Research articles for the 2021-03-03

'Shiny' Crypto Assets: A Systemic Look at Gold-Backed Cryptocurrencies during the COVID-19 Pandemic
Jalan, Akanksha,Matkovskyy, Roman,Yarovaya, Larisa
Are gold-backed cryptocurrencies as stable as gold during crises? In this paper, we assess whether gold-backed stablecoins, purported to be safer than other cryptocurrencies indeed demonstrate safe haven characteristics during the COVID-19 pandemic. In the digital assets’ ecosystem, gold-backed cryptocurrencies have potential to address the regulatory and policy concerns by decreasing volatility of cryptocurrency prices and facilitating a broader cryptocurrency adoption. We find that during the COVID-19 pandemic, gold-backed cryptocurrencies were susceptible to volatility transmitted from gold markets. However, unlike gold, they were unable to quickly recover from the COVID-19 shock. Gold-backed stablecoins were less volatile in comparison to Bitcoin but did not show the same persistence to the COVID-19 shock as gold, their underlying asset.

A unified approach to xVA with CSA discounting and initial margin
Francesca Biagini,Alessandro Gnoatto,Immacolata Oliva

In this paper we extend the existing literature on xVA along three directions. First, we enhance current BSDE-based xVA frameworks to include initial margin in presence of defaults. Next, we solve the consistency problem that arises when the front-office desk of the bank uses trade-specific discount curves (CSA discounting) which differ from the discount rate adopted by the xVA desk. Finally, we clarify the impact of aggregation of several sub-portfolios of trades on the xVA-valuation of the resulting global portfolio and study related non-linearity effects.

Adaptive Bernstein Copulas and Risk Management
Dietmar Pfeifer,Olena Ragulina

We present a constructive approach to Bernstein copulas with an admissible discrete skeleton in arbitrary dimensions when the underlying marginal grid sizes are smaller than the number of observations. This prevents an overfitting of the estimated dependence model and reduces the simulation effort for Bernstein copulas a lot. In a case study, we compare different approaches of Bernstein and Gaussian copulas w.r.t. the estimation of risk measures in risk management.

Approaches to Asian Option Pricing with Discrete Dividends
Jacob Lundgren,Yuri Shpolyanskiy

The method and characteristics of several approaches to the pricing of discretely monitored arithmetic Asian options on stocks with discrete, absolute dividends are described. The contrast between method behaviors for options with an Asian tail and those with monitoring throughout their lifespan is emphasized. Rates of convergence are confirmed, but greater focus is put on actual performance in regions of accuracy which are realistic for use by practitioners. A hybrid approach combining Curran's analytical approximation with a two-dimensional finite difference method is examined with respect to the errors caused by the approximating assumptions. For Asian tails of equidistant monitoring dates, this method performs very well, but as the scenario deviates from the method's ideal conditions, the errors in the approximation grow unfeasible. For general monitoring straightforward solution of the full three-dimensional partial differential equation by finite differences is highly accurate but suffers from rapid degradation in performance as the monitoring interval increases. For options with long monitoring intervals a randomized quasi-Monte Carlo method with control variate variance reduction stands out as a powerful alternative.

Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas
Grassi, Stefano,Violante, Francesco
Starting from the Cholesky-GARCH model, recently proposed by Darolles, Francq, and Laurent (2018), the paper introduces the Block-Cholesky GARCH (BC-GARCH). This new model adapts in a natural way to the asset pricing framework. After deriving conditions for stationarity, uniform invertibility and beta tracking, we investigate the finite sample properties of a variety of maximum likelihood estimators suited for the BC-GARCH by means of an extensive Monte Carlo experiment. We illustrate the usefulness of the BC-GARCH in two empirical applications. The first tests for the presence of beta spillovers in a bivariate system in the context of the Fama and French (1993) three factor framework. The second empirical application consists of a large scale exercise exploring the cross-sectional variation of expected returns for 40 industry portfolios.

Attention to Inattention: Evidence from Private Acquisitions
Huang, Emily J.,Ma, Qingzhong,Zhang, Wei Athena
When a new blockholder (NewB) is expected to form in private firm acquisitions paid with stock, investors react strongly to the perceived certification and monitoring effects. The salience of a NewB, however, induces investor inattention to other information, opening doors for managerial opportunism. Financially weak acquirers pay attention to inattention and sneak in speculative deals. Our findings support these hypotheses. First, acquirers’ announcement-period abnormal returns are significantly associated with the presence of a NewB, but not with acquirers’ financial health that indicates managerial opportunism. Second, the NewB acquirers are financially weak. Finally, they underperform in the long run.

Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle
Piotr Tomasz Makowski,Yuya Kajikawa

There is a resurging interest in automation because of rapid progress of machine learning and AI. In our perspective, innovation is not an exemption from their expansion. This situation gives us an opportunity to reflect on a direction of future innovation studies. In this conceptual paper, we propose a framework of innovation process by exploiting the concept of unit process. Deploying it in the context of automation, we indicate the important aspects of innovation process, i.e. human, organizational, and social factors. We also highlight the cognitive and interactive underpinnings at micro- and macro-levels of the process. We propose to embrace all those factors in what we call Innovation-Automation-Strategy cycle (IAS). Implications of IAS for future research are also put forward.

