Research articles for the 2021-02-16

A Study on Investment Behavior of Middle Class Households in Nagpur
Samudra, Aparna,Burghate, Dr Mukul
The aim of this research was to examine the investment behaviour of the middle income class households in Nagpur. The rationale behind choosing this research topic is the premise that the middle class in India has gained attention of the economists, policy makers & the marketers, as still there remains a considerable untapped potential in this income class of India. The research has been conducted to answer few important questions on the preference of the investment instruments & investment pattern of the middle class households, to know the various objectives of investment of the middle income class households and to know whether there has been any increase in their savings & the reasons for the same. It is not only the income of the household that has an immediate bearing on the investment preferences but also the age group to which the head of the household belongs that influences the choice of investment avenue. Therefore the paper has also been directed towards finding the difference in choice of investment avenues in different age-groups & income classes of the middle income class segment in Nagpur.

An Approximate Formula linking Active Share And Tracking Error
Marmoiton, Antoine
The concept of Active Share in portfolio management has gained widespread acceptance since it was proposed in 2009 by Cremers and Petajisto (2009). An explicit relationship between Active Share and the other popular measure of relative risk, Tracking Error, was proposed by Stowe in 2014 but necessitates the full knowledge of all the weights of the portfolio and of the complete covariance matrix of the assets. I derive an approximation in a simple setup where the exact weights are unknown, the pairwise correlation between the returns of the assets is fixed, and the volatility of the assets is described by its mean and variance. This approximation is really a “toy model” and works for the purpose of understanding changes in Tracking error stemming from changes in a portfolio, and to show what the drivers of the link between Active Share and Tracking error are. Using the approximation and the Fundamental Law of Active Management, I compute the total expected return and variance of a fund with a given active share in our setup. A full derivation of the main results is provided in the appendix.

An Effort to Measure Customer Relationship Performance in Indonesia's Fintech Industry
Alisya Putri Rabbani,Andry Alamsyah,Sri Widiyanesti

The availability of social media simplifies the companies-customers relationship. An effort to engage customers in conversation networks using social media is called Social Customer Relationship Management (SCRM). Social Network Analysis helps to understand network characteristics and how active the conversation network on social media. Calculating its network properties is beneficial for measuring customer relationship performance. Financial Technology, a new emerging industry that provides digital-based financial services utilize social media to interact with its customers. Measuring SCRM performance is needed in order to stay competitive among others. Therefore, we aim to explore the SCRM performance of the Indonesia Fintech company. In terms of discovering the market majority thought in conversation networks, we perform sentiment analysis by classifying into positive and negative opinion. As case studies, we investigate Twitter conversations about GoPay, OVO, Dana, and LinkAja during the observation period from 1st October until 1st November 2019. The result of this research is beneficial for business intelligence purposes especially in managing relationships with customers.

Bank Runs And Media Freedom: What You Don’t Know Won’t Hurt You?
Benov, Alexander,Semenova, Maria
During periods of financial turmoil, depositor behaviour is influenced by the economic information environment, which is largely formed by the mediaâ€"at least for retail depositors. Therefore the severity of bank runs during financial crises, and their efficiency might be conditional on the volume of the bad news appearing in the media during a crisis. If the news flow remains unrestrained, then the probability of bank runs will increase due to the information sensitivity of depositors. Examining whether it is possible to reduce the severity of bank runs during a crisis by controlling the media, we use the panel data 28 countries from 2001 until 2016. We analyze the impact of media freedom on the growth rate of retail deposits: the major role in bank runs is usually played by unsophisticated individual depositors. Generally the results do not support the hypothesis that changes in the degree of media freedom directly influence behavioural strategies of retail depositors during financial crises. However information limitations may be an instrument to support the market discipline mechanisms: higher media freedom during crises seems to blur the information environment depositors make decisions in. Media restrictions could also prevent the financial literacy effect from dilution during financial crises, ensuring that market discipline is not further undermined.

Banks, Shadow Banks, and Business Cycles
Becard, Yvan,Gauthier, David
Credit spreads on household and business loans move in lockstep and spike in every recession. We propose a theory as to why banks tighten their lending standards following a drop in market sentiment. The key feature is a procyclical shadow banking sector that shifts risk from traditional banks to investors through securitisation. We fit the model to euroâ€'area data and find that market sentiment shocks are the main driver of business and financial cycles over the past two decades.

COVID-19 Stringency Measures and Foreign Investment: An Early Assessment
Giofré, Maela
This paper investigates the evolution of foreign investment in the immediate aftermath of the implementation of COVID-19 government stringency measures. The average stringency index is not correlated with inward investment positions. However, after removing country fixed-effect and controlling for the severity of the outbreak spread, the within-country standard deviation of the stringency index is positively and significantly correlated with inward portfolio investments at the end of the first quarter of 2020. At the end of the second quarter, the same dispersion measure is instead not associated with a significant change in inward investment. We interpret this evidence as follows. Foreign portfolio investments, typically more volatile and reactive than foreign direct ones, are more responsive to governments' prompt reactions than to gradual ones at the end of the first quarter, thus suggesting that the former policies are perceived as a more serious commitment to stem the spread of COVID-19. In the second quarter, instead, the standard deviation of the index captures the abrupt retreats of the containment measures, together with the timeliness in the adoption of policies, thus becoming less informative for foreign investors.

