Research articles for the 2021-05-10

A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news
Obaid, Khaled,Pukthuanthong, Kuntara
By applying machine learning to the accurate and cost-effective classification of photos based on sentiment, we introduce a daily market-level investor sentiment index (Photo Pessimism) obtained from a large sample of news photos. Consistent with behavioral models, Photo Pessimism predicts market return reversals and trading volume. The relation is strongest among stocks with high limits to arbitrage and during periods of elevated fear. We examine whether Photo Pessimism and pessimism embedded in news text act as complements or substitutes for each other in predicting returns and find evidence that the two are substitutes.

Acquiring to Sell: Acquisition Flippers and Earnings Management
Choi, Lyungmae,Huang, Shawn X.,Kim, Min
This study explores an interesting phenomenon in which some acquirers buy and own targets for a relatively short period of time and then “flip” or resell these targets to other companies for profit. We show that acquisition flippers engage in earnings management to improve the appeal of flipped targets. In particular, subsequent acquirers of flipped targets are more likely to restate earnings downward post-acquisition than acquirers of non-flipped targets. For available flipped targets, we find they have larger abnormal accruals than non-flipped targets. Additional analyses show that acquiring flipped targets is detrimental to subsequent acquirers, as the acquirers experience larger declines in operating performance, have a higher likelihood of goodwill impairment, and are less likely to acquire flipped targets in the future than acquirers of non-flipped targets. Cross-sectional tests reveal more (less) pronounced effects among targets flipped by serial flippers and professional investors (among subsequent acquirers with high-quality M&A advisors).

Aspects of a phase transition in high-dimensional random geometry
Axel Prüser,Imre Kondor,Andreas Engel

A phase transition in high-dimensional random geometry is analyzed as it arises in a variety of problems. A prominent example is the feasibility of a minimax problem that represents the extremal case of a class of financial risk measures, among them the current regulatory market risk measure Expected Shortfall. Others include portfolio optimization with a ban on short selling, the storage capacity of the perceptron, the solvability of a set of linear equations with random coefficients, and competition for resources in an ecological system. These examples shed light on various aspects of the underlying geometric phase transition, create links between problems belonging to seemingly distant fields and offer the possibility for further ramifications.

BGL Group: Artificial Intelligence (AI) Strategy
Holland, Christopher P.
This research presents a detailed case analysis of BGL Group, a leading, international, distributor of insurance and household financial services. The AI strategy is described by analysing and evaluating a set of AI applications covering a variety of business areas: 1. Machine learning for pricing; 2. Chatbot AI technology to improve the customer experience in e-service; 3. Customer experience design thinking and a/b testing in new product development; 4. Voice recognition and Natural Language Processing (NLP) in call centre operations; 5. AI techniques for market segmentation. Each application is described in detail, and the concept of value creation in service markets is illustrated using data flow diagrams of customer interactions for different stages of the customer journey. A benefits matrix model is proposed that captures the principal AI benefits to both the supplier and the customer. The case discussion uses a new model, an AI systems map, to describe and explain the overall landscape of current AI applications, traditional Management Information Systems (MIS) and possible future application areas based on broad AI strategies and cognitive AI/thinking machines. Some concluding remarks are made on the importance of a digital first culture, up-to-date digital infrastructure and technology partnerships for successful implementation of AI systems, the crucial role of big data in AI strategies, and the growing importance of AI ethics in business applications. Finally, some propositions are offered regarding the future direction of AI in insurance markets.

Banking Practices and Borrowing Firms’ Financial Reporting Quality: Evidence from Bank Cross-Selling
Su, Barbara
This paper studies whether banking practices affect borrowing firms’ financial reporting quality. Specifically, I examine the effect of bank cross-selling activities (i.e., a bank’s joint provisions of lending and underwriting services to the same firm) on borrowers’ financial reporting quality for debt contracting purposes. Compared to issuing stand-alone loans, cross-selling increases a bank’s risk exposure to the firm and therefore gives the bank more motivation to monitor the borrower’s financial condition (incentive effect). In addition, cross-selling enables information sharing between the underwriting and lending divisions and allows the bank to have a closer understanding of the borrower’s underlying economics, thereby better disciplining the borrower’s ability to withhold bad news (information effect). Consistent with these arguments, I expect and find that cross-selling is associated with an improvement in the debt contracting value (DCV) of accounting information at borrowing firms. I also provide evidence in support of the incentive effect and the information effect.

Bayesian inference and superstatistics to describe long memory processes of financial time series
Geoffrey Ducournau

One of the standardized features of financial data is that log-returns are uncorrelated, but absolute log-returns or their squares namely the fluctuating volatility are correlated and is characterized by heavy tailed in the sense that some moment of the absolute log-returns is infinite and typically non-Gaussian [20]. And this last characteristic change accordantly to different timescales. We propose to model this long-memory phenomenon by superstatistical dynamics and provide a Bayesian Inference methodology drawing on Metropolis-Hasting random walk sampling to determine which superstatistics among inverse-Gamma and log-Normal describe the best log-returns complexity on different timescales, from high to low frequency. We show that on smaller timescales (minutes) even though the Inverse-Gamma superstatistics works the best, the log-Normal model remains very reliable and suitable to fit the absolute log-returns probability density distribution with strong capacity of describing heavy tails and power law decays. On larger timescales (daily), we show in terms of Bayes factor that the inverse-Gamma superstatistics is preferred to the log-Normal model. We also show evidence of a transition of statistics from power law decay on small timescales to exponential decay on large scale with less heavy tails meaning that on larger time scales the fluctuating volatility tend to be memoryless, consequently superstatistics becomes less relevant.

Bitcoin Sentiment Index and Stock Market Return
Soomro, Najma Ali,Oad Rajput, Suresh Kumar,Soomro, Ishfaque Ahmed
The returns predictions and price movements of financial markets are predicted through online search engines. These search engines claim to trade sentiments of individual investors. This study aims to determine the changes in the American stock market returns due to Bitcoin investors’ sentiments. The Bitcoin sentiment index is constructed and used as a benchmark for Bitcoin investors’ sentiments from the time period of 2013-2018. This index is constructed through searching terms from top business magazines and journals available online. Such index is used as benchmark to determine the bitcoin potential investor sentiments and their impact on S&P returns. By using the ordinary least square method it was found that there is a negative impact of BSI on S&P returns. Further vector autoregressive(VAR) model is used to determine the association between these economic time series. According to VAR results it was found positive significant impact of S&P returns on BSI whereas, BSI itself was unable to predict S&P returns. Therefore, it can be said that S&P returns causes BSI.

Blockholder’s Presence, Board Structure, and CEO Compensation: Evidence from India
Jatana, Chhavi
The present study investigates the impact of blockholder’s presence and board structure on CEO compensation level as well as the pay-performance relationship (PPR) for the companies included in the S&P BSE 500 Index during the period 2015-2019. A panel data analysis revealed the preference towards accounting-based measures for fixing CEO pay than market performance. Further, the firm’s largest shareholders are found to play a weak supervisory role in strengthening the PPR, indicating collusion with CEOs to extract private benefits of control. However, outside blockholders are actively monitoring CEOs by limiting excessive compensation and positively moderating the PPR. With respect to board structure, independent directors are found to have a significant role in aligning pay with performance. The stewardship role of CEOs is also highlighted wherein they effectively align PPR while holding the position of board’s chairman simultaneously. The study has important implications for practitioners as well as policy-makers. It reveals governance areas requiring efforts for improvement in order to design performance-based compensation contracts.

Bonds vs. Equities: Information for Investment
Chang, Huifeng,d'Avernas, Adrien,Eisfeldt, Andrea L.
We provide robust empirical evidence that uncovers the reason for the observed closer relationship between the bond market versus the equity market and the macroeconomy. Our results indicate that the tight bond market-macroeconomy link is not due to differences in the investor base, but instead to the unique transformations of asset volatility and leverage that credit spreads and equity volatility represent. We focus on the investment channel. Using firm-level data, we find that the sensitivity of investment to equity volatility is highly significant, but changes sign in the cross section of firms depending on their distance to default. This sign change confounds aggregate inference. We rationalize these findings using a simple structural model of credit risk and investment with debt overhang.