Keywords: innovation, automation of innovation, unit process, innovation-automation-strategy cycle

Central Bank Independence and Systemic Risk
Andries, Alin Marius,Podpiera, Anca Maria,Sprincean, Nicu
We investigate the relationship of central bank independence and banks’ systemic risk measures. Our results support the case for central bank independence, revealing that central bank independence has a robust, negative, and significant impact on the contribution and exposure of a bank to systemic risk. Moreover, the impact of central bank independence is similar for the stand-alone risk of individual banks. Secondarily, we study how the central bank independence affects the impact of selected country and banking system indicators on these systemic measures. The results show that central bank independence may exacerbate the effect of a crisis on the contribution of banks to systemic risk. However, central bank independence seems to mitigate the harmful effect of a bank’s high market power on its systemic risk contribution.

Cheap Talk and Cherry-Picking: What ClimateBert has to say on Corporate Climate Risk Disclosures
Bingler, Julia Anna,Kraus, Mathias,Leippold, Markus
Disclosure of climate-related financial risks greatly helps investors assess companies' preparedness for climate change. Voluntary disclosures such as those based on the recommendations of the Task Force for Climate-related Financial Disclosures (TCFD) are being hailed as an effective measure for better climate risk management. We ask whether this expectation is justified. We do so with the help of a deep neural language model, which we christen ClimateBert. We train ClimateBert on thousands of sentences related to climate-risk disclosures aligned with the TCFD recommendations. In analyzing the disclosures of TCFD-supporting firms, ClimateBert comes to the sobering conclusion that the firms' TCFD support is mostly cheap talk and that firms cherry-pick to report primarily non-material climate risk information. From our analysis, we conclude that the only way out of this dilemma is to turn voluntary reporting into regulatory disclosures.

Cleaning Corporate Governance
Frankenreiter, Jens,Hwang, Cathy,Nili, Yaron,Talley, Eric L.
Although empirical scholarship dominates the field of law and finance, much of it shares a common vulnerability: an abiding faith in the accuracy and integrity of a small, specialized collection of corporate governance data. In this paper, we unveil a novel collection of three decades’ worth of corporate charters for thousands of public companies, which shows that this faith is misplaced.We make three principal contributions to the literature. First, we label our corpus for a variety of firm- and state-level governance features. Doing so reveals significant infirmities within the most well-known corporate governance datasets, including an error rate exceeding eighty percent in the G-Index, the most widely used proxy for “good governance” in law and finance. Correcting these errors substantially weakens one of the most well-known results in law and finance, which associates good governance with higher investment returns. Second, we make our corpus freely available to others, in hope of providing a long-overdue resource for traditional scholars as well as those exploring new frontiers in corporate governance, ranging from machine learning to stakeholder governance to the effects of common ownership. Third, and more broadly, our analysis exposes twin cautionary tales about the critical role of lawyers in empirical research, and the dubious practice of throttling public access to public records.

Courting Innovation: The Effects of Litigation Risk on Corporate Innovation
Hassan, M. Kabir,Houston, Reza,Karim, Md. Sydul
In this study, we examine the impact of class action litigation shocks on corporate innovation. Our experimental design is based on an unanticipated Court ruling that reduces the risk of shareholder class action lawsuits for firms located in the U.S. Ninth Circuit. Innovation output of firms headquartered in the Ninth Circuit increases significantly following this ruling, relative to firms outside of the Ninth Circuit. This result is consistent with the threat of litigation restricting innovation. Our results are more pronounced for firms with good corporate governance, greater institutional ownership, and higher CEO ownership. We also find that headquartering states’ characteristics (e.g., local political corruption and unified state control) significantly impact post-ruling innovation output. We conclude that a reduction in the threat of class action litigation leads firms to increase innovation.

Dissecting Climate Risks: Are they Reflected in Stock Prices?
Faccini, Renato,Matin, Rastin,Skiadopoulos, George S.
We construct novel proxies of physical and transition climate risks by conducting textual analysis of climate-change news over 2000-2018. This analysis uncovers four textual risk factors related to the topics of U.S. climate policy, international summits, natural disasters, and global warming, respectively. The first two factors proxy transition risks, whereas the last two proxy physical risks. We find that only the climate policy factor is priced in the U.S. stock market, with the evidence being more pronounced over 2012-2018. The documented positive premium is consistent with the argument that investors hedge short-term transition risks. We validate this explanation using a narrative approach to mark the content of climate news. Our results imply that investors' attention is an important driver of asset returns.

ETFs in Liquidity Provision
Koont, Naz,Ma, Yiming,Zeng, Yao
We conceptualize and quantify liquidity provision by index-tracking fixed-income exchange-traded funds (ETFs), which have more than tripled in size since 2015 to reach $1 trillion in 2020. We show that they provide liquidity by pooling investors' idiosyncratic liquidity risks and by relying on arbitrage by authorized participants (APs), which are mostly dealer banks. However, because of AP balance sheet constraints, ETF liquidity provision is subject to disruptions that coincide with strains at dealer banks, as evident during the COVID-19 crisis. Further, ETF liquidity provision comes at the expense of their ability to track the underlying bond index, and this tradeoff steepens when APs are more constrained. Finally, we find that post-crisis regulation intended to stabilize banks have contributed to AP constraints and reduced the liquidity provision and index-tracking capacity of ETFs.