COVID-19 Vaccines: Saving Lives and the Global Stock Markets
Chan, Kam Fong,Chen, Zhuo,Wen, Yuanji,Xu, Tong
Global stock markets react positively when different phases of human clinical trials on COVID-19 vaccine candidates begin. The average increase in stock market returns on day one of the trials is 15.2 basis points, and this estimate is both economically and statistically significant. There are also cross-phase and cross-country variations in the market reactions. We use a simple capital budgeting framework to explain the finding: stock markets convey important information about the market-wide expectation on the development of vaccines that evolves along with the pandemic.

COVID-19 and Flight to Advanced Economies: A First Assessment
Giofré, Maela
This paper investigates the extent of the flight to quality effect, in the aftermath of the COVID outbreak, towards advanced economies. Within a generalized decline in foreign investment, we observe that advanced countries, with higher GDP per capita, belonging to the G7 group, or to the Euro area are significantly less severly hit by the pandemic than emerging and developing countries. In particular, comparing the growth in foreign liabilities at the end of the first and second quarter of 2020, the wedge between advanced economies and emerging countries is about 4%, and is even larger for G7 countries. These findings are particularly strong and systematic in the first quarter, and survive to the inclusion of COVID government stringency measures, alternative measures of pandemics severity, and different sample specifications.

COVID-19 and Stock Market Liquidity: An International Evidence
Umar, Muhammad ,Rubbaniy, Ghulame,Rizvi, Syed Kumail Abbas
This study analyzes the impact of COVID-19 on stock market liquidity of China and four worst hit countries by the pandemic. Using daily data for the stock market illiquidity spanning over July 1, 2019 to July 10, 2020 and the data for new cases and deaths over the period from December 31, 2019 to July 10, 2020, the results of our GARCH analysis show that liquidity in stock markets of all the sampled countries hit hard by the news of the outbreak. We find that for all sampled countries inflation in illiquidity due to temporary shocks reverts to long term trend shortly suggesting that the liquidity shocks due to the incidence of COVID-19were short lived. The findings of our VAR analysis show an absence of any short-term relationship between COVID-19 new cases or deaths and illiquidity. Since the series are not integrated at same level, long-term relationship between COVID-19 and stock market illiquidity do not exist as well suggesting no evidence of the effect of COVID-19 on stock market liquidity.

Earnings Yield, Smoothing Adjustment, and Dividend Dynamics
Yu, Deshui,Huang, Difang,Chen, Li
We decompose earnings yield into a smoothing component and a stationary residual component to isolate the fluctuations due to variation in expected returns from those due to the change in the forecast of dividend dynamics. The residual component forms a powerful predictor of dividend growth motivated by linking the dividend partial adjustment model to the present-value framework. Empirically, the proposed predictor displays statistically significant in-sample and out-of-sample predictive power for aggregate dividend growth at monthly and annual frequencies, robust in dividend reinvestment strategies, in pre- and post-war data, in good and bad times, and at short and long horizons.

European Stock Markets’ Response to COVID-19, Lockdowns, Government Response Stringency and Central Banks’ Interventions
Rubbaniy, Ghulame,Khalid, Ali Awais,Umar, Muhammad ,Mirza, Nawazish
Using daily data of COVID-19 fear index and stock indices of 29 European countries over the period from January 1, 2020 to September 17, 2020, this study finds no evidence of adverse impact of COVID-19 outbreak on European stock markets at the level of full sample nor at European sub-regional levels. However, we report a significantly negative time-varying reaction of European stock markets to COVID-19 eruption. Our results document that the response of European stock markets to oil price shocks is dependent on the choice of the proxy; and exchange rate changes have a negative influence on European stock markets. Our study provides the evidence that neither lockdowns nor the stringent measures taken by the governments to improve effect of COVID-19 on European stock markets are effective. The findings of the study reveal that most of the temporary interventions by the central banks of different European countries do not improve the adverse impact of COVID-19 on European stock markets. However, some of the financial measures by central banks (e.g., reduction in capital buffers) help mitigating the adverse impacts of COVID-19 on European stock markets. Our findings have important implications for investors in their decision making and, for policy makers and central banks in terms of improving their quantitative easing to support European stock markets during turbulent times such as pandemics.

Event Studies with Daily Stock Returns in Stata: Which Command to Use?
Kaspereit, Thomas
This article provides an overview of existing community-contributed commands for executing event studies. I assess which command(s) could have been used to conduct event studies that have appeared in the past ten years in three leading accounting, finance and management journals. The older command eventstudy provides a comfortable graphical user interface and good functionality for event studies that do not require hypotheses testing. The command estudy described in Pacicco et al. (2018, Stata Journal 18(2), pp. 416â€"476; 2020, Stata Journal, forthcoming) provides a set of commonly applied test statistics, useful exporting routines to spreadsheet software and LATEX for event studies with a limited number of events. The most complete command in terms of available test statistics and benchmark models as well as its ability to handle events with insufficient data, thin trading and large samples is eventstudy2.

FRM Financial Risk Meter for Emerging Markets
Ben Amor, Souhir,Althof, Michael,Härdle, Wolfgang K.
The fast-growing Emerging Market (EM) economies and their improved transparency and liquidity have attracted international investors. However, the external price shocks can result in a higher level of volatility as well as domestic policy instability. Therefore, an efficient risk measure and hedging strategies are needed to help investors protect their investments against this risk. In this paper, a daily systemic risk measure, called FRM (Financial Risk Meter) is proposed. The FRM@ EM is applied to capture systemic risk behavior embedded in the returns of the 25 largest EMs’ FIs, covering the BRIMST (Brazil, Russia, India, Mexico, South Africa, and Turkey), and thereby reflects the financial linkages between these economies. Concerning the Macro factors, in addition to the Adrian & Brunnermeier (2016) Macro, we include the EM sovereign yield spread over respective US Treasuries and the above-mentioned countries’ currencies. The results indicated that the FRM of EMs’ FIs reached its maximum during the US financial crisis following by COVID -9 crisis and the Macro factors explain the BRIMST’ FIs with various degrees of sensibility. We then study the relationship between those factors and the tail event network behavior to build our policy recommendations to help the investors to choose the suitable market for investment and tail-event optimized portfolios. For that purpose, an overlapping region between portfolio optimization strategies and FRM network centrality is developed. We propose a robust and well-diversified tail-event and cluster risk-sensitive portfolio allocation model and compare it to more classical approaches.

