model
Horneff, Vanya,Maurer, Raimond,Mitchell, Olivia S.
Tax-qualified vehicles helped U.S. private-sector workers accumulate $25Tr in retirement assets. An often-overlooked important institutional feature shaping decumulations from these retirement plans is the “Required Minimum Distribution” (RMD) regulation, requiring retirees to withdraw a minimum fraction from their retirement accounts or pay excise taxes on withdrawal shortfalls. Our calibrated lifecycle model measures the impact of RMD rules on financial behavior of heterogeneous households during their worklives and retirement. We show that proposed reforms to delay or eliminate the RMD rules should have little effects on consumption profiles but more impact on withdrawals and tax payments for households with bequest motives.

Does It Pay to be Socially Connected with Wall Street Brokerages? Evidence from Cost of Equity
Luong, Thanh Son,Qiu, Buhui,Wu, Ava
We show that social connections between a firm’s executives and directors and brokerages that follow the firm decrease the firm’s cost of equity. We use quasi-natural experiments to address endogeneity concerns and find that the uncovered effect of firm-brokerage social connections on cost of equity is likely causal. The effect is found to be more pronounced for firms with more soft information, opaque information environments, tight financial constraints, weak corporate monitoring, or high executive equity ownership. Further, consistent with the evidence on cost of equity, we find that firm-brokerage social connections reduce SEO underpricing, decrease information asymmetry in stock markets, and improve the firm’s equity valuation.

Dynamic industry uncertainty networks and the business cycle
Jozef Barunik,Mattia Bevilacqua,Robert Faff

We argue that uncertainty network structures extracted from option prices contain valuable information for business cycles. Classifying U.S. industries according to their contribution to system-related uncertainty across business cycles, we uncover an uncertainty hub role for the communications, industrials and information technology sectors, while shocks to materials, real estate and utilities do not create strong linkages in the network. Moreover, we find that this ex-ante network of uncertainty is a useful predictor of business cycles, especially when it is based on uncertainty hubs. The industry uncertainty network behaves counter-cyclically in that a tighter network tends to associate with future business cycle contractions.

Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics
Ayoub Ammy-Driss,Matthieu Garcin

This paper investigates the impact of COVID-19 on financial markets. It focuses on the evolution of the market efficiency, using two efficiency indicators: the Hurst exponent and the memory parameter of a fractional L\'evy-stable motion. The second approach combines, in the same model of dynamic, an alpha-stable distribution and a dependence structure between price returns. We provide a dynamic estimation method for the two efficiency indicators. This method introduces a free parameter, the discount factor, which we select so as to get the best alpha-stable density forecasts for observed price returns. The application to stock indices during the COVID-19 crisis shows a strong loss of efficiency for US indices. On the opposite, Asian and Australian indices seem less affected and the inefficiency of these markets during the COVID-19 crisis is even questionable.

Equity Factor Timing With Kalman Filter
Zhang, Kai
Extensive research literature has shown that equity factor premia is not constant over time. With the broad adoption of factor investing among active managers, to generate differentiated market views and returns, factor or style timing remains as one attractive meaning. We present an adaptive linear factor model to capture time-varying factor risk premia and discuss its application in equity portfolio investment. The model framework that allows time-varying factor returns can potentially capture more returns and allows an investor to understand the changes in cross-sectional factor returns. We estimate model coefficients through a Kalman filter model and discuss the results with an empirical example.

Evaluating Policies Early in a Pandemic: Bounding Policy Effects with Nonrandomly Missing Data
Brantly Callaway,Tong Li

During the early stages of the Covid-19 pandemic, national and local governments introduced a large number of policies, particularly non-pharmaceutical interventions, to combat the spread of Covid-19. Understanding the effects that these policies had (both on Covid-19 cases and on other outcomes) is particularly challenging though because (i) Covid-19 testing was not widely available, (ii) the availability of tests varied across locations, and (iii) the tests that were available were generally targeted towards individuals meeting certain eligibility criteria. In this paper, we propose a new approach to evaluate the effect of policies early in the pandemic that accommodates limited and nonrandom testing. Our approach results in (generally informative) bounds on the effect of the policy on actual cases and in point identification of the effect of the policy on other outcomes. We apply our approach to study the effect of Tennessee's open-testing policy during the early stage of the pandemic. For this policy, we find suggestive evidence that the policy decreased the number of Covid-19 cases in the state relative to what they would have been if the policy had not been implemented.

Fat Tails, Serial Dependence, and Implied Volatility Connections
Ellington, Michael
This paper assesses the role of fat tails and serial dependence for implied volatility network connections among equity and commodity markets using Bayesian VAR models. I provide network connection measures over the short-, medium-, and long-term. I then study the information content of implied volatility network connections for predicting underlying asset returns and whether conventional risk factors explain variation of portfolios that sort on directional connections. Results show that network connectedness measures forecast underlying asset returns, and that one can construct short-term and medium-term portfolios that hedge against mispricing anomalies at horizons of less than one month.