Business Strategy and Cost of Bank Loans
Amin, Md Ruhul,Masum, Abdullah Al
Following Miles and Snow’s Business Strategy (BS) topology, we find that banks imposerelatively higher loan spreads for the firms that follow an Innovation-Oriented Business Strategy(IOBS). We further document that IOBS is positively associated with corporate risk measures suchas variances in equity returns and returns on assets. Overall, our findings suggest that banks charge a higher cost of debt in anticipation of borrowers’ payback riskiness from an IOBS.

CEO turnover, leadership vacuum, and stock market reactions
Joo, Jeong Hwan,Bae, Jihun
CEO departures with a delay in successor appointment create a leadership vacuum inducing operational disruption and strategic uncertainty. Such departures also produce turnaround benefits from cutting ties with a poorly performing CEO and by allowing additional time to search for a qualified successor. Prior studies fail to disentangle these perceived costs and benefits associated with CEO dismissal. After filtering out the turnaround benefits, we find the market reacts incrementally negatively to CEO departure announcements with a delay in successor appointment than those without such delay, capturing incremental switching costs caused by a leadership vacuum. We also find that the leadership vacuum cost is larger in a more volatile environment or with abandonment of a relay succession plan. Our findings contribute to CEO turnover literature by suggesting that a temporary leadership vacuum is an indicator of abandonment of a succession plan that has been influenced by a poorly performing CEO and that such abandonment creates an opportunity to achieve performance turnaround through a better successor.

Calculating the dispersion factor and the efficiency of solar cells based on their packages
Enayat, Wahidullah
Solar cells can be used to build large assemblies of solar panels. In this paper, the calculation of a dispersion factor and the efficiency of the solar cell is done by two methods, one is parallel, and the other in series. The results of parallel and series method packing show that the output power is the same in both methods and the current or voltage will be variable. For higher voltages is series panels and for higher currents is parallel panels. Or even it can be used as a combination of parallel and in series panels. The data also shows that parallel mode has more current with dispersion factor (0.37%) and efficiency of solar cells (0.03%). In series mode, has more voltage with dispersion factor (0.63%) and efficiency of solar cells (0.12%).

Climate Change Uncertainty and Supply Chain Financing
Cao, Zhangfan,Lee, Edward
This paper investigates the impact of climate change uncertainty (CCU) on supply chain financing. We find that firms significantly curtail trade credit during periods of high climate change uncertainty. By exploiting the staggered adoptions of state-level Climate Change Adaptation Plans (CCAP), which systematically bolster states’ effort in mitigating climate change, we show that firms offer significantly more trade credit following the adoptions of CCAP. Further analyses reveal that, while firms with environmental concerns and those operating in high-pollution industries offer less trade credit in general, they strategically extend more trade credit to customers during high CCU periods, implying their significant concern about their future sales due to the negative externality of their businesses. In addition, using interstate banking branching deregulation as an exogenous shock to firms’ access to bank credit, we conduct a triple-differences (DiDiD) analyses and document that the negative impact of climate risk on trade credit is less pronounced in states with more credit supply following the relaxations of interstate bank branching regulations. Our results are robust to an instrumental variable (IV) approach based on exogenous occurrences of major disasters in the US, propensity-score-matching (PSM) analyses, and the alternative measures of key variables. Collectively, our findings highlight that climate change, as a new yet increasingly prominent risk factor at the microeconomic level, can reshape the financial interactions along the supply chain.

Climate Change Valuation Adjustment (CCVA) using parameterized climate change impacts
Chris Kenyon,Mourad Berrahoui

We introduce Climate Change Valuation Adjustment (CCVA) to capture climate change impacts on CVA+FVA that are currently invisible assuming typical market practice. To discuss such impacts on CVA+FVA from changes to instantaneous hazard rates we introduce a flexible and expressive parameterization to capture the path of this impact to climate change endpoints, and transient transition effects. Finally we provide quantification of examples of typical interest where there is risk of economic stress from sea level change up to 2101, and from transformations of business models. We find that even with the slowest possible uniform approach to a climate change impact in 2101 there can still be significant CVA+FVA impacts on interest rate swaps of 20 years or more maturity. Transformation effects on CVA+FVA are strongly dependent on timing and duration of business model transformation. Using a parameterized approach enables discussion with stakeholders of economic impacts on CVA+FVA, whatever the details behind the climate impact.

Clustering Dynamics and Persistence for Financial Multivariate Panel Data
João, Igor Custodio,Lucas, Andre,Schaumburg, Julia
We introduce a new method for dynamic clustering of panel data with dynamics for cluster location and shape, cluster composition, and for the number of clusters. Whereas current techniques typically result in (economically) too many switches, our method results in economically more meaningful dynamic clustering patterns. It does so by extending standard cross-sectional clustering techniques using shrinkage towards previous cluster means. In this way, the different cross-sections in the panel are tied together, substantially reducing short-lived switches of units between clusters (flickering) and the birth and death of incidental, economically less meaningful clusters. In a Monte Carlo simulation, we study how to set the penalty parameter in a data-driven way. A systemic risk surveillance example for business model classification in the global insurance industry illustrates how the new method works empirically.

Cross-border capital flows and information spillovers across the equity and currency markets in emerging economies
Bathia, Deven,Demirer, Riza,Ferrer Lapeña, Roman,Raheem, Ibrahim
This paper presents a novel perspective on the interaction between equity and currency markets in emerging market economies (EMEs) by (i) examining the nonlinear effects of capital flows on return spillovers between the stock and currency markets in a sample of twelve EMEs via the causality-in-quantiles approach of Balcilar et al., (2016), and (ii) providing a comparative analysis of the influence of debt versus equity flows over the spillover patterns. We show that the causal effects of international debt and equity flows on return spillovers across the equity and FX markets are largely concentrated at lower quantiles, suggesting that the arrival of information via capital flows tends to ease shock transmissions across these markets. At the same time, international flows are found to facilitate the propagation of shocks in the direction of the currency market from the equity market, in line with the portfolio rebalancing hypothesis wherein equity market fluctuations lead to a subsequent correction in the currency market. The findings have important implications for investors and policy makers regarding the role of international capital flows as a facilitator of informational spillovers in emerging equity and currency markets.

Culture, Children and Couple Gender Inequality
Jessen, Jonas
This paper examines how culture impacts within-couple gender inequality. I compare child penalties of couples socialised in a more gender-egalitarian culture to those in a gender-traditional culture exploiting the setting of Germany's division and reunification. The long-run penalty on the female income share is 29.9 percentage points in West German couples, compared to 19.9 in East German couples. I additionally show that the arrival of children leads to a stronger increase in the share of housework performed by women in West Germany and that West German mothers are responsible for a larger share of child care as those from the East. A specialisation index indicates that children only lead to a permanent (re-)traditionalisation in West German couples. A battery of robustness checks confirms that differences between East and West socialised couples are not driven by current location, economic factors, day care availability or other smooth regional gradients. The main findings are complemented with an analysis of time-use diary data from the GDR and reunified Germany comparing parents with childless couples. Lastly, I show that attitudes towards maternal employment are more egalitarian among East Germans, but that the arrival of children leads to more traditional attitudes for both East and West Germans.