Hans-Bernd Schäfer, Bucerius Law School, Hamburg, University of Hamburg Früchte des Zorns, Anmerkungen zum Buch von Katharina Pistor, The Code of Capital, How The Law Creates Wealth and Inequality, Princeton University Press 2019 (Grapes of Wrath, Notes on the Book by Katharina Pistor, The Code of Capital, How The Law Creates Wealth and Inequality, Princeton University Press 2019)
Schäfer, Hans-Bernd
German Abstract: Die zentrale These des Buchs von Katharina Pistor besagt, Privatrecht diene in Verbindung mit seiner zunehmenden Globalisierung den Interessen der Reichen und ermögliche „Herrschaft durch Recht“ (S.205) anstelle der Herrschaft des Rechts. Der Leser gewinnt den Eindruck, Privatrecht sei in kapitalistischen Staaten das selbstgemachte von Anwälten kodierte und von willigen Gerichten umgesetzte Recht reicher Leute und großer Unternehmungen, das deren Reichtum und gleichzeitig die die Ungleichheit vergrößere. Wenn Pistor über Reichtum durch Neukodierung von Rechtsnormen schreibt, unterscheidet sie nicht klar genug zwischen privatem Reichtum in einer Klientelwirtschaft, der nur durch Umverteilung möglich wird, indem die Gesellschaft insgesamt stagniert oder ärmer wird, Nationalreichtum, der ein Land wirtschaftlich voranbringt, aber hohe und unkompensierte Schäden bei Vielen erzeugen kann und Nationalreichtum, der wirtschaftliche Vorteile für viele oder alle und bei kaum jemandem Schäden verursacht aber zugleich die Ungleichheit erhöht. Wenn Pistor zudem fordert, generell zivilrechtliche Neukodierungen von Kapital durch Anwälte und Gerichte, die über Basismodule hinausgehen, abzuschaffen (S.224), schießt sie weit über das Ziel hinaus. English Abstract: The central thesis of Katharina Pistor's book is that private law, in conjunction with its increasing globalization, serves the interests of the rich and enables "rule by law" instead of the rule of law. The reader gets the impression that private law in capitalist states is the self-made law of rich people and large corporations, codified by lawyers and implemented by willing courts, which increases their wealth and at the same time increases inequality. When Pistor writes about wealth through recoding legal norms, she does not distinguish clearly enough between private wealth in a patronage economy, which is made possible only through redistribution, stagnating or making society as a whole poorer, national wealth, which advances a country economically but can produce high and uncompensated harms to many, and national wealth, which produces economic benefits for many or all and harms hardly anyone but at the same time increases inequality. When Pistor also calls for generally abolishing civil recodifications of capital by lawyers and courts that go beyond basic modules, she overshoots the mark.

Incentive Realignment: Mutual Funds’ Influence on Executive Compensation Contracts
Agarwal, Vikas,Cao, Sean,Huang, Shawn X.,Kim, Min
Using a regulation that increased portfolio disclosure frequency of US mutual funds as an exogenous shock shortening funds’ investment horizon, we find that affected funds influence portfolio firms to reduce the pay duration of their executives to incentivize them to also have shorter investment horizon. We show that funds affect this change through both voice and exit channels, i.e., voting on compensation-related issues and divesting from portfolio firms. Cross-sectional tests corroborate these findings to reveal more pronounced effects when fund managers have stronger career incentives and are less distracted, and when funds are less concerned about free rider problems and share ownership with potentially supportive other short-term oriented investors.

Integrating Floor Plans into Hedonic Models for Rent Price Appraisal
Kirill Solovev,Nicolas Pröllochs

Online real estate platforms have become significant marketplaces facilitating users' search for an apartment or a house. Yet it remains challenging to accurately appraise a property's value. Prior works have primarily studied real estate valuation based on hedonic price models that take structured data into account while accompanying unstructured data is typically ignored. In this study, we investigate to what extent an automated visual analysis of apartment floor plans on online real estate platforms can enhance hedonic rent price appraisal. We propose a tailored two-staged deep learning approach to learn price-relevant designs of floor plans from historical price data. Subsequently, we integrate the floor plan predictions into hedonic rent price models that account for both structural and locational characteristics of an apartment. Our empirical analysis based on a unique dataset of 9174 real estate listings suggests that current hedonic models underutilize the available data. We find that (1) the visual design of floor plans has significant explanatory power regarding rent prices - even after controlling for structural and locational apartment characteristics, and (2) harnessing floor plans results in an up to 10.56% lower out-of-sample prediction error. We further find that floor plans yield a particularly high gain in prediction performance for older and smaller apartments. Altogether, our empirical findings contribute to the existing research body by establishing the link between the visual design of floor plans and real estate prices. Moreover, our approach has important implications for online real estate platforms, which can use our findings to enhance user experience in their real estate listings.

