Research articles for the 2020-04-21

Assessment of Criteria for Performance Excellence (KPKU) and Firm Performance: Evidence from Indonesia
Ratri, Melinda Cahyaning,Harymawan, Iman,Nowland, John
This study aims to examine whether the assessment of Criteria for Performance Excellence (KPKU) is related to the firm performance of States-Owned Enterprise (SOE) in Indonesia. This study uses 82 firms-year observations from 19 State-Owned Enterprise listed on the Indonesia Stock Exchange (IDX) for the period 2009 to 2018. This study found that KPKU assessment was positively related to firm performance. This shows that KPKU assessment can be a signal that the company has good performance. The study also found that the positive relationship between KPKU assessment and company performance is stronger in companies audited by Big 4 and in big-sized companies. This study is the first research that discusses the relationship between KPKU assessment and firm performance. This study may be useful for practitioners and academics that are interested in the subject of SOE performance assessment. The results suggest to conduct a regular KPKU assessment because it can be useful to provide a positive signal for shareholders and potential investors.

CEO Emotions and Underpricing in Initial Coin Offerings
Momtaz, Paul P.
CEO emotions are difficult to measure and hence empirically understudied. However, using artificial emotional intelligence, positive and negative affects can be identified from facial muscle contraction-relaxation patterns obtained from public CEO photos during initial coin offerings (ICOs), i.e., blockchain-based issuances of cryptocurrency tokens to raise growth capital. The results suggest that CEO affects impact firm valuation in two ways. First, CEOs’ own firm valuations conform more to those of industry peers if negative affects are pronounced (conformity mechanism). Second, investors use CEO affects as signals about firm value and discount when negative affects are salient (signaling mechanism). Negative affects can reduce firm value by up to 15%. Both mechanisms are stronger in the presence of asymmetric information and robust to tests of endogeneity.

COVID-19 and Unequal Social Distancing across Demographic Groups
Yilmazkuday, Hakan
This paper analyzes whether social distancing experienced by alternative demographic groups within the U.S. has been different amid COVID-19. The formal investigation is achieved by using daily state-level data from the U.S. covering information on the demographic categories of income, education and race/ethnicity. The results show that the social distancing experienced by the highest-income group after the declaration of National Emergency has been about 33% more than the first and the second income quartiles, and 25% more than the third income quartile. The social distancing experienced by the highest-education group after the declaration of National Emergency has been about 53% more than the first education quartile, 46% more than the second education quartile, and 34% more than the third education quartile. The social distancing experienced by the Asian race after the declaration of National Emergency has been about 21% more than Blacks, 21% more than Hispanics, and 15% more than whites.

COVID-19: Are Stocks on Sale?
DeGennaro, Ramon P.
What should investors do after a market crash? Whether stocks are likely to recover depends not on how much they declined, but rather, on why they declined. Perhaps surprisingly, it also depends on what you mean by “recover.”

Capital Structure Determinants, Dynamics and Speed of Adjustment Towards Target Leverage: A Systematic Literature Review of Empirical and Theoretical Disciplines
William, Ramy
This article aims at defining the main gaps and presenting the results of literature about the determinants of capital structure, capital structure dynamics and the determinants of the speed of adjustment towards target leverage. Beside the effects of firm-specific determinants, the article covers the major macro-economic events affecting capital structure decisions like the global financial crisis as well as political uncertainty. The article also shed the light on the differences between banks and non-financial institutions in terms of rules and regulations that shape the dynamic behavior of utilizing the different sources of finance.As a conceptual article, the author employed a reflective stance by counting solely on secondary literature. According to Dzansi and Hoeyi (2013), this stance is consistent with interpretivist reasoning in the social sciences.Analysis of empirical studies revealed that the capital structure decision is influenced by profitability, size of the firm, asset tangibility, non-debt tax shield, and growth. Too, results from different markets indicated that firms follow the implications of the pecking order theory in a sense that; firms adjust capital structure towards a target leverage ratio. The speed of adjustment is affected by firm characteristics (like size and growth) as well as the distance between current and target leverage ratios.This article presents opportunities for future research in capital structure topic based on the presented literature gaps.To the best of author’s knowledge, this is the first article to address considerable number of papers in a large period of time for different aspects of capital structure and offer recommendations for future research based on the identified gaps.