Customer Concentration and Corporate Risk-taking
Cao, Yue,Dong, Yizhe ,Ma, Diandian,Sun, Li
This study empirically investigates the relationship between customer concentration and corporate risk-taking. We find that overall customer concentration significantly reduces corporate risk-taking. However, the relationship varies across different settings. Specifically, the negative relationship between customer-base concentration and corporate risk-taking is only significantly present in more marketized regions, more competitive industries, firms with lower market shares, less innovative and non-state-owned firms, and those without major governmental or state-owned-enterprise customers. Moreover, our panel threshold models indicate significant threshold effects. When customer-base concentration is below the first threshold (low concentration level), it is positively associated with corporate risk-taking. When customer-base concentration increases to above the second threshold, the association turns significantly negative, suggesting that a highly concentrated customer base prompts suppliers to take more precautionary measures and avoid excessive risk-taking. Overall, our findings suggest that the concentration of a supplier’s customer base significantly impacts its risk-taking behaviours.

Deeply decarbonizing residential and urban central districts through photovoltaics plus electric vehicle applications
Takuro Kobashi,Younghun Choi,Yujiro Hirano,Yoshiki Yamagata,Kelvin Say

With the costs of renewable energy technologies declining, new forms of urban energy systems are emerging that can be established in a cost-effective way. The SolarEV City concept has been proposed that uses rooftop Photovoltaics (PV) to its maximum extent, combined with Electric Vehicle (EV) with bi-directional charging for energy storage. Urban environments consist of various areas, such as residential and commercial districts, with different energy consumption patterns, building structures, and car parks. The cost effectiveness and decarbonization potentials of PV + EV and PV (+ battery) systems vary across these different urban environments and change over time as cost structures gradually shift. To evaluate these characteristics, we performed techno-economic analyses of PV, battery, and EV technologies for a residential area in Shinchi, Fukushima and the central commercial district of Kyoto, Japan between 2020 and 2040. We found that PV + EV and PV only systems in 2020 are already cost competitive relative to existing energy systems (grid electricity and gasoline car). In particular, the PV + EV system rapidly increases its economic advantage over time, particularly in the residential district which has larger PV capacity and EV battery storage relative to the size of energy demand. Electricity exchanges between neighbors (e.g., peer-to-peer or microgrid) further enhanced the economic value (net present value) and decarbonization potential of PV + EV systems up to 23 percent and 7 percent in 2030, respectively. These outcomes have important strategic implications for urban decarbonization over the coming decades.

Design principles for agricultural risk management policies
Glauber, Joseph,Baldwin, Katherine,Antón, Jesús,Ziebinska, Urszula
Government support for agricultural risk management tools has grown substantially over the past two decades. While these tools can play a role in strengthening farm-level resilience by helping farmers to cope with the financial impact of adverse events, they also modify farmers' incentives to invest in risk-reducing measures and market tools. Policy design is critical to maximise effectiveness while minimising unintended consequences. This report reviews the accumulated experience on four types of publicly-supported agricultural risk management tools (ex post disaster aid, agricultural insurance, income stabilisation schemes and tax and savings measures). It suggests some basic principles on how countries can improve the design of their agricultural risk management policies, using a holistic approach and focusing on market failures. The report also highlights the need for more transparency on basic programme data, and for periodic public evaluation of existing programmes.

Determination of Long-term Investment Intentions: Moderating Role of Construal Priming
Praja, Arief Kusuma Among,Takarinawati, Suryanti,Sinaga, Obsatar
The current study investigates long-term investment intentions by linking the moderating role of construal priming in the causal relationship to defensive pessimism, which is a novel approach. The data was collected from 450 employees of private institutions by means of questionnaires and PLS-SEM was used in analysis. The results indicated a positive relationship between defensive pessimism, self-control, consumer financial product bias, and long-term investment. In addition, negative moderation role of the level of construal priming was observed, along with the links of defensive pessimism and long-term investment. Thus, the study provides crucial contexts for understanding long-term investment intentions from a behavioral perspective, which is often ignored in the financial management literature.

Estimates of the social cost of carbon have not changed over time
Richard S.J. Tol

Some claim that as knowledge about climate change accumulates, the social cost of carbon increases. A meta-analysis of published estimates shows that this is not the case. Correcting for inflation and emission year and controlling for the discount rate, kernel density decomposition reveals a stationary distribution. Actual carbon prices are almost everywhere below the estimated social cost of carbon.

Firm Commitments
Bolton, Patrick,Kacperczyk, Marcin T.
We provide a first empirical analysis of firm commitments to reduce their carbon emissions. A growing fraction of publicly traded companies around the world have already voluntarily made commitments to attain reductions in their emissions by a certain date or to reduce the emission intensity of their activities. What drives companies to make such commitments and what are their effects? We explore two major commitment movements, the carbon disclosure project (CDP), and the science-based target initiative (SBTi). Our main findings are, first that while the companies that make commitments subsequently further reduce their emissions, the effect of these commitment initiatives on overall emissions of publicly traded companies (including those that do not commit) has been small. Second, the companies that agree to commit, and those that make the most ambitious commitments, tend to be companies with lower carbon emissions. Third, firm commitments to reduce emissions are less prevalent in countries where governments have made national commitments. Overall, the movements to get companies to commit have been successful in drawing in the willing but have found greater resistance from the companies that need to reduce their emissions the most.

Global Index on Financial Losses due to Crime in the United States
Thilini Mahanama,Abootaleb Shirvani,Svetlozar Rachev

Crime can have a volatile impact on investments. Despite the potential importance of crime rates in investments, there are no indices dedicated to evaluating the financial impact of crime in the United States. As such, this paper presents an index-based insurance portfolio for crime in the United States by utilizing the financial losses reported by the Federal Bureau of Investigation for property crimes and cybercrimes. Our research intends to help investors envision risk exposure in our portfolio, gauge investment risk based on their desired risk level, and hedge strategies for potential losses due to economic crashes. Underlying the index, we hedge the investments by issuing marketable European call and put options and providing risk budgets (diversifying risk to each type of crime). We find that real estate, ransomware, and government impersonation are the main risk contributors. We then evaluate the performance of our index to determine its resilience to economic crisis. The unemployment rate potentially demonstrates a high systemic risk on the portfolio compared to the economic factors used in this study. In conclusion, we provide a basis for the securitization of insurance risk from certain crimes that could forewarn investors to transfer their risk to capital market investors.

Greening Monetary Policy: Evidence from the People's Bank of China
RPS Submitter, Banque de France,Macaire, Camille,Naef, Alain
In June 2018, the People’s Bank of China (PBoC) decided to include green financial bondsinto the pool of assets eligible as collateral for its Medium Term Lending Facility. The PBoCalso gave green financial bonds a “first-among-equals” status. We measure the impact of thepolicy on the yield spread between green and non-green bonds. We show that pre-reformtrends are minor, meaning that both green and non-green bonds yields evolved similarily atthe time of the reform. Using a difference-in-differences approach, we show that the policyincreased the spread by 46 basis points. Our approach differs from the literature in that wematch bonds under review with non-green bonds with similar characteristics and issued bythe same firm, which improves the relevance of firm fixed-effects. We also specificallyinvestigate the impact on green bonds. The granularity of the data (daily) also allows us toconduct a dynamic analysis by dividing the sample into weekly, monthly and quarterlyobservations. Our results also show that the impact of the reform starts to materialize afterthree weeks, has a maximum effect after three months, and has a persistent effect over sixmonths.3

Hedge Filtering
Hammarlid, Ola,Höök, Josef
In this paper we present a method for calculating the entire hedge surface of a derivative who’s future underlying asset has been simulated by a market simulator for example with the Monte Carlo method. Our method is built from work on penalized filtering techniques and is applied on a grid of hedges. Example using basis functions are also provided and we discuss the connection between penalization and use of basis functions. The method is tested on a a number of classical examples e.g. geometrical Brownian motion, the Heston model and the local volatility models with transaction costs. The results are very convincing in that for reasonable data sizes of just a couple of thousand data points, a working hedge function can be estimated. We believe that the generality of our method can be a competitive alternative to (or be combined with) recent methods that utilize deep learning for calculating hedges.