Interdependencies between Mining Costs, Mining Rewards and Blockchain Security
Pavel Ciaian,d'Artis Kancs,Miroslava Rajcaniova

This paper studies to what extent the cost of operating a proof-of-work blockchain is intrinsically linked to the cost of preventing attacks, and to what extent the underlying digital ledger security budgets are correlated with the cryptocurrency market outcomes. We theoretically derive an equilibrium relationship between the cryptocurrency price, mining rewards and mining costs, and blockchain security outcomes. Using daily crypto market data for 2014-2021 and employing the autoregressive distributed lag approach - that allows treating all the relevant moments of the blockchain series as potentially endogenous - we provide empirical evidence of cryptocurrency price and mining rewards indeed being intrinsically linked to blockchain security outcomes.

Investigating the Impact of COVID-19 Outbreak On U.S. Bond and Commercial Paper Market
Destin, Achu Dobgima
SARS-Cov-2 was first reported in Wuhan, a town in Hubei Province of China with a population of 11 million in December 2019, following an outbreak of non-pneumonia a clear cause. The virus has now spread across the globe to more than 200 countries and territories, and the world health organization (WHO) described it as a pandemic on 11 March 2020. On the economic front, COVID-19 has led more than 200 countries partial or totally lockdown, disrupted global supply chain, and induced a significant fall in both economic activity and financial asset prices. United States, being one of the highest country affected by the Virus with 80.9M Cases, 45.8M Infected, and 1.77M Deaths as at the 28th of December 2020. Recently vaccines have been developed but the contamination wave keeps on increasing every day. On the socioeconomic front, COVID-19 has led more than 200 countries into partial or total lockdown, disrupted global supply chains, and induced a fall in both economic activity and financial asset prices. The objective of this research is to investigate the impact of COVID-19 on U.S Bond and Commercial Paper Markets.The result show that, intercept, interest rate, TED spread and Total cases are the only determinants of Bond price because of the robust relationship between them. Meanwhile, normal model show that, Intercept, TED spread (i.e. the difference between the 3 months Treasury bill and the 3-month LIBOR based in U.S. dollars), Total Cases, Interest Rate, and Total Death are robust determinants of the prices of Treasury bill while the generic model highlights the importance of Interest Rate, Total Cases, Total COVID-19 Deaths cases.

Investigating the Impact of COVID-19 Outbreak On U.S. Commodity Market
Destin, Achu Dobgima
SARS-Cov-2 was first reported in Wuhan, a town in Hubei Province of China with a population of 11 million in December 2019, following an outbreak of non-pneumonia a clear cause. The virus has now spread across the globe to more than 200 countries and territories, and the world health organization (WHO) described it as a pandemic on 11 March 2020. On the economic front, COVID-19 has led more than 200 countries partial or totally lockdown, disrupted global supply chain, and induced a significant fall in both economic activity and financial asset prices. United States, being one of the highest country affected by the Virus with 80.9M Cases, 45.8M Infected, and 1.77M Deaths as at the 28th of December 2020. Recently vaccines have been developed but the contamination wave keeps on increasing every day. On the socioeconomic front, COVID-19 has led more than 200 countries into partial or total lockdown, disrupted global supply chains, and induced a fall in both economic activity and financial asset prices. It’s of prime importance to study how COVID-19 impact’s U.S commodity market. The commercial and financial effect of COVID-19 The impact of COVID-19 are unclear because the public health crisis is still unfolding. There is limited amount of studies concerning this topic, because the crisis is still unfolding. The objective of this study is to investigate the impact of COVID-19 on U.S commodity market. The author uses extreme bound analysis for market interpretation and sourced data from the Federal Reserve Economic Database (FRED) and Our World in Data COVID-19, from January 2 to November 16 2020.The results of the commodity market show that, Foreign Exchange and Stringency Index are the only determinants of commodity Prices from Leamer EBA approach. Furthermore, The results of the normal model show that, TED spread (i.e. the difference between the 3 months Treasury bill and the 3-month LIBOR based in U.S. dollars), and Total Death are robust determinants of Oil Prices while the generic model highlights the importance of TED spread, Total Deaths. In addition, the correlation matrix show that, Foreign exchange and the price of Bitcoin has and impact on Gold Prices, a significant negative relationship with Stringency index. On the other hand, Total Deaths of COVID-19 has a significant negative relationship on Oil prices.

Investigating the Impact of COVID-19 Outbreak On U.S. Stock Market
Destin, Achu Dobgima
SARS-Cov-2 was first reported in Wuhan, a town in Hubei Province of China with a population of 11 million in December 2019, following an outbreak of non-pneumonia a clear cause. The world health organization (WHO) described it as a pandemic on 11 March 2020. On the economic front, COVID-19 has led more than 200 countries partial or totally lockdown. The objective of this study is to investigate the impact of COVID-19 on U.S stock market. The objective of this study is to investigate the impact of COVID-19 on U.S stock market. The author uses extreme bound analysis for market interpretation and sourced data from the Federal Reserve Economic Database (FRED) and Our World in Data COVID-19, from January 2 to November 16 2020.The results of the study show that, Foreign Exchange and Stringency Index are the only determinants of Stock Prices from Leamer EBA approach. Again, the normal model show that, Interest Rate, TED spread (i.e. the difference between the 3 months Treasury bill and the 3-month LIBOR based in U.S. dollars), Foreign Exchange, and Stringency Index are robust determinants of Stock Prices while the generic model highlights the importance of TED spread, Foreign Exchange, Stringency Index, Interest Rate. In addition, the correlation matrix show that, Bitcoin, Interest Rate, Foreign exchange and Gold Price have a Positive Impact on Stock Price while Stringency Index and the TED Spread has a negative significant relationship with stock prices.