Economic Policy Uncertainty and Hedge Fund Returns
Liang, Bing,Wang, Songtao,Zhou, Chunyang
In this paper, we study if the risk associated with innovations in economic policy uncertainty (EPU), that is, EPU risk, is priced in the cross section of hedge fund returns. Based on decile portfolios sorted on the EPU beta, we show that EPU risk commands a significantly negative premium of -0.49% per month. Conventional risk factors cannot explain the return pattern associated with the spread in EPU betas, and our findings are robust to controls for share restrictions, exposure to other risks, and the illiquidity of assets under management and to the exclusion of financial crises. In addition, we show that 12.5% of hedge funds have EPU timing ability and that an investment strategy long in top-ranked EPU timing funds and short in bottom-ranked EPU timing funds delivers a significantly positive risk-adjusted return.

Equity Market Fragmentation and Capital Investment Efficiency
Landsman, Wayne R.,Pan, Jing,Stubben, Stephen
This study examines how equity market fragmentation affects firms’ capital investment decisions. Recent empirical research finds that market fragmentation improves market quality. We examine whether this increase in market quality translates into greater revelatory price efficiency, where prices reveal with greater precision information to managers and/or creditors about firms’ investment opportunities. Findings reveal that the association between capital investment and investment opportunities is increasing in market fragmentation. Additional findings reveal that (a) the effects of market fragmentation on capital investment increase with financing constraints and (b) market fragmentation is associated with a higher sensitivity of new loans to investment opportunities, suggesting that the effects of market fragmentation work primarily by reducing information asymmetry between creditors and borrowing firms. We find evidence that market fragmentation also provides information to managers about the firm’s investment opportunities; the effects of market fragmentation on capital investment decrease with the extent to which managers are informed. Inferences based on difference-in-differences and an instrumental variable test are consistent with those based on our primary findings.

Extreme-Strike Comparisons and Structural Bounds for SPX and VIX Options
Andrew Papanicolaou

This article explores the relationship between the SPX and VIX options markets. High-strike VIX call options are used to hedge tail risk in the SPX, which means that SPX options are a reflection of the extreme-strike asymptotics of VIX options, and vice versa. This relationship can be quantified using moment formulas in a model-free way. Comparisons are made between VIX and SPX implied volatilities along with various examples of stochastic volatility models.

Factor Forestry: Pruning using an Economic Chainsaw
Abhyankar, Abhay,Wu, Yudi
Hundreds of anomalies, factors, or characteristic portfolios have been discovered whose risk-return spread is not explained by benchmark empirical factor models. Each of these is a potential candidate as a factor in such models. Efforts to narrow down this plethora of candidates to a parsimonious set has mainly relied on econometric and statistical tools. Standard textbooks, however, emphasize that factors in models proxy for the marginal utility of aggregate consumption growth. Imposing the economic restrictions that this link implies, we find that only 10-20 per cent of this forest of factors impound news about future consumption growth, the low-frequency risk of consumption growth or its extreme tails i.e. bad times. Interestingly, new factors used in models that perform better than the benchmark models do better in passing economically motivated hurdles. Our results imply that imposing theoretical restrictions, on this forest of potential factors can impose discipline, in the search for an ex-post MV efficient portfolios. In addition, applying an economic chainsaw to yet to be discovered anomalies could curb the growth of this forest.

Financial Returns to Collecting Rare Political Economy Books
Ursprung, Heinrich W.
Rare books of political economy are eminently collectable. Using historical prices, I employ hedonic regressions to estimate financial returns to collecting the works of ten eminent political economists and develop a price index for this corpus of collectables. For the observation period 1975-2019, I find that in those 45 years investing in rare political economy books yielded an average annual real rate of return of 2.8%, which is well in line with the returns to collecting rare books of classical literature. Compared with other collectibles such as fine art, investing in rare books turns out to be financially more profitable.

Foreign Exchange Dynamics and Reserve Accumulation under Capital Inflows
Hui, Cho-Hoi,Lo, Chi-Fai,Liu, Chi-Hei
When a currency’s appreciation expectation cannot be offset by lower interest rates which have fallen to the zero lower bound, the monetary authority needs to intervene to prevent currency appreciation due to capital inflows and resulting in foreign reserve accumulation. Based on a standard flexible-price monetary framework, this paper extends a target-zone model in which the intervention policy is incorporated by specifying the asymmetric mean-reverting fundamental dynamics with the smooth-pasting condition at a moving boundary. The solution of the model shows that the exchange rate dynamics is more sensitive to the change in the fundamental when the domestic interest rate is constrained at zero, suggesting more intensive interventions are required to counteract currency appreciation pressure. The empirical results using market data during January 2015 â€" February 2020 demonstrate that the model can describe the dynamics of the Swiss franc exchange rate following the mean-reverting square-root process. The accumulation of foreign reserves through interventions is negatively co-integrated with the exchange rate volatility and the value of the mean level of the Swiss franc exchange rate in the dynamics, to some extent indicating a reasonably high degree of effectiveness of the Swiss National Bank’s interventions.