Hedging under rough volatility
Masaaki Fukasawa,Blanka Horvath,Peter Tankov

In this chapter we first briefly review the existing approaches to hedging in rough volatility models. Next, we present a simple but general result which shows that in a one-factor rough stochastic volatility model, any option may be perfectly hedged with a dynamic portfolio containing the underlying and one other asset such as a variance swap. In the final section we report the results of a back-test experiment using real data, where VIX options are hedged with a forward variance swap. In this experiment, using a rough volatility model allows to almost completely remove the bias and reduce the overall hedging error by a factor of 27% compared to traditional diffusion-based models.

High-Resolution Poverty Maps in Sub-Saharan Africa
Kamwoo Lee,Jeanine Braithwaite

Up-to-date poverty maps are an important tool for policy makers, but until now, have been prohibitively expensive to produce. We propose a generalizable prediction methodology to produce poverty maps at the village level using geospatial data and machine learning algorithms. We tested the proposed method for 25 Sub-Saharan African countries and validated them against survey data. The proposed method can increase the validity of both single country and cross-country estimations leading to higher precision in poverty maps of 44 Sub-Saharan African countries than previously available. More importantly, our cross-country estimation enables the creation of poverty maps when it is not practical or cost-effective to field new national household surveys, as is the case with many low- and middle-income countries.

Hindu Female Intestate Succession Laws and Their Impact on Fundamental Rights of the Elderly
Das, Bidisha,Banerjee, Shivangi
Females in Hindu families have long been discriminated against in terms of both inheritance and succession. For the duration of forty-nine years, men and women had different schemes with regard to inheritance where the woman was refused the right to marital property on the basis of her marital status. Fortunately, in 2005, the amendment to the Hindu Succession Act dealt with most inheritance-based injustice. However, it is observed that Hindu female intestates who die as married women continue to face injustice that is backed up by various discriminatory provisions under the Hindu Succession Act. This paper recognizes the constitutional implications of such provisions and their effect on the elderly.

How to Avoid another Derivative Crisis: Risk management for emerging markets
Al Janabi, Mazin A. M.
The losses reported by companies and financial institutions caused enormous alarm and concern in society, as well as debate and confusion on the appropriate use of derivatives instruments. Were derivatives responsible for these losses or was it simply their poor management? The fact is that while derivatives securities can effectively control and hedge financial risks, their uncontrolled use can be very dangerous. The chapter “Derivative Products in Emerging Markets and Prudential Regulations”, included in the monography Emerging Markets: Recent Developments, Challenges and Future Prospects (Nova Science Publishers, Inc., New York, 2018), examined the recent changes observed in derivatives trading in emerging markets, such as Mexico. In my experience as a practitioner and researcher of risk management and derivative products, I analyze the main obstacles to the adequate use of these instruments and offer practical recommendations for the use of efficient operational platforms, rigorous regulations and effective surveillance to discourage delinquencies and rogue trading within the financial service industry.

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 propose 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.

Interest Rate Swaps: A Comparison of Compounded Daily Versus Discrete Reference Rates
Jarrow, Robert,Li, Siguang
This paper studies the hedging effectiveness of interest rate swaps using different reference rates for eliminating interest rate risk from floating rate loans. Two different reference rates are studied. The first is a reference rate whose maturity, ∆, matches the payment interval of the floating rate loan. The second is a reference rate whose maturity is ∆/N. The prime examples are LIBOR and SOFR, respectively. We show that the ∆-based interest rate swap provides a good static hedge, but the ∆/N-based swap does not. Although dynamic hedging with the ∆-based interest rate swap is possible under some conditions, it both introduces model risk and increases transaction costs, making it a less practical alternative.

Investigating Socio-spatial Differences between Solo Ridehailing and Pooled Rides in Diverse Communities
Jason Soria,Amanda Stathopoulos

Transformative mobility services present both considerable opportunities and challenges for urban mobility systems. Increasing attention is being paid to ridehailing platforms and connections between demand and continuous innovation in service features; one of these features is dynamic ride-pooling. To disentangle how ridehailing impacts existing transportation networks and its ability to support economic vitality and community livability it is essential to consider the distribution of demand across diverse communities. In this paper we expand the literature on ridehailing demand by exploring community variation and spatial dependence in ridehailing use. Specifically, we investigate the diffusion and role of solo requests versus ride-pooling to shed light on how different mobility services, with different environmental and accessibility implications, are used by diverse communities. This paper employs a Social Disadvantage Index, Transit Access Analysis, and a Spatial Durbin Model to investigate the influence of both local and spatial spillover effects on the demand for shared and solo ridehailing. The analysis of 127 million ridehailing rides, of which 15% are pooled, confirms the presence of spatial effects. Results indicate that density and vibrancy variables have analogue effects, both direct and indirect, on demand for solo vs pooled rides. Instead, our analysis reveals significant contrasting effects for socio-economic disadvantage, which is positively correlated with ride-pooling and negatively with solo rides. Additionally, we find that higher rail transit access is associated with higher demand for both solo and pooled ridehailing along with substantial spatial spillovers. We discuss implications for policy, operations and research related to the novel insight on how pooled ridesourcing relate to geography, living conditions, and transit interactions.

Investment Banks’ Research Activities in the Post-Reform Era: Are Analysts’ Conflicts of Interest Still Alive?
Dubois, Michel,Moraru-Arfire, Andreea
In this paper, we identify a channel where affiliated banks maintain a positive gap between the implied return (computed from target price) of the corporate client stock and that of the client’s peer. This behavior is triggered after the business deal disclosure when investment banks, including those sanctioned in the Global Research Settlement Act, are most likely to exploit such conflicts. The client’s high institutional ownership and target prices issued in isolation exacerbate the implied return gap. We show that the subsequent sanctions incurred for the violation of Financial Industry Regulatory Authority’s rules effectively discourage the affiliated investment banks to favor their corporate clients via the client-peer channel.

Investor Sentiment, Media and Stock Returns: The Advancement of Social Media
Lachana, Ioanna,Schröder, David
Recent research in behavioural finance has shown the importance of investor sentiment to explain stock market returns. In light of the changes in the media scene from traditional print media towards social media platforms over the past decade, this paper analyses and compares the effect of sentiment indices obtained from different media sources in their ability to explain stock market movements. Using a large set of articles and reader comments covering the time from 2006 to 2020, we show that social media is better in capturing investor sentiment than traditional media outlets. The results of the paper highlight the importance of alternative media sources to understand market behaviour.

Labor Skill and Dividend Policy
Nguyen, Tilda,Jung, Boochun,Yang, Yanhua Sunny Sunny
We examine how firms’ labor skill heterogeneity affects dividend policy. Since it is more costly to hire, retain, and layoff skilled labor than unskilled labor, we hypothesize that firms relying more on skilled labor are more cautious in setting their dividend policy, which competes with funding for labor force. We find that firms with more skilled labor are less likely to distribute or increase dividends, and when they do so, the magnitudes are smaller. We further document that dividend increases by such firms are more strongly correlated with future earnings increases and are accompanied by stronger stock market reactions.

Least squares Monte Carlo methods in stochastic Volterra rough volatility models
Henrique Guerreiro,João Guerra

In stochastic Volterra rough volatility models, the volatility follows a truncated Brownian semi-stationary process with stochastic vol-of-vol. Recently, efficient VIX pricing Monte Carlo methods have been proposed for the case where the vol-of-vol is Markovian and independent of the volatility. Following recent empirical data, we discuss the VIX option pricing problem for a generalized framework of these models, where the vol-of-vol may depend on the volatility and/or not be Markovian. In such a setting, the aforementioned Monte Carlo methods are not valid. Moreover, the classical least squares Monte Carlo faces exponentially increasing complexity with the number of grid time steps, whilst the nested Monte Carlo method requires a prohibitive number of simulations. By exploring the infinite dimensional Markovian representation of these models, we device a scalable least squares Monte Carlo for VIX option pricing. We apply our method firstly under the independence assumption for benchmarks, and then to the generalized framework. We also discuss the rough vol-of-vol setting, where Markovianity of the vol-of-vol is not present. We present simulations and benchmarks to establish the efficiency of our method.