Investment in Cryptocurrencies: A Perspective from Asset Pricing and Portfolio Theory
Dempsey, Michael J.,Anh Pham, Huy Nguyen,Ramiah, Vikash
We consider the performance of cryptocurrencies in the light of fundamental asset pricing and portfolio theory. We observe how a traditional focus on reducing asset return volatility with Markowitz diversification actually misses the significance of such volatility for growth. The recognition that asset growth is more likely subject to exponential or continuously-compounding growth characteristics reveals that asset volatility can be exploited both across assets and across investment periods to deliver superior returns.

Investor Monitoring, Money-Likeness and Stability of Money Market Funds
Järvenpää, Maija,Paavola, Aleksi
An asset is money-like if investors have no incentives to acquire costly private information on the underlying collateral. However, privately provided money-like assetsâ€"like prime money market fund (MMF) sharesâ€"are prone to runs if investors suddenly start to question the value of the collateral. Therefore, for risky assets, lack of money-likeness is a necessary condition for lack of run incentives. But is it a sufficient one? This paper studies the effect of the U.S. money market fund reform of 2014â€"2016 on investor monitoring, money-likeness and stability of institutional prime MMFs. Using the number of distinct IP addresses accessing MMFs’ regulatory reports as a proxy for investor monitoring, we find that the reform increased monitoring and thus decreased money-likeness of institutional prime funds. However, we also show that after the reform, institutional prime funds that are more likely to impose the newly introduced redemption restrictions are more monitored, suggesting that investors may monitor in order to avoid being hit by the restrictions. Overall, our results indicate that increased monitoring, or decreased money-likeness, has not made institutional prime MMFs run-free, and it may have actually created a new source of fragility for MMFs.

LATE for History
Alberto Bisin,Andrea Moro

In Historical Economics, Persistence studies document the persistence of some historical phenomenon or leverage this persistence to identify causal relationships of interest in the present. In this chapter, we analyze the implications of allowing for heterogeneous treatment effects in these studies. We delineate their common empirical structure, argue that heterogeneous treatment effects are likely in their context, and propose minimal abstract models that help interpret results and guide the development of empirical strategies to uncover the mechanisms generating the effects.

Lending Cycles and Real Outcomes: Costs of Political Misalignment
Bircan, Cagatay,Saka, Orkun
We document a strong political cycle in bank credit and industry outcomes in Turkey. In line with theories of tactical redistribution, state-owned banks systematically adjust their lending around local elections compared with private banks in the same province based on electoral competition and political alignment of incumbent mayors. This effect only exists in corporate lending and creates credit constraints for firms in opposition areas, which suffer drops in assets, employment and sales but not firm entry. Financial resources and factors of production are misallocated as more effient provinces and industries suffer the greatest constraints, reducing aggregate productivity.

Mispricing and Uncertainty in International Markets
Sandulescu, Mirela,Schneider, Paul
We develop Residual MisPricing (RMP), an index capturing mispricing relative to a linear benchmark asset pricing model, from the structure imposed by no-arbitrage. RMP is fully conditional and depends only on the returns of basic assets. Return data for several economies reveal that RMP is countercyclical and related to financial uncertainty. RMP further shows a strong positive relation to conditional international equity and currency risk premia, as well as a close link to market-wide funding liquidity shocks. The relations we document hold in particular out-of-sample. Our evidence points to new record highs for RMP during the COVID-19 era, similar to its behavior in the 2008 financial crisis.

Money in the Twenty-First Century: From Rusty Coins to Digital Currencies
Prates, Marcelo
After the Global Financial Crisis, central banks became identified as banks’ closest allies, rescuing them from failure when things go wrong. Banks, in turn, emerged as complex and unstable institutions that privatize profits and socialize losses, to the despair of taxpayers. And regulation and regulators were seen as incapable of curbing financial excess. The coronavirus pandemic only exacerbated the generally negative sentiment, as governments lacked a fast and simple way to send relief money directly to their citizens. In the meantime, sovereign currencies have faced increased private competition, from Bitcoin to big tech global projects. At this point, some structural reform of the monetary system seems not only desirable but inevitable. It is about time to look again at the role of money in the modern economy and better understand its features and flaws. This Article thus offers a guide to the recent evolution of money and what its future might hold.

Multidimensional Stock Market Liquidity and Business Cycles
van Hees, Thomar,Verschoor, Willem F. C.
We examine the impact of multidimensional stock market liquidity on business cycles that captures the key market liquidity characteristics. Using seven different liquidity measures, we find that the effect of liquidity on economic growth and recessions differs among liquidity measures in the US stock market in the period of 1952 to 2011. Volume-based and transaction costs-based measures contain robust information about future conditions of the US economy, while for market-impact and price-based measures there is no causality in either direction. Moreover, the illiquidity ratio dominates all stock market liquidity measures in forecasting economic recessions. Our findings exemplify the importance of alternative liquidity proxies in explaining the state of the US economy.