Foreign Ownership, Appointment of Independent Directors, and Firm Value: Evidence from Japanese Firms
Ahmed, Anwer S.,Iwasaki, Takuya
We investigate the effects of foreign ownership on a key monitoring mechanism, the appointment of independent directors, for a sample of Japanese firms after the Tokyo Stock Exchange passed rules requiring appointment of at least one independent director or an independent statutory auditor. We find that foreign ownership is significantly positively associated with the appointment of independent directors and firm value respectively. We also find, using path analysis, that foreign ownership affects firm value via the appointment of independent directors. In robustness tests, we also examine whether foreign ownership affects a monitoring outcome (earnings management). We find that foreign ownership is significantly negatively related to benchmark beating using both accrual and real earnings management. Overall, our evidence suggests that despite their smaller shareholdings, foreign investors enhance firm value through improving monitoring of managers.

Global Daily CO$_2$ emissions for the year 2020
Zhu Liu,Zhu Deng,Philippe Ciais,Jianguang Tan,Biqing Zhu,Steven J. Davis,Robbie Andrew,Olivier Boucher,Simon Ben Arous,Pep Canadel,Xinyu Dou,Pierre Friedlingstein,Pierre Gentine,Rui Guo,Chaopeng Hong,Robert B. Jackson,Daniel M. Kammen,Piyu Ke,Corinne Le Quere,Crippa Monica,Greet Janssens-Maenhout,Glen Peters,Katsumasa Tanaka,Yilong Wang,Bo Zheng,Haiwang Zhong,Taochun Sun,Hans Joachim Schellnhuber

The diurnal cycle CO$_2$ emissions from fossil fuel combustion and cement production reflect seasonality, weather conditions, working days, and more recently the impact of the COVID-19 pandemic. Here, for the first time we provide a daily CO$_2$ emission dataset for the whole year of 2020 calculated from inventory and near-real-time activity data (called Carbon Monitor project: It was previously suggested from preliminary estimates that did not cover the entire year of 2020 that the pandemics may have caused more than 8% annual decline of global CO$_2$ emissions. Here we show from detailed estimates of the full year data that the global reduction was only 5.4% (-1,901 MtCO$_2$, ). This decrease is 5 times larger than the annual emission drop at the peak of the 2008 Global Financial Crisis. However, global CO$_2$ emissions gradually recovered towards 2019 levels from late April with global partial re-opening. More importantly, global CO$_2$ emissions even increased slightly by +0.9% in December 2020 compared with 2019, indicating the trends of rebound of global emissions. Later waves of COVID-19 infections in late 2020 and corresponding lockdowns have caused further CO$_2$ emissions reductions particularly in western countries, but to a much smaller extent than the declines in the first wave. That even substantial world-wide lockdowns of activity led to a one-time decline in global CO$_2$ emissions of only 5.4% in one year highlights the significant challenges for climate change mitigation that we face in the post-COVID era. These declines are significant, but will be quickly overtaken with new emissions unless the COVID-19 crisis is utilized as a break-point with our fossil-fuel trajectory, notably through policies that make the COVID-19 recovery an opportunity to green national energy and development plans.

Government Activism in Bankruptcy
Ellias, Jared A.,Triantis, George G.
It is widely recognized that bankruptcy law can stymie regulatory enforcement and present challenges for governments when regulated businesses file for Chapter 11. It is less-widely understood that bankruptcy law can present governments with opportunities to advance policy goals if they are willing to adopt tactics traditionally associated with activist investors, a strategy we call “government bankruptcy activism.” The bankruptcy filings by Chrysler and General Motors in 2009 are a famous example: the Federal government used activist tactics to help both auto manufacturers resolve their financial distress while promoting the policy objectives of protecting union workers and addressing climate change. A decade later, the government of California used its bargaining power in the Pacific Gas & Electric Company’s Chapter 11 case to protect climate policies and the victims of wildfires. These examples illustrate that, by tapping into the bankruptcy system, governments can gain access to the exceptional powers that a debtor enjoys under bankruptcy law, which can complement the traditional tools of appropriations and regulation to facilitate and accelerate policy outcomes. This strategy is especially useful in times of urgency and policy paralysis, when government bankruptcy activism can provide a pathway past veto players in the political system. However, making policy through the bankruptcy system presents potential downsides as well, as it may also allow governments to evade democratic accountability and obscure the real losses that stakeholders are forced to absorb.  