Characteristics of Politically Connected Firms in Indonesia
Harymawan, Iman,Agustia, Dian,Agung, Ardyan Kusuma
This study investigates the types and characteristics of firms with politically connected directors in the boards of the company. The study uses data from all firms listed in Indonesia Stock Exchange spanning from 2004 to 2006. This study employs univariate analyses to address the research questions. The finding shows that firms with political connections are prevalence in chemical, infrastructure, investment, and miscellaneous industry. Furthermore, firm size is the only variable which significantly affects the probability of being politically connected firms. Specifically, larger firms are more likely to be politically connected. This study implies that the size of the firms is an important determinant in establishing political connections in Indonesia.

Climate Change as a Systemic Risk â€" are Macroprudential Authorities up to the Task?
Gruenewald, Seraina N.
There is growing acknowledgement among policymakers that climate change may give rise to potentially catastrophic financial risk and impact financial stability. This paper explores the specific features of climate-related financial risks (CRFR), drawing on a growing body of macrofinancial literature and policy work, and discusses the options macroprudential policy-makers have in the face of such risk. It finds that there are significant challenges associated with ‘greening’ macroprudential policy, both epistemological and methodological as well as behavioural, and points to potential ingredients of a ‘green’ macroprudential policy. In light of the radical uncertainty in relation to the dynamics of CRFR, the timing of policy action is of the essence. The paper, in particular, explores the merits and challenges associated with a precautionary approach to tackling the systemic effects of CRFR. Finally, it discusses the role that Central Banks can and should play in the transition to a low-carbon economy, both within the confines and in fulfilment of their price and financial stability mandates.

Clustering volatility regimes for dynamic trading strategies
Gilad Francis,Nick James,Max Menzies,Arjun Prakash

We develop a new method to find the number of volatility regimes in a non-stationary financial time series. We use change point detection to partition a time series into locally stationary segments, then estimate the distributions of each piece. The distributions are clustered into a learned number of discrete volatility regimes via an optimisation routine. Using this method, we investigate and determine a clustering structure for indices, large cap equities and exchange-traded funds. Finally, we create and validate a dynamic portfolio allocation strategy that learns the optimal match between the current distribution of a time series with its past regimes, thereby making online risk-avoidance decisions in the present.

Corporate Social Responsibility and Market Efficiency: Evidence from ESG and Misvaluation Measures
Bofinger, Yannik,Heyden, Kim J.,Rock, Björn
We study the impact of corporate sustainability on market efficiency in the US from 2004 to 2017. Our results indicate that a firm's Environmental, Social and Governance (ESG) profile significantly affects valuation: an enhancement of a firm's corporate sustainability leads to a substantially higher ratio of actual to true firm value. Analyzing the positive relation between ESG and misvaluation separately, we find that ESG expands existing overvaluation whereas it supports undervalued firms to converge towards the true value. We argue that the extension of overvaluation is driven by the trend to invest sustainable. The reduction in undervaluation, however, is attributable to increasing information availability to capital markets.

Decomposition of Optimal Dynamic Portfolio Choice with Wealth-Dependent Utilities in Incomplete Markets
Chenxu Li,Olivier Scaillet,Yiwen Shen

This paper establishes a new decomposition of optimal dynamic portfolio choice under general incomplete-market diffusion models by disentangling the fundamental impacts on optimal policy from market incompleteness and flexible wealth-dependent utilities. We derive explicit dynamics of the components for the optimal policy, and obtain an equation system for solving the shadow price of market incompleteness, which is found to be dependent on both market state and wealth level. We identify a new important hedge component for non-myopic investors to hedge the uncertainty in shadow price due to variation in wealth level. As an application, we establish and compare the decompositions of optimal policy under general models with the prevalent HARA and CRRA utilities. Under nonrandom but possibly time-varying interest rate, we solve in closed-form the HARA policy as a combination of a bond holding scheme and a corresponding CRRA strategy. Finally, we develop a simulation method to implement the decomposition of optimal policy under the general incomplete market setting, whereas existing approaches remain elusive.