Multilayer heat equations: application to finance
A. Itkin,A. Lipton,D. Muravey

In this paper, we develop a Multilayer (ML) method for solving one-factor parabolic equations. Our approach provides a powerful alternative to the well-known finite difference and Monte Carlo methods. We discuss various advantages of this approach, which judiciously combines semi-analytical and numerical techniques and provides a fast and accurate way of finding solutions to the corresponding equations. To introduce the core of the method, we consider multilayer heat equations, known in physics for a relatively long time but never used when solving financial problems. Thus, we expand the analytic machinery of quantitative finance by augmenting it with the ML method. We demonstrate how one can solve various problems of mathematical finance by using our approach. Specifically, we develop efficient algorithms for pricing barrier options for time-dependent one-factor short-rate models, such as Black-Karasinski and Verhulst. Besides, we show how to solve the well-known Dupire equation quickly and accurately. Numerical examples confirm that our approach is considerably more efficient for solving the corresponding partial differential equations than the conventional finite difference method by being much faster and more accurate than the known alternatives.

On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning
Marco Ortu,Nicola Uras,Claudio Conversano,Giuseppe Destefanis,Silvia Bartolucci

This work aims to analyse the predictability of price movements of cryptocurrencies on both hourly and daily data observed from January 2017 to January 2021, using deep learning algorithms. For our experiments, we used three sets of features: technical, trading and social media indicators, considering a \textit{restricted model} of only technical indicators and an \textit{unrestricted model} with technical, trading and social media indicators. We verified whether the consideration of trading and social media indicators, along with the classic technical variables (such as price's returns), leads to a significative improvement in the prediction of cryptocurrencies price's changes. We conducted the study on the two highest cryptocurrencies in volume and value (at the time of the study): Bitcoin and Ethereum. We implemented four different machine learning algorithms typically used in time-series classification problems: \textit{Multi Layers Perceptron (MLP)}, \textit{Convolutional Neural Network (CNN)}, \textit{Long Short Term Memory (LSTM) neural network} and \textit{Attention Long Short Term Memory (ALSTM)}. We devised the experiments using the advanced bootstrap technique to consider the variance problem on test samples, which allowed us to evaluate a more reliable estimate of the model's performance. Furthermore, the \textit{Grid Search} technique was used to find the best \textit{hyperparameters} values for each implemented algorithm. The study shows that, based on the hourly frequency results, the unrestricted model outperforms the restricted one. The addition of the trading indicators to the classic technical indicators improves the accuracy of Bitcoin and Ethereum price's changes prediction, with an increase of accuracy from a range of 51-55\% for the restricted model, to 67-84\% for the unrestricted model.

On the value of non-Markovian Dynkin games with partial and asymmetric information
Tiziano De Angelis,Nikita Merkulov,Jan Palczewski

We prove that zero-sum Dynkin games in continuous time with partial and asymmetric information admit a value in randomised stopping times when the stopping payoffs of the players are general \cadlag measurable processes. As a by-product of our method of proof we also obtain existence of optimal strategies for both players. The main novelties are that we do not assume a Markovian nature of the game nor a particular structure of the information available to the players. This allows us to go beyond the variational methods (based on PDEs) developed in the literature on Dynkin games in continuous time with partial/asymmetric information. Instead, we focus on a probabilistic and functional analytic approach based on the general theory of stochastic processes and Sion's min-max theorem (M. Sion, Pacific J. Math., 8, 1958, pp. 171-176). Our framework encompasses examples found in the literature on continuous time Dynkin games with asymmetric information and we provide counterexamples to show that our assumptions cannot be further relaxed.

Power-Law Return-Volatility Cross Correlations of Bitcoin
T. Takaishi

This paper investigates the return-volatility asymmetry of Bitcoin. We find that the cross correlations between return and volatility (squared return) are mostly insignificant on a daily level. In the high-frequency region, we find thata power-law appears in negative cross correlation between returns and future volatilities, which suggests that the cross correlation is \revision{long ranged}. We also calculate a cross correlation between returns and the power of absolute returns, and we find that the strength of \revision{the cross correlations} depends on the value of the power.

Pyramid scheme in stock market: a kind of financial market simulation
Yong Shi,Bo Li,Guangle Du

Artificial stock market simulation based on agent is an important means to study financial market. Based on the assumption that the investors are composed of a main fund, small trend and contrarian investors characterized by four parameters, we simulate and research a kind of financial phenomenon with the characteristics of pyramid schemes. Our simulation results and theoretical analysis reveal the relationships between the rate of return of the main fund and the proportion of the trend investors in all small investors, the small investors' parameters of taking profit and stopping loss, the order size of the main fund and the strategies adopted by the main fund. Our work are helpful to explain the financial phenomenon with the characteristics of pyramid schemes in financial markets, design trading rules for regulators and develop trading strategies for investors.

Reaching for Yield in the Going-Public Market: Evidence from SPACs
Bai, Jessica,Ma, Angela,Zheng, Miles
This paper provides a unified explanation for the existence, time-series variation, and recent boom of the Special Purpose Acquisition Company (SPAC). We develop a theoretical framework in which SPAC and IPO markets serve different types of production firms and public investors. SPAC managers act as non-bank certification intermediaries and match yield-seeking investors with value-creating but risky production firms. Reaching for yield in the going-public market contributes to the rise of SPACs. Our model jointly explains several important empirical patterns regarding the U.S. SPAC market: (1) Compared to IPO firms, SPAC firms are ex-ante smaller, riskier, but grow at higher or similar rates ex-post going public. (2) SPAC issuance boomed in 2007 prior to the Global Financial Crisis and accelerated from 2015 to 2020. (3) The market share of SPACs is strongly positively correlated with equity market sentiment. Our model implies that a well-functioning SPAC market improves social welfare and stimulates economic growth by allowing creative, risk-taking firms to go public, increasing innovative activity ex-ante. Finally, we highlight the importance of aligning SPAC managers with long-term investors and provide recommendations for improved market regulation.