HighFrequencyCovariance: A Julia Package for Estimating Covariance Matrices Using High Frequency Financial Data
Baumann, Stuart,Klymak, Margaryta
High frequency data typically exhibit asynchronous trading and microstructure noise, which can bias the covariances estimated by standard estimators. While a number of specialised estimators have been developed, they have had limited availability in open source software. HighFrequencyCovariance is the first Julia package which implements specialised estimators for volatility, correlation and covariance using high frequency financial data. It also implements complementary algorithms for matrix regularisation as well as functions to estimate a covariance matrix blockwise and combine the results. This paper first presents the issues associated with exploiting high frequency financial data. We then describe the volatility, covariance and regularisation algorithms and demonstrate their implementation in the HighFrequencyCovariance package. We perform a Monte Carlo experiment, which shows the accuracy gains that are possible in different settings. Finally, we show that different estimators can be combined to form an ensemble estimator which can produce more accurate estimates with lower variance than any of the individual estimators.

How Did the Asset Markets Change after the Global Financial Crisis?
Chang, Kuang-Liang,Leung, Charles K.
The Global Financial Crisis (GFC) changes the relative economic riskiness and risk-adjusted-performance of different asset markets. While the empirical distribution for stock return shifted to the right and became more concentrated around the mean after the GFC, the real estate market counterparts moved to the left and became more spread out. The economic risk of the OFHEO and Case-Shiller housing indices was smaller than the counterpart of the equity REIT (EREITs) market before the financial crisis, it substantially increased. Also, the economic performance of the OFHEO and Case-Shiller housing indices decreased after the financial crisis. They are below the performance indices of the stock and EREITs markets. The ex-post real estate premium vanishes. If we presume the "best model" to be the same before and after the GFC, we could severely misestimate the risk after the GFC.

How to Motivate and Engage Generation Clash of Clans at Work? Emergent Properties of Business Gamification Elements in the Digital Economy
Nicholas Dacre,Panos Constantinides,Joe Nandhakumar

Organisations are currently lacking in developing and implementing business systems in meaningful ways to motivate and engage their staff. This is particularly salient as the average employee spends eleven cumulative years of their life at work, however less than one third of the workforce are actually engaged in their duties throughout their career. Such low levels of engagement are particularly prominent with younger employees, referred to as Generation Y (GenY), who are the least engaged of all groups at work. However, they will dedicate around five cumulative years of their life immersed playing video games such as Clash of Clans, whether for social, competitive, extrinsic, or intrinsic motivational factors.

Using behavioural concepts derived from video games, and applying game design elements in business systems to motivate employees in the digital economy, is a concept which has come to be recognised as Business Gamification. Thus, the purpose of this research paper is to further our understanding of game design elements for business, and investigate their properties from design to implementation in gamified systems. Following a two-year ethnographic style study with both a system development, and a communication agency largely staffed with GenY employees, findings suggest properties in game design elements are emergent and temporal in their instantiations.

Identification at the Zero Lower Bound
Sophocles Mavroeidis

I show that the Zero Lower Bound (ZLB) on interest rates can be used to identify the causal effects of monetary policy. Identification depends on the extent to which the ZLB limits the efficacy of monetary policy. I develop a general econometric methodology for the identification and estimation of structural vector autoregressions (SVARs) with an occasionally binding constraint. The method provides a simple way to test the efficacy of unconventional policies, modelled via a `shadow rate'. I apply this method to U.S. monetary policy using a three-equation SVAR model of inflation, unemployment and the federal funds rate. I reject the null hypothesis that unconventional monetary policy has no effect at the ZLB, but find some evidence that it is not as effective as conventional monetary policy.

Interpretable ML-driven Strategy for Automated Trading Pattern Extraction
Artur Sokolovsky,Luca Arnaboldi,Jaume Bacardit,Thomas Gross

Financial markets are a source of non-stationary multidimensional time series which has been drawing attention for decades. Each financial instrument has its specific changing over time properties, making their analysis a complex task. Improvement of understanding and development of methods for financial time series analysis is essential for successful operation on financial markets. In this study we propose a volume-based data pre-processing method for making financial time series more suitable for machine learning pipelines. We use a statistical approach for assessing the performance of the method. Namely, we formally state the hypotheses, set up associated classification tasks, compute effect sizes with confidence intervals, and run statistical tests to validate the hypotheses. We additionally assess the trading performance of the proposed method on historical data and compare it to a previously published approach. Our analysis shows that the proposed volume-based method allows successful classification of the financial time series patterns, and also leads to better classification performance than a price action-based method, excelling specifically on more liquid financial instruments. Finally, we propose an approach for obtaining feature interactions directly from tree-based models on example of CatBoost estimator, as well as formally assess the relatedness of the proposed approach and SHAP feature interactions with a positive outcome.