Lessons for the Age of Consequences: COVID-19 and the Macroeconomy
Storm, Servaas
Based on comparative empirical evidence for 22 major OECD countries, I argue that country differences in cumulative mortality impacts of SARS-CoV-2 are largely caused by: (1) weaknesses in public health competence by country; (2) pre-existing country-wise variations in structural socio-economic and public health vulnerabilities; and (3) the presence of fiscal constraints. The paper argues that these pre-existing conditions, all favorable to the coronavirus, have been created, and amplified, by four decades of neoliberal macroeconomic policies â€" in particular by (a) the deadly emphasis on fiscal austerity (which diminished public health capacities, damaged public health and deepened inequalities and vulnerabilities); (b) the obsessive belief of macroeconomists in a trade-off between ‘efficiency’ and ‘equity’, which is mostly used to erroneously justify rampant inequality; (c) the complicit endorsement by mainstream macro of the unchecked power over monetary and fiscal policy-making of global finance and the rentier class; and (d) the unhealthy aversion of mainstream macro (and MMT) to raising taxes, which deceives the public about the necessity to raise taxes to counter the excessive liquidity preference of the rentiers and to realign the interests of finance and of the real economy. The paper concludes by outlining a few lessons for a saner macroeconomics.

Leveraging latent persistency in United States patent and trademark applications to gain insight into the evolution of an innovation-driven economy
Iraj Daizadeh

Objective: An understanding of when one or more external factors may influence the evolution of innovation tracking indices (such as US patent and trademark applications (PTA)) is an important aspect of examining economic progress/regress. Using exploratory statistics, the analysis uses a novel tool to leverage the long-range dependency (LRD) intrinsic to PTA to resolve when such factor(s) may have caused significant disruptions in the evolution of the indices, and thus give insight into substantive economic growth dynamics. Approach: This paper explores the use of the Chronological Hurst Exponent (CHE) to explore the LRD using overlapping time windows to quantify long-memory dynamics in the monthly PTA time-series spanning 1977 to 2016. Results/Discussion: The CHE is found to increase in a clear S-curve pattern, achieving persistence (H~1) from non-persistence (H~0.5). For patents, the inflection occurred over a span of 10 years (1980-1990), while it was much sharper (3 years) for trademarks (1977-1980). Conclusions/Originality/Value: This analysis suggests (in part) that the rapid augmentation in R&D expenditure and the introduction of the various patent directed policy acts (e.g., Bayh-Dole, Stevenson-Wydler) are the key impetuses behind persistency, latent in PTA. The post-1990s exogenic factors seem to be simply maintaining the high degree and consistency of the persistency metric. These findings suggest investigators should consider latent persistency when using these data and the CHE may be an important tool to investigate the impact of substantive exogenous variables on growth dynamics.

Los Angeles Law Firms Before and After Recessions
Park, James J.
Major recessions often prompt significant changes at large law firms. This report studies Los Angeles firms over the past forty years to assess the impact of recessions on the Los Angeles legal market. It tracks the number of lawyers working in the Los Angeles offices of a sample of national law firms (half founded in Los Angeles and half founded outside of Los Angeles) over three recessions. It concludes that significant reductions in the attorneys employed by law firm offices after a recession largely reflect reversals of extraordinary growth prior to the recession. Because Los Angeles law firm offices were not expanding prior to 2020, the impact of the 2020 recession on the number of lawyers employed by national firms in Los Angeles may be modest.

Low emission zones: Effects on alternative-fuel vehicle uptake and fleet CO2 emissions
Jens F. Peters,Mercedes Burguillo,Jose M. Arranz

This study analyses the actual effect of a representative low-emission zone (LEZ) in terms of shifting vehicle registrations towards alternative fuel technologies and its effectiveness for reducing vehicle fleet CO2 emissions. Vehicle registration data is combined with real life fuel consumption values on individual vehicle model level, and the impact of the LEZ is then determined via an econometric approach. The increase in alternative fuel vehicles (AFV) registration shares due to the LEZ is found to be significant but fosters rather fossil fuel powered AFV and plug-in hybrid electric vehicles than zero emission vehicles. This is reflected in the average CO2 emissions of newly registered vehicles, which do not decrease significantly. In consequence, while the LEZ is an effective measure for stimulating the shift towards low emission vehicles, the support of non-electric AFV as low emission vehicles jeopardizes its effectiveness for decarbonizing the vehicle fleet.

MCTG:Multi-frequency continuous-share trading algorithm with GARCH based on deep reinforcement learning
Zhishun Wang,Wei Lu,Kaixin Zhang,Tianhao Li,Zixi Zhao

Making profits in stock market is a challenging task for both professional institutional investors and individual traders. With the development combination of quantitative trading and reinforcement learning, more trading algorithms have achieved significant gains beyond the benchmark model Buy&Hold (B&H). There is a certain gap between these algorithms and the real trading decision making scenarios. On the one hand, they only consider trading signals while ignoring the number of transactions. On the other hand, the information level considered by these algorithms is not rich enough, which limits the performance of these algorithms. Thus, we propose an algorithm called the Multi-frequency Continuous-share Trading algorithm with GARCH (MCTG) to solve the problems above, which consists of parallel network layers and deep reinforcement learning. The former is composed of three parallel network layers, respectively dealing with different frequencies (five minute, one day, one week) data, and day level considers the volatilities of stocks. The latter with a continuous action space of the reinforcement learning algorithm is used to solve the problem of trading stock shares. Experiments in different industries of Chinese stock market show our method achieves more extra profit comparing with basic DRL methods and bench model.

Modeling Non-Maturing Deposits: A Procedure for the Determination of the Minimal Time Series Length Required for Model Calibration and Back-Testing
Döpp, Sophie,Horovitz, Andre,Szimayer, Alexander
This paper proposes a procedure for the determination of the minimal length of the historical time series of daily deposit variations in accordance with an institution’s specific risk tolerance. In a previously released paper we developed a methodology to ascertain an institutional specific confidence level to be used for the same purposes. As the formula for the determination of the confidence level depends on the length of the deposit variations time series, we complete the procedural construct by proposing a means to estimating the minimal length of the daily deposit volume variations vector in accordance with Principle 9 of the EBA recommendations for liquidity risk management best practices. As the formula determining the minimal length of the volume time series will depend on the institutional specific confidence level to be used (as described in the previous paper), we will augment our procedure with a recursive method which converges to optimal values for both parameters. The procedure centers on the identification of structural breaks in the volume dynamics distributions. The resulting vectors of constant maturities are identified via distributional power statistical tests. We further illustrate the application of the proposed procedure using a dataset of daily demand deposit volumes from a fictional European savings bank.

Monotone Sharpe ratios and related measures of investment performance
Mikhail Zhitlukhin

We introduce a new measure of performance of investment strategies, the monotone Sharpe ratio. We study its properties, establish a connection with coherent risk measures, and obtain an efficient representation for using in applications.

NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation
Anastasis Kratsios,Cody Hyndman

Effective feature representation is key to the predictive performance of any algorithm. This paper introduces a meta-procedure, called Non-Euclidean Upgrading (NEU), which learns feature maps that are expressive enough to embed the universal approximation property (UAP) into most model classes while only outputting feature maps that preserve any model class's UAP. We show that NEU can learn any feature map with these two properties if that feature map is asymptotically deformable into the identity. We also find that the feature-representations learned by NEU are always submanifolds of the feature space. NEU's properties are derived from a new deep neural model that is universal amongst all orientation-preserving homeomorphisms on the input space. We derive qualitative and quantitative approximation guarantees for this architecture. We quantify the number of parameters required for this new architecture to memorize any set of input-output pairs while simultaneously fixing every point of the input space lying outside some compact set, and we quantify the size of this set as a function of our model's depth. Moreover, we show that no deep feed-forward network with commonly used activation function has all these properties. NEU's performance is evaluated against competing machine learning methods on various regression and dimension reduction tasks both with financial and simulated data.