Recruiting Dark Personalities for Earnings Management
Harris, Ling L.,Jackson, Scott B.,Owens, Joel,Seybert, Nicholas
Prior research indicates that managers’ dark personality traits increase their tendency to engage in disruptive and unethical organizational behaviors including accounting earnings management. Other research suggests that the prevalence of dark personalities in management may represent an accidental byproduct of selecting managers with accompanying desirable attributes that fit the stereotype of a “strong leader.” Our paper posits that organizations may hire some managers who have dark personality traits because their willingness to push ethical boundaries aligns with organizational objectives, particularly in the accounting context where ethical considerations are especially important. Using several validation studies and experiments, we find that experienced executives and recruiting professionals favor hiring a candidate with dark personality traits into an accounting management position over an otherwise better-qualified candidate when the hiring organization faces pressure to manage earnings. Our results help to illuminate why individuals with dark personality traits may effectively compete for high-level accounting positions.

Sector Neutral Portfolios: Long memory motifs persistence in market structure dynamics
Jeremy Turiel,Tomaso Aste

We study soft persistence (existence in subsequent temporal layers of motifs from the initial layer) of motif structures in Triangulated Maximally Filtered Graphs (TMFG) generated from time-varying Kendall correlation matrices computed from stock prices log-returns over rolling windows with exponential smoothing. We observe long-memory processes in these structures in the form of power law decays in the number of persistent motifs. The decays then transition to a plateau regime with a power-law decay with smaller exponent. We demonstrate that identifying persistent motifs allows for forecasting and applications to portfolio diversification. Balanced portfolios are often constructed from the analysis of historic correlations, however not all past correlations are persistently reflected into the future. Sector neutrality has also been a central theme in portfolio diversification and systemic risk. We present an unsupervised technique to identify persistently correlated sets of stocks. These are empirically found to identify sectors driven by strong fundamentals. Applications of these findings are tested in two distinct ways on four different markets, resulting in significant reduction in portfolio volatility. A persistence-based measure for portfolio allocation is proposed and shown to outperform volatility weighting when tested out of sample.

Skin in the Game: Operating Growth, Firm Performance, and Future Stock Returns
Cao, Sean,Wang, Zhe,Yeung, P. Eric
Prior research documents that asset growth is negatively associated with future firm performance. In contrast, we show that growth financed by product market stakeholders (i.e., “operating growth”) is positively associated with future firm performance. Investors and security analysts under-estimate the positive effects of operating growth on future performance, resulting in return predictability and overly pessimistic earnings forecasts for firms with high operating growth. Future stock returns largely concentrate around subsequent earnings announcements with declining magnitudes, consistent with the error-in-expectation explanation. Results from cross-sectional tests further support the hypothesis that operating growth signals high future performance but investors underreact to it.

Stock Market Volatility: Friend or Foe?
Dempsey, Michael J.,Gunasekarage, Abey,Truong, Thanh
Although a good deal of research effort has been allocated to understanding the time-series volatility of stock returns â€" as both market (or systematic) volatility and idiosyncratic (or non-systematic) volatility â€" the relationship of such volatility with cross-sectional volatility or dispersion of outcomes is sparse. Nevertheless, the quest to understand one must involve the quest to understand the other. In this paper, we investigate the dynamic of the dispersion of return outcomes in generating a portfolio’s expected return outcome. We find that changes in the level of cross-sectional volatility have highly significant implications for portfolio performances and the notion of risk.

Supportive 5G infrastructure policies are essential for universal 6G: Evidence from an open-source techno-economic simulation model using remote sensing
Edward J. Oughton,Ashutosh Jha

Work has now begun on the sixth generation of cellular technologies (`6G`) and cost-efficient global broadband coverage is already becoming a key pillar. Indeed, we are still far from providing universal and affordable broadband connectivity, despite this being a key part of the Sustainable Development Goals (Target 9.c). Currently, both Mobile Network Operators and governments still require independent analysis of the strategies that can help achieve this target with the cellular technologies available (4G and 5G). Therefore, this paper provides quantitative evidence which demonstrates how current 5G policy affects universal broadband, as well as drawing conclusions over how decisions made now affect future evolution to 6G. Using a method based on an open-source techno-economic codebase, combining remote sensing with least-cost network algorithms, performance analytics are provided for different 4G and 5G universal broadband strategies. As an example, the assessment approach is applied to India, the world`s second-largest mobile market and a country with notoriously high spectrum prices. The results demonstrate the trade-offs between technological decisions. This includes demonstrating how important current infrastructure policy is, particularly given fiber backhaul will be essential for delivering 6G quality of service. We find that by eliminating the spectrum licensing costs, full 5G population coverage can viably be achieved using fiber backhaul. In conclusion, supportive 5G infrastructure policies are essential in providing a superior foundation for evolution to 6G.

Surrogate Monte Carlo
A. Christian Silva,Fernando F. Ferreira

This article proposes an artificial data generating algorithm that is simple and easy to customize. The fundamental concept is to perform random permutation of Monte Carlo generated random numbers which conform to the unconditional probability distribution of the original real time series. Similar to constraint surrogate methods, random permutations are only accepted if a given objective function is minimized. The objective function is selected in order to describe the most important features of the stochastic process. The algorithm is demonstrated by producing simulated log-returns of the S\&P 500 stock index.