Limit Theorems for Default Contagion and Systemic Risk
Amini, Hamed,Cao, Zhongyuan,Sulem, Agnes
We consider a general tractable model for default contagion and systemic risk in a heterogeneous financial network, subject to an exogenous macroeconomic shock. We show that, under some regularity assumptions, the default cascade model could be transferred to a death process problem represented by balls-and-bins model. We also reduce the dimension of the problem by classifying banks according to different types, in an appropriate type space. These types may be calibrated to real-world data by using machine learning techniques. We then state various limit theorems regarding the final size of default cascade over different types. In particular, under suitable assumptions on the degree and threshold distributions, we show that the final size of default cascade has asymptotically Gaussian fluctuations. We next state limit theorems for different system-wide wealth aggregation functions and show how the systemic risk measure, in a given stress test scenario, could be related to the structure and heterogeneity of financial networks. We finally show how these results could be used by a social planner to optimally target interventions during a financial crisis, with a budget constraint and under partial information of the financial network.

Making it normal for new enrollments: Effect of institutional and pandemic influence on selecting an engineering institution under the COVID-19 pandemic situation
Prashant Mahajan,Vaishali Patil

The COVID19 pandemic has forced Indian engineering institutions (EIs) to bring their previous half shut shades completely down. Fetching new admissions to EI campuses during the pandemic has become a now or never situation for EIs. During crisis situations, institutions have struggled to return to the normal track. The pandemic has drastically changed students behavior and family preferences due to mental stress and the emotional life attached to it. Consequently, it becomes a prerequisite, and emergencies need to examine the choice characteristics influencing the selection of EI during the COVID19 pandemic situation.

The purpose of this study is to critically examine institutional influence and pandemic influence due to COVID19 that affects students choice about an engineering institution (EI) and consequently to explore relationships between institutional and pandemic influence. The findings of this quantitative research, conducted through a self-reported survey, have revealed that institutional and pandemic influence have governed EI choice under the COVID19 pandemic. Second, pandemic influence is positively affected by institutional influence. The study demonstrated that EIs will have to reposition themselves to normalize pandemic influence by tuning institutional characteristics that regulate situational influence and new enrollments. It can be yardstick for policy makers to attract new enrollments under pandemic situations.

Market Efficient Portfolios in a Systemic Economy
Kerstin Awiszus,Agostino Capponi,Stefan Weber

We study the ex-ante minimization of market inefficiency, defined in terms of minimum deviation of market prices from fundamental values, from a centralized planner's perspective. Prices are pressured from exogenous trading actions of leverage targeting banks, which rebalance their portfolios in response to asset shocks. We characterize market inefficiency in terms of two key drivers, the banks' systemic significance and the statistical moments of asset shocks, and develop an explicit expression for the matrix of asset holdings which minimizes such inefficiency. Our analysis shows that to reduce inefficiencies, portfolio holdings should deviate more from a full diversification strategy if there is little heterogeneity in banks' systemic significance.

Measuring Corporate Investment Horizons and Identifying Short-Termism
Knetsch, Andreas
This paper proposes an empirical approach to capture investment horizons. I utilize this method to analyze short-termist investment. It relies on information which is not observable to investors in the period of investment and therefore considers the nature of short-termism as an agency problem. My empirical findings establish the validity of the introduced approach by relating it to an existing measure of investment horizons as well as multiple firm characteristics which are connected to short-termism. I observe that investment horizons are shorter for firms that inflate their reported income through real or accrual-based earnings management and for firms whose stock prices are more sensitive to earnings surprises. I also investigate which governance mechanisms are effective in curtailing short-termism. Managerial entrenchment, analyst coverage, institutional ownership, the effectiveness of the board of directors, and managerial long-term compensation all relate to longer investment horizons and thus less short-termism.

Modeling of crisis periods in stock markets
Apostolos Chalkis,Emmanouil Christoforou,Theodore Dalamagkas,Ioannis Z. Emiris

We exploit a recent computational framework to model and detect financial crises in stock markets, as well as shock events in cryptocurrency markets, which are characterized by a sudden or severe drop in prices. Our method manages to detect all past crises in the French industrial stock market starting with the crash of 1929, including financial crises after 1990 (e.g. dot-com bubble burst of 2000, stock market downturn of 2002), and all past crashes in the cryptocurrency market, namely in 2018, and also in 2020 due to covid-19. We leverage copulae clustering, based on the distance between probability distributions, in order to validate the reliability of the framework; we show that clusters contain copulae from similar market states such as normal states, or crises. Moreover, we propose a novel regression model that can detect successfully all past events using less than 10% of the information that the previous framework requires. We train our model by historical data on the industry assets, and we are able to detect all past shock events in the cryptocurrency market. Our tools provide the essential components of our software framework that offers fast and reliable detection, or even prediction, of shock events in stock and cryptocurrency markets of hundreds of assets.