Netherlands Commercial Court als mogelijke WHOA-rechter bij internationale herstructureringen (Jurisdiction of the Netherlands Commercial Court for WHOA proceedings in international restructurings)
Boon, Gert-Jan,Reinout, Vriesendorp,Sijbesma, Robin
Dutch abstract: De Wet homologatie onderhands akkoord (WHOA) is door de wetgever vormgegeven om ook in de internationale, grensoverschrijdende herstructureringspraktijk te worden toegepast. Ondanks diverse aspecten van de WHOA die dit bevorderen blijft één aspect nagenoeg onbesproken: de procestaal. In de parlementaire discussie heeft de minister voor Rechtsbescherming kort opgemerkt dat slechts Nederlands als procestaal een beperking kan zijn voor de WHOA en dat ‘[w]ellicht (…) in de toekomst geëxperimenteerd (kan) worden met behandeling van WHOA-zaken en het doen van gerechtelijke uitspraken in het Engels, zoals nu al gebeurt met commerciële geschillen bij de Netherlands Commercial Court’. In deze bijdrage behandelen wij de vraag in hoeverre verzoeken en geschillen in het kader van een WHOA-procedure door de Netherlands Commercial Court (NCC) in het Engels zouden kunnen worden behandeld. De NCC laat hierover zelf onduidelijkheid bestaan in de NCC Rules en het Zaaktoedelingsregister waarin vooralsnog niet wordt ingegaan op WHOA-akkoorden en daarmee samenhangende procedures. De wettelijke bevoegdheid van de NCC omvat echter naar onze mening al wel de WHOA-procedures. Alleen dient de NCC hiertoe enerzijds haar wettelijke bevoegdheid niet beperkt uit te leggen en anderzijds haar organisatie in te richten op de behandeling van een WHOA-procedure door rechters uit de ‘WHOA-pool’. Als de NCC deze route niet zelf zou willen faciliteren, biedt de Tijdelijke Experimentenwet rechtspleging (Experimentenwet) de Minister een tijdelijk alternatief voor behandeling van WHOA-procedures bij de NCC. English abstract: The Dutch legislator drafted the Wet homologatie onderhands akkoord (WHOA) in such a way that it can also be used in international, cross-border restructurings. Although various aspects of the WHOA support its international use, one aspect is left largely unaddressed: the language of the case. During the parliamentary discussions on the WHOA, the Minister for Legal Protection observed that the use of Dutch as the sole language of the case could be an impediment in practice. Therefore, he suggested that in the future, there could be experiments to use English as the language of the case, as is currently already done for other commercial disputes before the Netherlands Commercial Court (NCC). In this paper, we explore to what extent requests and disputes in the course of a WHOA proceeding could be dealt with in English by the NCC. In the NCC Rules, as well as in the Case Allocation Register (Zaaktoedelingsregister), the NCC does not address whether and to what extent it can hear requests in a WHOA proceeding. We argue that, the NCC’s statutory jurisdiction extends to requests in WHOA proceedings. Therefore, the NCC should not interpret the scope of its own jurisdiction restrictively. Furthermore, the NCC should be organised in such a way that the judges, which are part of the ‘pool’ of WHOA judges, can hear cases in English before the NCC. Should the NCC not facilitate this route itself, the Temporary Act on Experiments in Administration of Justice (Tijdelijke Experimentenwet rechtspleging) would allow the Minister to authorise the NCC, by way of a temporary experiment, to hear requests regarding a WHOA proceeding before the NCC.

On representation of energy storage in electricity planning models
James H Merrick,John E.T. Bistline,Geoffrey J. Blanford

This paper considers the representation of energy storage in electricity sector capacity planning models. The incorporation of storage in long-term systems models of this type is increasingly relevant as the cost of storage technologies, particularly batteries, and of complementary variable renewable technologies, decline. To value storage technologies appropriately, a representation of linkages between time periods is required, breaking classical temporal aggregation strategies that greatly improve computation time. This paper appraises approaches to address this problem, highlighting a common underlying structure and challenges of aggregation at relevant geographical scales, and investigates improvements on the literature state of the art. We also demonstrate a novel decomposition scheme to avoid temporal aggregation for applications where longer runtimes are permissible. These examples frame aspects of the problem ripe for contributions from the operations research community.

On the Role of Incentives in Evolutionary Approaches to Organizational Design
Stephan Leitner

This paper introduces a model of a stylized organization that is comprised of several departments that autonomously allocate tasks. To do so, the departments either take short-sighted decisions that immediately maximize their utility or take long-sighted decisions that aim at minimizing the interdependencies between tasks. The organization guides the departments' behavior by either an individualistic, a balanced, or an altruistic linear incentive scheme. Even if tasks are perfectly decomposable, altruistic incentive schemes are preferred over individualistic incentive schemes since they substantially increase the organization's performance. Interestingly, if altruistic incentive schemes are effective, short-sighted decisions appear favorable since they do not only increase performance in the short run but also result in significantly higher performances in the long run.

On the Time-Inconsistent Deterministic Linear-Quadratic Control
Hongyan Cai,Danhong Chen,Yunfei Peng,Wei Wei

A fundamental theory of deterministic linear-quadratic (LQ) control is the equivalent relationship between control problems, two-point boundary value problems and Riccati equations. In this paper, we extend the equivalence to a general time-inconsistent deterministic LQ problem, where the inconsistency arises from non-exponential discount functions. By studying the solvability of the Riccati equation, we show the existence and uniqueness of the linear equilibrium for the time-inconsistent LQ problem.

On time-consistent multi-horizon portfolio allocation
Cerreia-Vioglio, Simone,Ortu, Fulvio ,Rotondi, Francesco,Severino, Federico
We analyse the problem of constructing multiple mean-variance portfolios over increasing investment horizons in stochastic interest rate markets. The traditional one-period mean-variance optimal portfolios of Hansen and Richard (1987) require the replication of two payoffs. When several maturities are considered, different payoffs have to be replicated each time, with an impact on transaction costs. Using martingale decomposition techniques and introducing a family of risk-adjusted measures linked to increasing maturities, we provide an intertemporal version of the traditional orthogonal decomposition of asset returns. This allows us to construct a multi-horizon mean- variance frontier that is time-consistent and requires the replication of solely two payoffs for all horizons under consideration. When transaction costs are taken into account, our time-consistent mean-variance frontier may outperform the traditional mean-variance optimal strategies in terms of Sharpe ratio. Some interesting examples of this fact come from long-term contracts as life annuities.

Optimize your Investment Portfolio in Bearish Markets
Al Janabi, Mazin A. M.
Since the 2008-2009 global financial crisis, VaR (Value-at-Risk) techniques have become critical tools for monitoring and predicting the market risk and liquidity of financial assets. These financial risk modeling techniques, which have been recognized by the Bank for International Settlements (BIS) or the Basel Committee on capital adequacy and bank regulations, measure and prevent any potential losses that arise, not only from securities’ price changes and the interdependence between the different types of assets (stocks, currencies, interest rates or commodities), but also from their negative tail co-movements in bearish market conditions. In the event of a financial crisis or market downturn, adequate liquidity risk modeling is advisable. In fact, the main advantage of VaR models is their focus on downside risk (i.e., the impact of the results of negative tails) and their direct interpretation in monetary terms. Nevertheless, particularly in times of financial turbulence, traditional VaR models do not properly consider nonlinear dependence between portfolio assets and become inefficient in illiquid market scenarios. Despite the advances in measurement models, obtaining precise market liquidity risk estimations and applying them to optimize portfolios continues to be a challenge for financial institutions.