High-Frequency Trading and its Impact on Market Liquidity: A Review of Literature
Ersan, Oguz,Dalgic, Nihan,Ekinci, Cumhur,Bodur, Mehmet
High-frequency trading (HFT) has been dominating the activity in developed financial markets in the last two decades. Despite its recent formation, the literature on the impacts of HFT on financial markets and participants is broad. However, there are ongoing debates and unanswered questions within many subtopics. We survey through the research towards HFT effects on liquidity in an attempt to explain the coexistence of evidence regarding both the positive and the negative impacts of HFT. We name two main factors leading to mixed results. Former concerns the negative market conditions such as intraday shocks, through which HFT trading patterns may sharply change. Latter regards the certain characteristics of HFT liquidity provision with the potential to present externalities for the market.

Hunt-for-Duration in the Corporate Bond Market
Yu, Yifan
This paper examines the duration hedging behavior in the corporate bond market by studying the investment decisions of life insurance companies, the largest institutional investor in this market. Using security-level data on insurers' bond holdings, I find that life insurers are tilting their corporate bond portfolios towards bonds with higher duration as the interest rates decrease to historical lows since the 2008 financial crisis. This hunt-for-duration behavior is due to life insurers' interest rate risk hedging to ensure better duration matching between their assets and liabilities. I further show that hunt-for-duration by life insurers can drive overpricing of corporate bonds when a negative monetary policy surprise hits.

Indirect Costs of Government Aid and Intermediary Supply Effects: Lessons from the Paycheck Protection Program
Working Paper Series, FDIC,Puri, Manju,Balyuk, Tetyana,Prabhala, Nagpurnanand
The $669 billion Paycheck Protection Program (PPP) provides highly subsidizedfinancing to small businesses. The PPP is a positive shock in financing supply tothe small, highly constrained publicly listed firms in our sample and has averagepositive treatment effects. Yet, uptake is not universal. In fact, several firmsreturn PPP funds before use, and curiously, experience positive valuation effectswhen they do so. These firms desire and the markets value the release fromgovernment oversight even if it means giving up cheap funding. The PPP is alsoa demand shock to the banks making PPP loans. Intermediary supply effectsshape PPP delivery. Larger borrowers enjoy earlier PPP access, an effect that ismore pronounced in big banks. The results have implications for policy design,the costs of being public, and bank-firm relationships.

Manufacturing Risk-Free Government Debt
Jiang, Zhengyang,Lustig, Hanno,Van Nieuwerburgh, Stijn,Xiaolan, Mindy Z.
Governments face a trade-off between insuring bondholders and taxpayers. If the government fully insures bondholders by manufacturing risk-free zero-beta debt, then it cannot also insure taxpayers against permanent macroeconomic shocks over long horizons. Instead, taxpayers will pay more in taxes in bad times. Conversely, if the government fully insures taxpayers against adverse macro shocks, then the debt becomes risky, at least as risky as unlevered equity claim. As the world’s safe asset supplier, the U.S. appears to have escaped this trade-off thus far, whereas the U.K. has not.

Measuring Vacancies: Firm-level Evidence from Two Measures
Niels-Jakob Harbo Hansen,Hans Henrik Sievertsen

Using firm-level survey- and register-data for both Sweden and Denmark we show systematic mis-measurement in both vacancy measures. While the register-based measure on the aggregate constitutes a quarter of the survey-based measure, the latter is not a super-set of the former. To obtain the full set of unique vacancies in these two databases, the number of survey vacancies should be multiplied by approximately 1.2. Importantly, this adjustment factor varies over time and across firm characteristics. Our findings have implications for both the search-matching literature and policy analysis based on vacancy measures: Observed changes in vacancies can be an outcome of changes in mis-measurement, and are not necessarily changes in the actual number of vacancies.

Minority Investor Protection Mechanisms and Agency Costs: An Empirical Study Using the World Bank-Developed Approach
N. Pham, Hoang,Nguyen, Cong Minh
This study examines the impacts of minority investor protection mechanisms on agency costs in Vietnam. All relevant indicators of minority investor protection developed by the World Bank are employed with a panel data sample of 135 Vietnamese listed firms during the period from 2014-2018. It is found that the following mechanisms are effective in mitigating agency costs and hence agency problems at the firm level: i) extent of disclosure; ii) extent of director liability; iii) ease of shareholder suit; iv) shareholders’ rights in major corporate decisions; and v) corporate transparency. Interestingly, it is found that the board independence and controlling government shareholder do not play significant roles in addressing agency problems. To the best of the authors’ knowledge, this is one of the first attempts at testing for the impact of minority investor protection mechanisms developed by the World Bank on agency costs at the firm level. This study also provides policy implications for selecting effective mechanisms to mitigate agency conflicts between controlling shareholders and minority investors in order to promote the financial performance of the firm in an Asian emerging market.