Mostly electric assisted airplanes (MEAP) for regional aviation: A South Asian perspective
Vinamra Chaturvedi

Aircraft manufacturing relies on pre-order bookings. The configuration of the to be assembled aircraft is fixed by the design assisted market surveys. The sensitivity of the supply chain to the market conditions, makes, the relationship between the product (aircraft) and the associated service (aviation), precarious. Traditional model to mitigate this risk to profitability rely on increasing the scales of operations. However, the emergence of new standards of air quality monitoring and insistence on the implementation, demands additional corrective measures. In the quest for a solution, this research commentary establishes a link, between the airport taxes and the nature of the transporting unit. It warns, that merely, increasing the number of mid haulage range aircrafts (MHA) in the fleet, may not be enough, to overcome this challenge. In a two-pronged approach, the communication proposes, the use of mostly electric assisted air planes, and small sized airports as the key to solving this complex problem. As a side-note the appropriateness of South Asian region, as a test-bed for MEAP based aircrafts is also investigated. The success of this the idea can be potentially extended, to any other aviation friendly region of the world.

Portfolio Tilts using Views on Macroeconomic Regimes
Elkamhi, Redouane,Lee, Jacky S.H.,Salerno, Marco
Long-term investors rebalance their portfolios given their views on the investment landscape. Portfolio tilting is often implemented using investors' views on point estimates of asset expected returns which are notoriously difficult to estimate and lead to unstable portfolio weights. We avoid such shortcomings by providing a methodology that incorporates views on the likelihood of economic regimes (e.g., growth and inflation). Using data on equities, bonds and commodities, we show - both in simulation and empirically - that our approach generates stable portfolio weights and a performance that is minimally affected by forecast errors.

Pricing Energy Derivatives in Markets Driven by Tempered Stable and CGMY Processes of Ornstein-Uhlenbeck Type
Piergiacomo Sabino

In this study we consider the pricing of energy derivatives when the evolution of spot prices follows a tempered stable or a CGMY driven Ornstein- Uhlenbeck process. To this end, we first calculate the characteristic function of the transition law of such processes in closed form. This result is instrumental for the derivation of non-arbitrage conditions such that the spot dynamics is consistent with the forward curve. Moreover, based on the results of Cufaro Petroni and Sabino (2020), we also conceive efficient algorithms for the exact simulation of the skeleton of such processes and propose a novel procedure when they coincide with compound Poisson processes of Ornstein-Uhlenbeck type. We illustrate the applicability of the theoretical findings and the simulation algorithms in the context of the pricing different contracts namely, strips of daily call options, Asian options with European style and swing options. Finally, we present an extension to future markets.

Reconsideration of Value Investing: Evaluation Based on Perfect Foresight
Kudoh, Hideaki,Katayama, Daisuke,Takayanagi, Kentaro
Japanese equity value investing used to be known for its stable investment return that was rarely observed elsewhere in the world. However, similarly to the global decline in value investing, Japanese equity value investing, which has also fallen into a difficult situation. This article examines the past and current performance of value investing based on corporate earnings. The results of our study demonstrate that (1) from 2010 onward, even if a stock is a value stock based on both forecasted and realized earnings, the discount in valuation has not been subsequently corrected and (2) on the other hand, price formation in response to changes in realized earnings has functioned properly in all decades we examined. However, from 2018 onward, excess return was impossible to obtain both in Japan and in the U.S. even for stocks that are value stocks based on realized earnings or value stocks whose future earnings would increase. Although price formation of value stocks in the market has functioned correctly in the long run, we found that the pricing mechanism of the stock market has not worked properly in recent years. Therefore, the stock market may have been dysfunctional in recent years.

Robust Utility Maximization in a Multivariate Financial Market with Stochastic Drift
Jörn Sass,Dorothee Westphal

We study a utility maximization problem in a financial market with a stochastic drift process, combining a worst-case approach with filtering techniques. Drift processes are difficult to estimate from asset prices, and at the same time optimal strategies in portfolio optimization problems depend crucially on the drift. We approach this problem by setting up a worst-case optimization problem with a time-dependent uncertainty set for the drift. Investors assume that the worst possible drift process with values in the uncertainty set will occur. This leads to local optimization problems, and the resulting optimal strategy needs to be updated continuously in time. We prove a minimax theorem for the local optimization problems and derive the optimal strategy. Further, we show how an ellipsoidal uncertainty set can be defined based on filtering techniques and demonstrate that investors need to choose a robust strategy to be able to profit from additional information.

Shadow of Empire: British Consol Yields, 1703-2016
Dasgupta, Dipak
Political economy factors overshadow standard economic explanations of financial markets behavior. During 300 plus long years, Britain traversed from a small island nation to become the world’s biggest empire and financial capital by the 19th century, before the tide turned in the 20th century. Britain issued consols (consolidated annuities) or perpetual bonds starting in the 18th century to finance its public spending. These bonds carried a fixed face-value coupon interest rate, but yields varied as their prices changed, reflecting the financial market’s changing assessment of risk. Using Bank of England data, we find that traditional economic explanations, inflation and public debt, do not explain well these movements. Instead, using ‘cliometrics’, the study of history with statistical methods, we find that more fundamental political economy factors work better: the rise and fall of Empire, profits of Atlantic slave trade, wars, depressions, pound sterling’s loss of global reserve currency status, global financial crises, and salient in today’s context, pandemics. We analyze how yields on British consols over three hundred plus years mirrored these great events, as Britain rose and then waned in the shadow of empire. There are lessons for today’s ascendant and emerging powers, and our understanding of financial markets.