Private equity buyouts, credit constraints, and firm exports
Lavery, Paul,Serena, José María,Spaliara, Marina‐Eliza,Tsoukas, Serafeim
We analyse the impact of private equity buyouts on firm exports, on a panel of UK non-financial firms over 2004--2017. Using difference-in-differences estimations, we show that private equity ownership increases the probability of exporting, the value of exports, and the export to sales ratio. We further show that the positive impact of private equity ownership on exports holds only after private-to-private buyouts, or acquisitions of small or young target firms. Our findings suggest that private equity investors mitigate the credit constraints faced by their portfolio companies, hence boosting their exports.

Production externalities and dispersion process in a multi-region economy
Minoru Osawa,José M. Gaspar

We consider an economic geography model with two inter-regional proximity structures: one governing goods trade and the other governing production externalities across regions. We investigate how the introduction of the latter affects the timing of endogenous agglomeration and the spatial distribution of workers across regions. As transportation costs decline, the economy undergoes a progressive dispersion process. Mono-centric agglomeration emerges when inter-regional trade and/or production externalities incur high transportation costs, while uniform dispersion occurs when these costs become negligibly small (i.e., when distance dies). In multi-regional geography, the network structure of production externalities can determine the geographical distribution of workers as economic integration increases. If production externalities are governed solely by geographical distance, a mono-centric spatial distribution emerges in the form of suburbanization. However, if geographically distant pairs of regions are connected through tight production linkages, multi-centric spatial distribution can be sustainable.

Reinforcement Learning with Expert Trajectory For Quantitative Trading
Sihang Chen,Weiqi Luo,Chao Yu

In recent years, quantitative investment methods combined with artificial intelligence have attracted more and more attention from investors and researchers. Existing related methods based on the supervised learning are not very suitable for learning problems with long-term goals and delayed rewards in real futures trading. In this paper, therefore, we model the price prediction problem as a Markov decision process (MDP), and optimize it by reinforcement learning with expert trajectory. In the proposed method, we employ more than 100 short-term alpha factors instead of price, volume and several technical factors in used existing methods to describe the states of MDP. Furthermore, unlike DQN (deep Q-learning) and BC (behavior cloning) in related methods, we introduce expert experience in training stage, and consider both the expert-environment interaction and the agent-environment interaction to design the temporal difference error so that the agents are more adaptable for inevitable noise in financial data. Experimental results evaluated on share price index futures in China, including IF (CSI 300) and IC (CSI 500), show that the advantages of the proposed method compared with three typical technical analysis and two deep leaning based methods.

Separability vs. robustness of Orlicz spaces: financial and economic perspectives
Felix-Benedikt Liebrich,Max Nendel

We investigate robust Orlicz spaces as a generalisation of robust $L^p$-spaces. Two constructions of such spaces are distinguished, a top-down approach and a bottom-up approach. We show that separability of robust Orlicz spaces or their subspaces has very strong implications in terms of the dominatedness of the set of priors and the lack of order completeness. Our results have subtle implications for the field of robust finance. For instance, norm closures of bounded continuous functions with respect to the worst-case $L^p$-norm, as considered in the $G$-framework, lead to spaces which are lattice isomorphic to a sublattice of a classical $L^1$-space lacking, however, any form of order completeness. We further show that the topological spanning power of options is always limited under nondominated uncertainty.

Social Responsibility and Bank Resiliency
Gehrig, Thomas,Iannino, Maria Chiara,Unger, Stephan
We provide transatlantic evidence about the relation between social responsibility and resiliency in the banking industry. We analyse various measures of resiliency, an exposure measure (SRISK) and a contribution measure (Delta CoVaR) to systemic risk, as well as measures of systematic risk (beta) and insolvency risk (z-score). Social responsibility is measured by Thomson Reuters’ ESG-scores and its pillars, both according to the older Asset 4 and the present TR ESG Refinitiv classification. We find that the social aggregate score significantly enhances resiliency in all dimensions and in both classifications. On the level of subcategories, we identify significant common resiliency enhancing factor proxies for long-term orientation, such as product responsibility and workforce training, while short-term objectives proxied by shareholder orientation tend to relate to lower levels of resiliency. Looking deeper into the components of each ESG pillar, we also discover significant transatlantic differences mainly related to the different organization of labour markets as well as the board structure

Sovereign rating methodologies, ESG and climate change risk: an overview
Angelova, Denitsa,Bosello, Francesco,Bigano, Andrea,Giove, Silvio
We review the sovereign credit rating methodologies of three credit rating agencies (Moody’s, S&P and Fitch) and analyze how they currently accommodate climate change risk and ESG considerations. We elaborate on the differences between the three rating methodologies and critically evaluate their suitability and limitations. We propose lines of improvement with respect to the indicator selection, normalization, aggregation and weighting procedures as well as the use of the sovereign rating indicator in connection with climate change scenarios.

Stock market volatility and public information flow: A non-linear perspective
Bertelsen, Kristoffer Pons,Borup, Daniel,Jakobsen, Johan Stax
The relationship between the level of stock market volatility and public information flow is non-linear, resembling a bell-shaped function. Medium levels of information flow generate heightened volatility, whereas weak and strong information flow do not, regardless of whether news are negative or positive. This novel empirical finding is established in a new realized GARCH model with time-varying intercept, measuring changes in the overall volatility level, which is governed by a new measure of daily macroeconomic news flow. We also device a test for model specification. States of medium information flow are characterized by elevated disagreement about the future stance of the economy compared to states of weak or strong information flow, such that our findings are explained by disagreement equilibrium-based models. We confirm our findings on international data.

Symbol Dynamics, Information theory and Complexity of Economic time series
Geoffrey Ducournau

We propose to examine the predictability and the complexity characteristics of the Standard&Poor500 dynamics behaviors in a coarse-grained way using the symbolic dynamics method and under the prism of the Information theory through the concept of entropy and uncertainty. We believe that experimental measurement of entropy as a way of examining the complexity of a system is more relevant than more common tests of universality in the transition to chaos because it does not make any prior prejudices on the underlying causes associated with the system dynamics, whether deterministic or stochastic. We regard the studied economic time series as being complex and propose to express it in terms of the amount of information this last is producing on different time scales and according to various scaling parameters.

Testing the effectiveness of unconventional monetary policy in Japan and the United States
Daisuke Ikeda,Shangshang Li,Sophocles Mavroeidis,Francesco Zanetti

Unconventional monetary policy (UMP) may make the effective lower bound (ELB) on the short-term interest rate irrelevant. We develop an empirical test of this `irrelevance hypothesis,' based on a simple idea that under the hypothesis, the short rate can be excluded in any empirical model that accounts for alternative measures of monetary policy. We develop a theoretical model that underpins this hypothesis, and test it empirically for Japan and the United States using a structural vector autoregressive model with the ELB. For each country, we firmly reject the hypothesis but find that UMP has had strong delayed effects.

The Future of EU Financial Law
Busch, Danny
The imprint of the major themes of our time is as apparent in the field of financial lawas in any other. Obvious examples are the coronavirus crisis, sustainability, the onwardmarch of technology, the unceasing struggle between integration and federalism on theone hand and protectionism and nationalism on the other and, last but not least, thepressure brought to bear by leading geopolitical powers such as China, the UnitedStates and Russia. These forces have largely shaped financial law in Europe, especiallyin the recent past, and will continue to do so in the future.Where these forces are actually leading us, however, is less easy to predict. It remainsto be seen whether all the new European rules and legislative proposals will produce afully integrated, sustainable and digital European Capital Markets Union and acomplete and smoothly functioning European Banking Union. And it is still much tooearly to gauge whether Brexit will work out well for the EU27.But one thing is certain: Europe’s tentacles reach deep into financial law. No matterwhat finance-related topic one studies, whether it be combating money laundering andterrorist financing or issues such as deposit insurance schemes, non-performing loans,the coronavirus crisis or local products such as investment-linked policies and shareleasing, one is bound sooner or later to have to deal with EU law. In other words, forpractitioners of financial law, the need to deal with EU law is simply a fact of life. Aslong as the European Union continues to exist, of course.