Multi-level Adaptation of Distributed Decision-Making Agents in Complex Task Environments
Darío Blanco-Fernández,Stephan Leitner,Alexandra Rausch

To solve complex tasks, individuals often autonomously organize in teams. Examples of complex tasks include disaster relief rescue operations or project development in consulting. The teams that work on such tasks are adaptive at multiple levels: First, by autonomously choosing the individuals that jointly perform a specific task, the team itself adapts to the complex task at hand, whereby the composition of teams might change over time. We refer to this process as self-organization. Second, the members of a team adapt to the complex task environment by learning. There is, however, a lack of extensive research on multi-level adaptation processes that consider self-organization and individual learning as simultaneous processes in the field of management science. We introduce an agent-based model based on the NK-framework to study the effects of simultaneous multi-level adaptation on a team's performance. We implement the multi-level adaptation process by a second-price auction mechanism for self-organization at the team level. Adaptation at the individual level follows an autonomous learning mechanism. Our preliminary results suggest that, depending on the task's complexity, different configurations of individual and collective adaptation can be associated with higher overall task performance. Low complex tasks favour high individual and collective adaptation, while moderate individual and collective adaptation is associated with better performance in case of moderately complex tasks. For highly complex tasks, the results suggest that collective adaptation is harmful to performance.

Müasir şəraitdə İslam maliyyə sisteminin spesifik xüsusiyyətləri (Specific Features of the Islamic Financial System in the Modern Condition)
Garibli, Emin,Azimzadeh, Aslan,Huseynli, Jabbar
Azerbaijani abstract: Tədqiqatın əsas məqsədi müasir şəraitdə İslam Maliyyə Sisteminin spesifik xüsusiyyətlərinin öyrənilməsinə yönəlmişdir. Tədqiqat işi müqayisəli təhlil və məntiqi ümumiləşdirmə kimi tədqiqat üsulları əsasında yerinə yetirilmişdir. Tədqiqatda İslam Maliyyə Sisteminin fəaliyyət prinsipləri sistemləşdirilərək kompleks araşdırılmışdır. Həmçinin tədqiqat işində İslam Maliyyə Sisteminin müasir dövrdəki və qlobal maliyyə böhranındakı vəziyyəti analiz edilmişdir. Tədqiqat nəticəsində İslam Maliyyə Sisteminin spesifik xüsusiyyətləri təhlil edilmiş, həmçinin bu sistemdən istifadənin yüksək perspektivli olması müəyyən olunaraq Azərbaycanda bu sistemin tətbiqinin verə biləcəyi səmərələr qeyd olunmuşdur. Tədqiqatın məhdudiyyətləri daha geniş praktik informasiya tələb etməsidir. Tədqiqatın praktiki əhəmiyyəti İslam Maliyyə Sisteminin spesifik xüsusiyyətlərindən yararlanaraq, digər ölkələrin maliyyə sistemlərinin təkmilləşdirilməsi və bunun nəticəsində iqtisadi böhranlara qarşı optimal adaptiv maliyyə mexanizminin yaradılmasıdır.English abstract: The main objective of the research is to study the specific features of İslamic Financial System in the modern condition. The research was carried out on the basis of research methods such as comparative analysis and logical summarization. In study principles of functioning of the Islamic Financial System was systemized with the complex research. The study also analyzes the state of the Islamic Financial System in the modern period and the global financial crisis. In the result of the investigation the Islamic Financial System and its specific features were analyzed, at the same time it were identified prospects for using this system and potential benefits from the introduction of this system in Azerbaijan. Limitations of the study: to require more extensive practical information. The practical significance of the research study is to improve the financial systems of other countries, using the specific features of the Islamic Financial System, and, as a result, create the optimal adaptive financial mechanism for the economic crisis.

Point and Interval Forecasts of Death Rates Using Neural Networks
Schnürch, Simon,Korn, Ralf
The Lee-Carter model has become a benchmark in stochastic mortality modeling. However, its forecasting performance can be significantly improved upon by modern machine learning techniques. We propose a convolutional neural network architecture for mortality rate forecasting, empirically compare this model as well as other neural network models to the Lee-Carter model and find that lower forecast errors are achievable for many countries in the Human Mortality Database. We provide details on the errors, forecasts and global behavior of our model to make it more understandable and, thus, more trustworthy. As neural networks by default only yield point estimates, previous works applying them to mortality modeling have not investigated prediction uncertainty. We address this gap in the literature by implementing a bootstrapping-based technique and demonstrate that it yields highly reliable prediction intervals for our neural network model.

Quantifying Soft Information, Mortgage Market Efficiency & Asset Pricing Implications
Bandyopadhyay, Arka
In this paper, I provide a novel framework for machine learning models to ingest quantified soft information during the life of a loan, using cutting-edge natural language processing techniques on salient unstructured text, beyond positive/negative sentiments, from servicer call transcripts which provides efficiency and alleviates the information asymmetry between the lender (and/or issuer) and the borrower. Proprietary servicer comments are hardly accessible and offer the soft information for real-time delinquency status of the mortgages. I investigate whether the special servicer invoked by the investor can utilize the valuable comments from the master servicer. The time-varying soft information about the borrower's financial condition, health of the loan and the property condition from these master servicer comments renders the predictive power and has asset pricing implications. Given this valuable information, the special servicer may choose to use this information, as I anecdotally see with several private equity investors. The well-known unresolved conflict of interest between the master and special servicers (see Mayer and Gan (2006)) can be resolved and this can have a significant reduction of moral hazard in the residential real estate market, thereby increasing efficiency and transparency.