Short-termist Investment and Time Preferences
Breuer, Wolfgang,Knetsch, Andreas,Salzmann, Astrid Juliane
This paper investigates the effect of shareholder and manager time preferences on short-termist investment behavior. Our theoretical analysis shows that managerial future orientation curtails short-termism whereas shareholder patience exacerbates it. We test these predictions by comparing the effects of time preferences on investment horizons of listed and unlisted firms in a sample of European firms. Based on the assumption that unlisted firms suffer from less asymmetric information, the effects of future orientation on investment horizons that are exclusive to listed firms provide weak support for our hypotheses. When considering future orientation on a national level, we find some evidence for firms in more future-oriented countries investing more long-term oriented. We can however not confirm the widespread notion that firms in more future-oriented countries suffer from less short-termism.

Simple Diagnostics for Two-Way Fixed Effects
Pamela Jakiela

Difference-in-differences estimation is a widely used method of program evaluation. When treatment is implemented in different places at different times, researchers often use two-way fixed effects to control for location-specific and period-specific shocks. Such estimates can be severely biased when treatment effects change over time within treated units. I review the sources of this bias and propose several simple diagnostics for assessing its likely severity. I illustrate these tools through a case study of free primary education in Sub-Saharan Africa.

Smart-Beta Indices: Selecting Risk Exposures
Dugar, Amitabh
Stock selection and weighting schemes can be viewed as complimentary tools for accomplishing investment goals. Most smart beta indices are based on ad hoc choices of these two features made by an index provider. Investors can benefit from learning how to evaluate risk factors and disentangle the effects of stock selection and stock weighting.

SoK: Decentralized Exchanges (DEX) with Automated Market Maker (AMM) protocols
Jiahua Xu,Nazariy Vavryk,Krzysztof Paruch,Simon Cousaert

As an integral part of the Decentralized Finance (DeFi) ecosystem, Automated Market Maker (AMM) based Decentralized Exchanges (DEXs) have gained massive traction with the revived interest in blockchain and distributed ledger technology in general. Most prominently, the top six AMMs -- Uniswap, Balancer, Curve, Dodo, Bancor and Sushiswap -- hold in aggregate 15 billion USD worth of crypto-assets as of March 2021. Instead of matching the buy and sell sides, AMMs employ a peer-to-pool method and determine asset price algorithmically through a so-called conservation function. Compared to centralized exchanges, AMMs exhibit the apparent advantage of decentralization, automation and continuous liquidity. Nonetheless, AMMs typically feature drawbacks such as high slippage for traders and divergence loss for liquidity providers. In this work, we establish a general AMM framework describing the economics and formalizing the system's state-space representation. We employ our framework to systematically compare the mechanics of the top AMM protocols, deriving their slippage and divergence loss functions.

Sovereign Debt Ratchets and Welfare Destruction
DeMarzo, Peter M.,He, Zhiguo,Tourre, Fabrice
An impatient and risk-neutral government can sell bonds at any time to a more patient group of competitive lenders. The key problem: the government cannot commit to either a particular financing strategy, or a default strategy. Despite risk-neutrality, in equilibrium debt adjusts slowly towards a target debt-to-income level, exacerbating booms and busts. Most strikingly, for any debt maturity structure, the gains from trade are entirely dissipated when trading opportunities are continuous, as lenders compete with each other and the government competes with itself. Moreover, citizens who are more patient than their government are strictly harmed by the unrestricted borrowing. We fully characterize debt dynamics, ergodics, and comparative statics when income follows a geometric Brownian motion, and analyze several commitment devices that allow the sovereign to recapture some gains from trade: self-imposed restrictions on debt issuances and levels, as well as “market-imposed” discipline.