The Association between Dividend Payouts and Firm Growth: Australian Evidence
Dempsey, Michael J.,Gunasekarage, Abey,Truong, Thanh
We report that whereas firms with high earnings distributions tend to have low to moderate growth (consistent with conventional theory), firms with low earnings distributions run the range between high and low performers. We interpret our findings for firm growth and payout policy in relation to the firm’s location on the Boston Consulting Group (BCG) matrix that combines high/low growth with high/low market share. Our findings suggest that the market has difficulty in distinguishing between these types of firms. A concern is that investor preferences as an outcome may be focused on dividend-paying firms at the expense of younger growing firms in need of retained earnings.

The COVID Pandemic in the Market: Infected, Immune and Cured Bonds
Zaghini, Andrea
By focusing on the cost conditions at issuance, I find that not only the COVID-19 pandemic effects were different across bonds and firms at different stages, but also that the market composition was significantly affected, collapsing on investment- grade bonds, a segment in which the share of bonds eligible to the ECB corporate programmes strikingly increased from 15% to 40%. At the same time the high-yield segment shrunk to almost disappear at 4%. In addition to a market segmentation along the bond grade and the eligibility to the ECB programmes, another source of risk detected in the pricing mechanism is the weak resilience to pandemic: the premium requested is around 30 basis points and started to be priced only after the early containment actions taken by the national authorities. On the contrary, I do not find evidence supporting an increased risk for corporations headquartered in countries with a reduced fiscal space, nor the existence of a premium in favour of green bonds, which should be the backbone of a possible “green recovery”.

The Impact of Credit Risk on Performance: A Case of South African Commercial Banks
Lawrence, Babatunde
The objective of the study was to comparatively assess the impact of credit risk on the performance of big and small banks in South Africa. Data from audited financial reports of 14 commercial banks were obtained and divided into two panel data sets and analysed using the R-Studio software version 3.5.1 to assess the impact of capital adequacy ratio (CAR), non-performing loan to gross loan (NPLGL), loan-to-deposit ratio (LTDR), leverage ratio (LR), board gender diversity (BGD), with bank size (total asset) and AGE as control variables, on performance, (return on asset [ROA] and return on equity [ROE]). The findings of the study revealed that non-performing loan (NPL), CAR, LR, LTDR and age of banks all have significant and greater impact on performance, as measured by ROA, of small banks when compared with big banks. Surprisingly, NPL was revealed to have a lesser impact on the ROE of small banks as compared to the ROE of big banks but showed no impact on the ROA of big banks during the period of 2008â€"2017.

The Option Value of Municipal Liquidity: Evidence from Federal Lending Cutoffs during COVID-19
Haughwout, Andrew,Hyman, Benjamin,Shachar, Or
We estimate the option value of municipal liquidity by studying bond market behavior and public sector hiring decisions when government budgets are severely distressed. Using a regression discontinuity (RD) design, we exploit lending eligibility cutoffs introduced by the Federal sector’s Municipal Liquidity Facility (MLF) in April 2020 to study the effect of an emergency liquidity option on yields, primary issuance, credit downgrade probability, and public sector employment. We find that while the announcement of the liquidity option improved overall municipal bond market functioning across the board, low-rated issuers additionally benefited from direct access: low-rated government bonds traded at higher prices and were issued more frequently on private markets with facility access. This suggests the presence of a credit-risk sharing channel on top of the Fed’s role as liquidity-provider of last resort. In contrast to investors, local governments responded to the liquidity option by retaining a greater share of public sector employees across the entire ratings distribution.The results imply municipal debt markets and employment outcomes would likely have been more distressed absent the MLF, and are consistent with the view that large government furloughs might have over-weighted the worst possible outcomes based on past experience.

The Value of Choice in Mandatory Health Insurance
Biener, Christian,Zou, Lan
Giving consumers choice can improve welfare in principle. In this study, we explore the financial consequences of choice and information provision in the Swiss mandatory health insurance market that entails non-optimal options by design. This market is characterized by a significant redistribution of welfare due to the approximately 36 percent of the adult population participating in such non-optimal plans. We run a laboratory experiment in which we contrast choices under an increased information and a restricted choice setting to the control choice situation as it is currently observed in the market. We find that financial losses resulting from poor choice are economically meaningful and amount to 9.4 percent of total annual health costs and that decision quality cannot be easily improved by interventions. We suggest several policy changes in light of our findings.

The Value of Registered Investment Advisors during the COVID-19 Financial Crash - Evidence from 13F and twitter
Cheng, Yuanshan,Guo, Tao,Sam, Janine,Gibson, Philip
The ongoing public health crisis associated with the COVID-19 pandemic has had a significant impact on business activities, government at large, financial markets, and individual households. This study is the first to our knowledge that seeks to examine the 2020 financial market crisis using manually downloaded data, which combined 13F filing with ADV forms with tweets from Registered Investment Advisors. We find that even during extremely negative return days, financial advisors communicate frequently and positively with their clients. Clients working with financial advisors tend to sell less and buy more during a market downturn as compared with self-discretionary clients.

Who Uses Which Order Type and Why?
Li, Sida,Ye, Mao,Zheng, Miles
Clientele effects explain the proliferation of order types on U.S. stock exchanges. Market and plain limit orders lose money, indicating that informed traders use more complex orders. The most complex order types refuse to trade with the national best bid and offer (NBBO) if the NBBO appears on another exchange. Fees provide one explanation for non-routable orders because Reg NMS might route orders to worse prices after adjusting for routing fees. Non-routable orders also win speed races to capture quick profits and contain short-term information. However, all order types containing long-term information are routable and often tailored to corporate events.