Renewable Energy Zones in Australia’s National Electricity Market
Simshauser, Paul
Australia’s National Electricity Market operates in one of the world’s longest and stringiest transmission networks. The 2016-2020 investment supercycle, in which 13,000 MW of renewables were committed, is slowly revealing the limits of network hosting capacity for renewable plant. In this article, side-effects arising from the supercycle are analysed. The majority sources of renewable investment failure relate to deteriorating system strength, viz. associated connection lags, remediation and curtailment costs. Although a multi-zonal market, the NEMs locational investment signals remain visibly strong. A change to nodal arrangements may refine dispatch efficiency but the bigger policy problem is rapidly diminishing network hosting capacity for new renewables, imperfect regulation and regulatory lag associated with augmentation. Markets participants seek to move faster than regulatory frameworks allow. Renewable Energy Zones (REZ) are examined through both i). a consumer-funded regulatory model and ii). a renewable generator-funded market model. A ‘super-sized concessional mezzanine’ facility is presented as a critical element of REZ capital funding. It forms the means by which to optimise market-based REZ transmission augmentation and moderate sponsor risks of transient underutilisation.

Skewness and Kurtosis Adjusted Black-Scholes Model: A Note on Hedging Performance
Vähämaa, Sami
This article investigates the delta hedging performance of the skewness and kurtosis adjusted Black-Scholes model of Corrado and Su (1996) and Brown and Robinson (2002). The empirical tests in the FTSE 100 index option market show that the more sophisticated skewness and kurtosis adjusted model performs worse than the simplistic Black-Scholes model in terms of delta hedging. The hedging errors produced by the skewness and kurtosis adjusted model are consistently larger than the Black-Scholes hedging errors, regardless of the moneyness and maturity of the options and the length of the hedging horizon.

Sudden Stop with Local Currency Debt
Liu, Siming,Ma, Chang,Shen, Hewei
Over the past two decades, emerging market economies have improved their external liability structures by increasing the share of debt denominated in local currencies, while foreign currency debt is considered a major source of financial instability. This paper embeds the debt denomination choice in a sudden stop model and explore its implications for the optimal capital control policy. As its payoff depends on the real exchange rate, the local currency debt provides better risk-sharing for emerging market economies but introduces additional distortions. Compared to the competitive equilibrium, a discretionary planner has incentives to deflate the debt burden denominated in local currencies, which increases its issuance cost ex ante. In contrast, a social planner with commitment would promise a higher future payment to obtain a more favorable local currency bond price. Quantitatively, the optimal policy under commitment encourages more borrowing in local currencies, mitigates the severity of crises, and improves welfare relative to the laissez-faire.

Summary of the Paper Entitled ‘The Mean Squared Prediction Error Paradox’
Pincheira, Pablo M.,Hardy, Nicolas
This is a summary of the paper entitled: “The Mean Squared Prediction Error Paradox”. In that paper, we show that traditional comparisons of Mean Squared Prediction Error (MSPE) between two competing forecasts may be highly controversial. This is so because when some specific conditions of efficiency are not met, the forecast displaying the lowest MSPE will also display the lowest correlation with the target variable. Given that violations of efficiency are usual in the forecasting literature, this opposite behavior in terms of accuracy and correlation with the target variable may be a fairly common empirical finding that we label here as "the MSPE Paradox." We characterize "Paradox zones" in terms of differences in correlation with the target variable and conduct some simple simulations to show that these zones may be non-empty sets. Finally, we illustrate the relevance of the Paradox with two empirical applications.

Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate
Pincheira, Pablo M.,Jarsun, Nabil
This draft is a summary of the paper entitled: Forecasting Fuel Prices with the Chilean Exchange Rate. In that paper we show that the Chilean exchange rate has the ability to predict the returns of oil prices and of three additional oil-related products: gasoline, propane and heating oil. The theoretical underpinnings of our empirical findings rely on the present-value theory for exchange rate determination and on the strong co-movement displayed by some commodity prices. The Chilean economy is heavily influenced by one particular commodity: copper, which represents nearly 50% of total national exports and attracts a similar share in terms of Foreign Direct Investment. As a consequence, the floating Chilean exchange rate is importantly affected by fluctuations in the copper price. As oil-related products display an important co-movement with base metal prices, it is reasonable to expect evidence of Granger causality from the Chilean peso to these oil-related products. We find substantial evidence of predictability both in-sample and out-of-sample. Our paper is part of a growing literature that in the recent years has explored the linkages between commodity prices and commodity currencies.