Statlig finansiering till småföretag? (Public Funding for Small Firms?)
Svensson, Roger
Swedish Abstract: SmÃ¥ och växande företag är viktiga för Sveriges tillväxt och för skapandet av nya arbetstillfällen. Eftersom nystartade företag samt smÃ¥ företag med riskfyllda teknikprojekt lider av begränsat kapital, är det inte orimligt att det skulle finnas fler smÃ¥företag som dessutom växte snabbare, om tillgÃ¥ngen pÃ¥ kapital vore bättre. Som Roger Svensson visar i den här rapporten stÃ¥r bÃ¥de dÃ¥liga regelverk och marknadsmisslyckanden i vägen för kapitaltillgÃ¥ngen för nÃ¥gra av de mindre företagen. Det främsta marknadsmisslyckandet som kan skapa kapitalbrist hos vissa smÃ¥företag bygger pÃ¥ asymmetrisk information och inkompletta kapitalmarknader. Det kan vara svÃ¥rt för externa finansiärer att avgöra vilka nystartade eller smÃ¥ bolag som det är värt att tillhandahÃ¥lla kapital till. Detta är speciellt fallet om verksamheten bygger pÃ¥ en ny produkt, innovation eller affärsidé som inte tidigare prövats av marknaden. I det läget kan det finnas skäl för offentlig finansiering att hjälpa till. Offentlig finansiering är legitimerad om â€" och endast om â€" det föreligger ett marknadsmisslyckande, och den fÃ¥r inte tränga ut privat kapital. Det innebär i praktiken att offentlig finansiering enbart ska finansiera smÃ¥ och riskfyllda projekt i tidiga faser. I dag är det emellertid sÃ¥ att det offentliga Ã¥tagandet gÃ¥r lÃ¥ngt utöver vad som är teoretiskt och empiriskt motiverat. De statliga VC-bolagen Fouriertransform och Inlandsinnovation är snarare förtäckta industri- och regionalstöd, och bör avvecklas. Industrifonden agerar i alldeles för sena faser och kan ocksÃ¥ avvecklas, eller stöpas om rejält. Regionalstöd gÃ¥r att motivera vid tillfälliga chocker, men de permanenta stöd vi har i dag kan ifrÃ¥gasättas. Almi:s smÃ¥företagslÃ¥n är bra vid ekonomisk kris men bör bantas rejält. En stor del av Norrlandsfondens lÃ¥n gÃ¥r till företag i alltför sena faser, och bör avvecklas eller bantas ner. I stället bör Almi:s innovationslÃ¥n expanderas, tillsammans med Almi Invests venture capital. Det är nämligen endast de tvÃ¥ som uteslutande gÃ¥r in med finansiering i smÃ¥ och riskfyllda projekt i tidiga faser. Men även olika skatteregler skapar snedvridna incitament för kapitalförsörjningen till smÃ¥företag. För det första försvÃ¥ras aktivt ägande i fÃ¥mansbolag genom 3:12-reglerna, vilket kan skapa en brist pÃ¥ sÃ¥ kallade affärsänglar. För det andra riskerar de nyskapade Investeringssparkontona att styra om pengar frÃ¥n onoterade till noterade bolag, och pÃ¥ sÃ¥ sätt Ã¥terigen missgynna mindre bolag. För det tredje dubbelbeskattas företagen genom att de först betalar bolagsskatt pÃ¥ vinsten och sedan utdelningsskatt när vinsterna delas ut. Detta skapar incitament för lÃ¥nefinansiering, vilket i sin tur kan vara svÃ¥rt för mindre företag att alls fÃ¥ tillgÃ¥ng till. För att pÃ¥ ett mer hÃ¥llbart sätt komma tillrätta med smÃ¥företags finansieringsbehov bör man avskaffa dubbelbeskattningen pÃ¥ aktier genom att utdelningsskatten tas bort. 3:12-reglerna är efter Ã¥tskilliga reformförsök ännu inte optimala och bör justeras, och dessutom bör man se över om ISK-konton ocksÃ¥ kan omfatta onoterade bolag.English Abstract: Small and growing companies are important for Sweden's growth and for the creation of new jobs. Since start-ups and small companies with risky technology projects suffer from limited capital financing, it is not unreasonable that there would be more small companies that also grew faster, if the supply of capital were better. Both poor regulations and market failures create obstacles for the capital supply for some of the smaller companies. The main market failure that creates capital shortages in some small businesses is based on asymmetric information and incomplete capital markets. It can be difficult for external financiers to determine which start-ups or small companies are worth providing capital to. This is especially the case if the business is based on a new product, innovation or business concept that has not previously been tested by the market. In that situation, there may be reasons to assist with public funding. Public funding is legitimized if - and only if - there is a market failure, and it must not crowd out private capital. In practice, this means that public funding should only fund small and risky projects in the early phases. Today, however, the public commitment in Sweden goes far beyond what is theoretically and empirically justified.

Synthetic Leverage and Fund Risk-Taking
Fricke, Daniel
Mutual fund risk-taking via active portfolio rebalancing varies both in the cross-section and over time. In this paper, I show that the same is true for funds' off-balance sheet risk-taking, even after controlling for on-balance sheet activities. For this purpose, I propose a novel measure of synthetic leverage, which can be estimated based on publicly available information. In the empirical application, I show that German equity funds have increased their risk-taking via synthetic leverage from mid-2015 up until early 2019. In the cross-section, I find that synthetically leveragedfunds tend to underperform and display higher levels of fragility.

Tax-Smart Portfolio Valuation and Performance Measurement
Kalotay, Andrew
The reported performance of a portfolio is consequential for both investors and managers. One component of the return calculation is the beginning and ending value of the portfolio. The standard in the industry is to calculate portfolio values from the market prices of the constituent securities. Assuming that the portfolio can be liquidated at these prices, in the absence of tax considerations the market value accurately represents the true value of the portfolio, and therefore the resulting measure of performance is uncontroversial. But what if the portfolio is taxable? Neither the market value nor the liquidation value accurately represents the true worth of a taxable portfolio. However, accurate values are essential to calculating the performance of mutual funds and ETFs. This is especially true for tax-exempt muni portfolios â€" interest is tax-free, but capital gains are taxable. We will explore three alternatives to pretax value: liquidation value, hold value, and the larger of these two, defined as tax-smart value. We recommend the tax-smart value to measure the performance of an actively managed portfolio.