The Importance of Measuring Liquidity Risk with Smart Financial Applications
Al Janabi, Mazin A. M.
Over the past few days, alarm bells have been ringing for the risk of recession in the world’s leading economies (Germany, United Kingdom, Italy, Brazil and Mexico). Deceleration is affecting several regions in the world and might even become more widespread, exacerbating investor mistrust and financial market instability produced by the U.S.-China trade war, among other uncertainty factors. Investors have transferred part of their investment portfolios to safe haven assets, such as sovereign bonds, with investor mistrust at record lows in recent years. Managing your investment portfolio when an economic cycle is drawing to an end can be tricky. Even though some experts recommend rebalancing asset allocation, buying treasury bonds, focusing on raw materials, commodities or real estate investment, the most important thing is to learn how to manage risk. In the current context of uncertainty and adverse market conditions, assessing investment portfolio performance optimization, as well as liquidity risk, is crucial, as explained in the chapter “Theoretical and practical foundations of liquidity-adjusted value-at-risk (LVaR): optimization algorithms for portfolio selection and management” of the recently published book Expert Systems in Finance. Smart Financial Applications in Big Data Environments (Routledge, Taylor & Francis Group, 2019).

The Tax Benefits of Direct Indexing, And How They Are Affected by the Biden Tax Plan
Sosner, Nathan,Gromis, Michael,Krasner, Stanley
Direct indexing is an investment approach that seeks to track the performance of a stock index by investing in individual stocks comprising the index. An investor holding a direct indexing portfolio can obtain tax benefits by harvesting losses on individual stock positions. We show that investors with allocations to hedge funds and derivatives are the most likely category of investors to have systematic short-term capital gains in their portfolios and, therefore, benefit the most from losses harvested by direct-indexing strategies. After the initial few years since inception, tax benefits offered by a direct-indexing strategy are only available to those investors who can take advantage of the difference in tax rates applicable to short-term and long-term capital gains, that is, investors with short-term capital gains from other investments. In connection with this, we show how tax benefits are affected by equalizing the tax rate applicable to long-term and short-term capital gains, like under the proposed Biden Tax Plan. Investors can increase tax benefits of a direct-indexing strategy by contributing capital to the strategy and increase them even further by combining the strategy with a charitable giving program. We use a character-deferral decomposition to explain why tax benefits of direct-indexing strategies decay with time since inception and why these tax benefits are increased by capital contributions and charitable giving.

The aftermarket performance of Spanish REITs
Castaño, Leticia,Farinós Viñas, José Emilio,Ibáñez, Ana M.
Since 2013, when the market for REITs started in Spain, the number of these investment vehicles has grown steadily. At the end of 2019, Spanish REITs ranked third in Europe in terms of market capitalisation, and first in terms of the number of REITs (EPRA, 2020). This research investigates the abnormal performance of REITs in the Spanish market for 6-, 12- and 24-month post-admission windows during the period from November 2013 to January 2020. We obtain evidence that issuers experience economically and statistically significant negative abnormal returns during the two years after going public. These results are robust to the different metrics, estimations and tests used. The differentiating characteristics of the market analysed (mainly the fact that the flotations were not carried out through an Initial Public Offering, unlike most previous studies, but through a direct listing procedure) are particularly relevant to determine the level of aftermarket performance.

Three Legal Reflections on the “Crude Oil Treasure” Incident: Starting with the CME Rule Change
Xu, Duoqi,Wang, Peiran,Wang, Yicheng
The fall of crude oil futures into extreme negative prices has raised concerns globally. On the one hand, although the negative price mechanism facilitates market price discovery to some extent, in the delivery month it can trigger serious consequences such as abnormal market price fluctuations due to insufficient liquidity, which creates extreme market injustice and raises suspicion of manipulation. On the other hand, the reckless change of programs, which allow negative prices, lacks necessary legitimacy at the procedural level. Market participants who have been treated unfairly should actively defend their rights, and United States regulators and the Chicago Mercantile Exchange Group Inc. (CME) should explain to the market with thorough investigations and credible conclusions. The negative oil price incident is a profound warning and lesson for financial institutions and regulators in China.

Tuning Trend Following Strategies with Macro ESG Data
Morgenstern, Christian,Coqueret, Guillaume,Kelly, James
Trend Following (TF) is a well-known and documented strategy which has been employed by practi- tioners since the 1980s. The focus so far has been on the alpha-generating potential of the strategies and in particular on extending the strategy to a broader range of asset markets. In this paper, we describe how to integrate sovereign Environmental, Social and Governance (ESG) information into a macro TF strategy. Notably, we find that the ESG exposure of the macro portfolios can be substantially increased without any cost in performance.

When Uncertainty and Volatility Are Disconnected: Implications for Asset Pricing and Portfolio Performance
Ait-Sahalia, Yacine,Matthys, Felix,Osambela, Emilio,Sircar, Ronnie
We analyze an environment where the uncertainty in the equity market return and its volatility are both stochastic, generating situations where they can move in tandem as one might expect, but also situations where they are disconnected. We solve in closed form a representative investor's optimal asset allocation and derive the resulting conditional equity premium and risk-free rate in equilibrium. Empirically, we find that equity returns respond negatively to contemporaneous volatility (consistent with the prevalence of the leverage effect in the data), but respond positively, and consistently across horizons, to the uncertainty component in the model. Our results therefore show that the equity premium appears to be earned for facing uncertainty, especially high uncertainty that is disconnected from low volatility, rather than for facing volatility as traditionally assumed. Incorporating the possibility of a disconnect between volatility and uncertainty significantly improves portfolio performance, over and above the performance obtained by conditioning on volatility only.

Who owns tobacco stocks?
Blitz, David,Swinkels, Laurens
We compare the ownership characteristics of tobacco stocks with their peers in the same country and industry group. We find lower reported ownership for stocks in the tobacco industry, which suggests that anonymous investors are larger owners of these sin stocks. Compared to peer stocks, U.S. and U.K. asset managers collectively overweight tobacco stocks, while norm-constrained investors such as sovereign wealth funds and pension funds underweight tobacco stocks. Passive managers have large stakes in tobacco stocks that are in line with the weights of these stocks in broad capitalization-weighted indices, indicating that passive replication of ethically screened indices is still a niche. We also identify some prominent active investors who take large positions in tobacco stocks.

‘Legaformalesty’ â€" A Different Approach for a New Amnesty in Albania
Meka, Elvin S.
Governments have periodically turned to tax amnesties, as a mechanism used in the frame of their fiscal programs, or partly to activate more capital in the national economy and establishing the fiscal rule to a new higher level. As a non-traditional instrument, it can be used to smooth out inconsistencies, arising from the existence of a tight tax regulatory framework, in an economic environment that experiences highly dynamic changes, within a short period of time. The implementation of the fiscal amnesty is not mainly related more to a country’s stage of economic development, or to the level and professional competence of the bodies collecting fiscal obligations, than to the practical objective that is required to be achieved.In Albania, various governments have made several efforts, back in 2011 and 2017, to implement the fiscal amnesty but, unfortunately, they were partial and failed to meet their initial goals and objectives. This is because they were not comprehensive and, above, all did not contain the key element, that of legal amnesty and secrecy.For an amnesty to be successful in Albania, it is proposed that, along standard elements of tax amnesty, it must also consider the legalization of all real assets built without permission, or illegal ones, as well as the formalization of various business activities, combined with the legal amnesty. Combining these elements would create an advantageous synergy, in terms of maximizing the expected economic effect, thus using amnesty not just as a classic instrument of collecting some more budget revenues and increasing fiscal discipline in the future, but as a lever that produces an efficient moment for the country’s economic development.