Hirsa, Ali,Hadji Misheva, Branka,Osterrieder, Joerg,Cao, Wenxin,Fu, Yiwen,Sun, Hanze,Wong, Kin Wai
The CBOE Volatility Index, known by its ticker symbol VIX, is a popular measure of the market’s expected volatility on the S&P 500 Index, calculated and published by the Chicago Board Options Exchange (CBOE). It is also often referred to as the fear index or the fear gauge. The current VIX index value quotes the expected annualized change in the S&P 500 index over the following 30 days, based on options-based theory and current options-market data. Despite its theoretical foundation in option price theory, CBOE’s Volatility Index is prone to inadvertent and deliberate errors because it is weighted average of out-of-the-money calls and puts which could be illiquid. Many claims of market manipulation have been brought up against VIX in recent years. This paper discusses several approaches to replicate the VIX index as well as VIX futures by using a subset of relevant options as well as neural networks that are trained to automatically learn the underlying formula. Using subset selection approaches on top of the original CBOE methodology, as well as building machine learning and neural network models including Random Forests, Support Vector Machines, feed-forward neural networks, and long short-term memory (LSTM) models, we will show that a small number of options is sufficient to replicate the VIX index. Once we are able to actually replicate the VIX using a small number of S&P options we will be able to exploit potential arbitrage opportunities between the VIX index and its underlying derivatives. The results are supposed to help investors to better understand the options market, and more importantly, to give guidance to the US regulators and CBOE that have been investigating those manipulation claims for several years.

The Price Impact and Timing of Actual Share Repurchases in Norway
Rehman, Obaidur
Little is known about the price impact and timing of actual share repurchases. Data unavailability has hindered research in most countries, including the United States. Using unique data on actual share repurchase transactions from Norway, we test for the price impact and timing of daily open market repurchases. We find evidence that share repurchases typically follow after a negative drift in the stock price, and the average three-day abnormal return around the announcement is 0.54%. Moreover, the initial market reaction is greater for repurchases that are pursued by small firms and for firms that experience a negative drift in the stock price prior to the transaction. The evidence presented is seemingly indicative of managers’ intent to signal undervaluation through repurchase transactions. However, we do not find any significant long-term abnormal returns for repurchasing firms. This result suggests that on average, managers do not time the market based on informational advantage.

The Support and Resistance Line Method: An Analysis via Optimal Stopping
Vicky Henderson,Saul Jacka,Ruiqi Liu

We study a mathematical model capturing the support/resistance line method (a technique in technical analysis) where the underlying stock price transitions between two states of nature in a path-dependent manner. For optimal stopping problems with respect to a general class of reward functions and dynamics, using probabilistic methods, we show that the value function is $C^1$ and solves a general free boundary problem. Moreover, for a wide range of utilities, we prove that the best time to buy and sell the stock is obtained by solving free boundary problems corresponding to two linked optimal stopping problems. We use this to numerically compute optimal trading strategies for several types of dynamics and varying degrees of relative risk aversion. We then compare the strategies with the standard trading rule to investigate the viability of this form of technical analysis.

Towards a Principled Approach for Bailouts of COVID-Distressed Critical/Systemic Firms
Eidenmueller, Horst,Paz Valbuena, Javier
In this essay, we propose a principled approach for government bailouts of critical/systemic firms who find themselves in COVID-19-induced financial distress. We also demonstrate why bankruptcy is the wrong tool to address the problems of these types of firms. The current pandemic threatens lives and livelihoods across the world. A key difference compared to previous market shocks is that lockdowns and related measures have, in certain instances, made it impossible for businesses to conduct their operations. This has resulted in a very specific type of distress, one that bankruptcy is not in the best position to address effectively. If there are no revenues, the design of bankruptcy laws makes them an inadequate tool â€" and the sheer volume of companies going through the process may put severe stress on the system. The difficulties that the vast majority of companies are encountering may be better solved using different tools: bailouts, bail-ins or a combination thereof, deployed by the government in wide-ranging statutory schemes. However, these schemes may not adequately address the issues of all companies; and the preservation of some of them â€" those that we refer to as critical/systemic â€" may be of such significant value to society that more intense assistance from the government is justified. We engage with the characteristics of firms that should be considered critical/systemic and the principles that should guide ad hoc rescues of those companies by the government. Firms are critical/systemic if their failure imposes significant negative externalities on the economy (or, conversely, their preservation generates significant positive externalities) or if they provide the public with an “infrastructure” not otherwise provided by the private sector. If firms are critical/systemic, the government should have the ability to bail them out, going beyond applicable statutory schemes and ensuring that the relevant externalities are considered when deciding whether to keep these companies as going concerns. Bankruptcy is a private process. It is not designed to vindicate such public considerations. Government bailouts, however, should be governed by principles, as any government intervention in the economy, and its associated efficiency and distributional effects must be considered with care. The guiding principles that we propose and elaborate on are (i) proportionality, (ii) efficiency, (iii) equity and (iv) transparency. The application of these principles should ensure that, if the government takes ownership of a private firm through an ad hoc bailout, this is a tool of last resort, and not more than temporary â€" and that the pre-distress investors properly contribute to the necessary measures.

Trading Signals In VIX Futures
M. Avellaneda,T. N. Li,A. Papanicolaou,G. Wang

We propose a new approach for trading VIX futures. We assume that the term structure of VIX futures follows a Markov model. The trading strategy selects a multi-tenor position by maximizing the expected utility for a day-ahead horizon given the current shape and level of the VIX futures term structure. Computationally, we model the functional dependence between the VIX futures curves, the VIX futures positions, and the expected utility as a deep neural network with five hidden layers. Out-of-sample backtests of the VIX futures trading strategy suggest that this approach gives rise to reasonable portfolio performance, and to positions in which the investor can be either long or short VIX futures contracts depending on the market environment.