Technical Note: Parameterised-Response Zero-Intelligence (PRZI) Traders
Dave Cliff

This brief technical note introduces PRZI (Parameterised-Response Zero Intelligence), a new form of zero-intelligence trader intended for use in simulation studies of auction markets. Like Gode & Sunder's classic Zero-Intelligence Constrained (ZIC) trader, PRZI generates quote-prices from a random distribution over some specified domain of discretely-valued allowable quote-prices. Unlike ZIC, which uses a uniform distribution to generate prices, the probability distribution in a PRZI trader is parameterised in such a way that its probability mass function (PMF) is determined by a real-valued control variable s in the range [-1.0, +1.0] that determines the strategy for that trader. When s is zero, a PRZI trader behaves identically to the ZIC strategy, with a flat/rectangular PMF; but when s is close to plus or minus one the PRZI trader's PMF becomes asymptotically maximally skewed to one extreme or the other of the price-range, thereby enabling the PRZI trader to act in the same way as the "Shaver" strategy (SHVR) or the "Giveaway" strategy (GVWY), both of which have recently been demonstrated to be surprisingly dominant over more sophisticated, and supposedly more profitable, trader-strategies that incorporate adaptive mechanisms and machine learning. Depending on the value of s, a PRZI trader will behave either as a ZIC, or as a SHVR, or as a GVWY, or as some hybrid strategy part-way between two of these three previously-reported strategies. The novel smoothly-varying strategy in PRZI has value in giving trader-agents plausibly useful "market impact" responses to imbalances in an auction-market's limit-order-book, and also allows for the study of co-adaptive dynamics in continuous strategy-spaces rather than the discrete spaces that have traditionally been studied in the literature.

Technology Adoption, Market Structure, and the Cost of Bank Intermediation
De Nicolo, Gianni,Presbitero, Andrea,Rebucci, Alessandro,Zhang, Gang
This paper studies the high and persistent U.S. cost of financial intermediation (CFI) documented by Philippon (2015) and its inverted U-shape behavior since the mid-1960s. We build a novel model of endogenous growth and bank intermediation and introduce imperfect bank competition, bank IT adoption and bank entry, and an occupational choice that determines the relative size of the labor force and the economy's average level of managerial ability. The interplay between verification costs, market structure, and occupational choice delivers implications for the CFI which are qualitatively consistent with the stylized facts of the U.S. economy. We find that the banking sector structure is the main determinant of the long-run level of the CFI. We also show that the U.S. productivity growth slowdown from the mid-1960s to the mid-1980s is a major driver of the simultaneous increase in the CFI and the number of banks during this period and their subsequent decline.

The Carrot and the Stick: Bank Bailouts and the Disciplining Role of Board Appointments
Mücke, Christian,Pelizzon, Loriana,Pezone, Vincenzo,Thakor, Anjan V.
This paper empirically examines the Capital Purchase program (CPP) under TARP that was usedby the U.S. government to bail out distressed banks with equity infusions. We hypothesize that a feature of the CPP, namely the ability of the government to appoint directors on the assisted bank’s board in case it missed six quarterly dividend payments, was a governance intrusion that banks would wish to avoid. Therefore, it would address both (i) the ex ante moral hazard that banks would take actions that increased the likelihood of a future government bailout as well as (ii) the ex post moral hazard that banks would undertake actions after receiving bailout funding that would increase the government’s risk exposure. We find evidence consistent with this hypothesis: in the empirical distribution of missed payments there is a sharp discontinuity at five and the probability of a sixth missed payment after missing five payments is sharply lower than the other transition probabilities. The appointment of government directors improves the bank’s profitability and reduces its risk. As a special case, the firing of Citicorp’s CEO in the third quarter of 2012 after the appointment of new directors on its board, pursuant to government participation in its common equity, induced a sharp exodus of assisted banks from the CPP.

The Contrarian Put
Chague, Fernando,Giovannetti, Bruno,Guimaraes, Bernardo
It is well-documented that retail investors like distressed stocks. We develop a quantitative model to study how this affects asset prices in equilibrium. We find that stocks will be overpriced even in normal times: in a distress scenario, the higher retail demand and short-selling costs yield a higher exit price for rational investors, effectively providing them with a put option. Our model is disciplined by a detailed dataset containing all retail trading and short-selling on OGX, a failed Brazilian oil giant popular among retail investors. We find that rational investors allow an overpricing of 6% in normal times because of the put option. The estimated average overpricing over almost two years is USD 1.7 billion.

The Current Chinese Global Supply Chain Monopoly and the Covid-19 Pandemic
George Rapciewicz Jr.,Dr. Donald Buresh

Because of the ongoing Covid-19 crisis, supply chain management performance seems to be struggling. The purpose of this paper is to examine a variety of critical factors related to the application of contingency theory to determine its feasibility in preventing future supply chain bottlenecks. The study reviewed current online news reports, previous research on contingency theory, as well as strategic and structural contingency theories. This paper also systematically reviewed several global supply chain management and strategic decision-making studies in an effort to promote a new strategy. The findings indicated that the need for mass production of products within the United States, as well as within trading partners, is necessary to prevent additional Covid-19 related supply chain gaps. The paper noted that in many instances, the United States has become dependent on foreign products, where the prevention of future supply chain gaps requires the United States restore its manufacturing prowess.

The Effects of a Selective Tax on Contract Design and Tax Timing
Zytnick, Jonathon
Taxation affects income via both a compensation contract response and a worker response. I show that executive contracts adjust to a tax on severances, and executives shift their taxable income timing in response to the interaction of tax and contract. In particular, “golden parachute” severances tend to bunch at a threshold (tied to taxable income) where the tax rate discontinuously increases, and CEOs exercise stock options in bulk to raise their taxable income and boost their threshold. Identification comes from a bunching analysis exploiting a discontinuous change in exercise incentives over time and variation across CEOs in contract incentives and deal timing. The paper demonstrates the role of contract structure in tax avoidance and additionally shows how contract structure affects worker behavior.

The Role of Corporate Social Responsibility (CSR) Information in Supply-Chain Contracting: Evidence from the Expansion of CSR Rating Coverage
Darendeli, Alper,Fiechter, Peter,Hitz, Joerg-Markus,Lehmann, Nico
We examine the effect of CSR information on stakeholder decision-making, specifically on supply-chain contracting decisions. We exploit a CSR information shock, the CSR rating coverage expansion by Thomson Reuters Asset4 in 2017, which provided CSR information and ratings for the first time for firms from the Russell 2000 index (hereafter, “treated firms”). Using a difference-in-differences design with the previously covered Russell 1000 supplier firms as control group, we find a negative effect of the CSR information shock for treated suppliers with low CSR ratings, who on average experience reductions in the number of contracts and the number of corporate customers. In cross-sectional analyses, we document variation in our treatment effect consistent with two underlying mechanisms: (i) benchmarking of suppliers’ CSR by corporate customers, and (ii) CSR-related public pressure on customer-supplier contracting. Collectively, our findings provide novel evidence on the causal effect of CSR information on stakeholders’ decision-making.

Volatility, Valuation Ratios, and Bubbles: An Empirical Measure of Market Sentiment
Martin, Ian,Gao, Can
We define a sentiment indicator that exploits two contrasting views of return predictability, and study its properties. The indicator, which is based on option prices, valuation ratios and interest rates, was unusually high during the late 1990s, reflecting dividend growth expectations that in our view were unreasonably optimistic. We interpret it as helping to reveal irrational beliefs about fundamentals. We show that our measure is a leading indicator of detrended volume, and of various other measures associated with financial fragility. We also make two methodological contributions. First, we derive a new valuation-ratio decomposition that is related to the Campbell and Shiller (1988) loglinearization, but which resembles the traditional Gordon growth model more closely and has certain other advantages for our purposes. Second, we introduce a volatility index that provides a lower bound on the market's expected log return.

Which SME is worth an investment? An explainable machine learning approach
Babaei, Golnoosh,Giudici, Paolo
Investments in Small and Medium Enterprise (SME) are facilitated by the availability of advanced machine learning (ML) methods, with high computational power and accuracy. However, despite their high accuracy, complex ML models do not provide sufficient explanation and may not be adequate for informed decision-making. In this paper, we propose an explainable AI model that can be used for analyzing SMEs and, in particular, for predicting their expected return, based on their credit risk and expected profitability. Our model is based on Shapley values which allow the predicted values generated by AI models to be interpreted according to the available explanatory variables. To validate our model we have extracted financial performance indicators from the annual balance sheets of 2049 SMEs. As a result of our empirical analysis, we show that the expected return of SMEs can be well predicted and explained by a set of characteristics deduced from their balance sheets. Therefore, their future behavior including risk and return can be predicted.

Would improved information environment of a less regulated OTC market benefit blue-chip foreign firms? Evidence from the OTCQX International Market
Kim, Martin,Lin, Steve,Yang, Liu
This study examines whether improved information environment in the OTCQX International market (hereafter QX market) benefits blue-chip foreign private issuers (FPIs). We find that around 600 FPIs traded their stocks in the QX market during 2007-2016, and they are financially better than their home-country counterparts. We also find approximately 6% abnormal return around the cross-listing days. Moreover, FPIs with higher financial reporting transparency (i.e., lower earnings smoothness and preparing financial statements in accordance with International Financial Reporting Standards) experience more pronounced abnormal returns and liquidity improvement around the cross-listing days. Further analysis shows that market premium of cross listing on the QX market is not attributed to the bonding effect. Our results highlight the importance of information environment of a less regulated OTC market in benefiting large and established FPIs, which should be of interest to market regulators, investors, and foreign firms that intend to access less regulated U.S. markets.