Derivatives Use and its Consequences for Management Earnings Forecasts
Campbell, John L.,Cao, Sean,Chang, Hye Sun,Chiorean, Raluca
This study examines whether firms’ risk management policies (i.e., the use of derivatives to hedge firm risk) are associated with the frequency and informativeness of management earnings forecasts. We offer three main results. First, we find that management forecasts increase after firms begin using derivatives; however, the increase only occurs when managers use derivatives to reduce the volatility of earnings. This suggests that managers only increase the frequency of their forecasts when they use derivatives in a way that makes it easier to predict future performance. Second, we find these effects are larger when managers have pronounced career concerns and a lower tolerance for missing previously issued forecasts. This suggests that, when managers otherwise face high disclosure costs, they only provide forecasts when derivatives use makes it easier to predict future earnings. Finally, we find that when managers use derivatives in a way that decreases ex-ante earnings uncertainty (i.e., to hedge volatility risk), their forecasts do not alter analysts’ perceptions of future earnings. This suggests that the previously documented increase in forecast frequency does not appear to be valuable to capital market participants. However, when managers use derivatives in a way that increases ex-ante earnings uncertainty (i.e., to speculate), we find that their forecasts have high informational value to analysts. Overall, we find that derivatives use impacts managers’ disclosure choices, and that managers do not appear to increase disclosures in response to investor demand when their personal disclosure cost is high.

Doing More With Less: The Catalytic Function of IMF Lending and the Role of Program Size
Krahnke, Tobias
Financial assistance provided by the International Monetary Fund (IMF) is supposed to unlock other financing, acting as a catalyst for private capital flows. The empirical evidence of the presence of such a catalytic effect has, however, been mixed. This paper shows that a possible explanation for the rather inconclusive empirical evidence to date is the neglect of the size of an IMF program. Applying a novel identification strategy to account for endogenous selection into (large) adjustment programs, and using a comprehensive data set spanning the years 1990-2018, we show that the catalytic effect of IMF financial assistance is weakened - and potentially reversed - if the size of a program exceeds a certain level. We argue that large IMF financial assistance coupled with the IMF's preferred creditor status can lead to a crowding-out of private investors by increasing their loss in the event of default. Our findings add to the debate on the optimal size of Fund-supported programs and can also inform the broader policy discussions on the adequacy of IMF resources.

Effects of FinTech and Crowdsourced Forecasting on Firms: Evidence from Estimize
Sul, Edward
This paper examines whether and how coverage from a unique crowdsourced financial estimates platform, Estimize, affects firms. Employing a difference-in-difference design comparing firms that gain coverage from Estimize with firms that do not, I find that covered firms experience decreased information asymmetry, implying that Estimize provides useful information to the market. I also provide evidence of a visibility effect, as the breadth of institutional ownership increases following initiation of Estimize coverage. In addition, firms gaining Estimize coverage become more likely to engage in real earnings management and issue downwards quarterly earnings guidance, suggesting increased pressure effects from Estimize coverage. However, I find no monitoring effects of Estimize on firms’ financial reporting and future firm performance. Lastly, I find that firm value significantly increases upon Estimize coverage, and that the driving channels are reduction of information asymmetry and increased visibility. Furthermore, the effects of Estimize coverage on firm outcomes appear to be more pronounced when a firm has zero analyst coverage. Taken together, the evidence in this paper suggests that crowdsourced forecasting affects firms through various channels, most notably through decreasing information asymmetry, increasing visibility and pressure, but that the net effect on firm value is positive.

Estimating the Life Expectancy and Value of Statistical Life (VSL) Losses from COVID-19 Infections in the United States
Wilson, Linus
Americans aged sixty or older stand to lose 153 to 222 days of life expectancy from contracting COVID-19. Over 90 percent of the U.S. population was under stay at home orders by April 2020. These social distancing measures to slow the spread of the SARS-CoV-2 or novel coronavirus have led to over 20 million new applications for unemployment benefits. Are these economic losses justified? We find the value of statistical lives lost (VSL) from an unconstrained spread of the virus which hypothetically infected 81 percent of the population would amount to $8 to $60 trillion.

Expected Discounted Valuation With Gamma and Brownian Hitting-Time Distributions â€" Extends the Life Span and Reduces the Premium
Sipiere, Frederic
The gamma and hitting-time distributions extend the geometric and exponential distributions allowing for greater flexibility in modelling termination events and their premia. In an example, the termination premia were calculated using prior beliefs and mean-variance approximation in addition to using the gamma and hitting-time distributions; they gave risk premia that were within 4 basis points of each other because skewness, kurtosis and higher order cumulants did not contribute significantly. Since the mean and variance are the significant contributors, the gamma and hitting-time distributions can be used interchangeably if the mean and variance of one distribution correspond with those of the other distribution. If spreadsheets are used, it is not necessary to add a termination premium to the discount rate; instead, the spreadsheet cells can be truncated at some point before the expected life span of the income stream and the income discounted without the termination premium added to the discount rate.Two applications demonstrate the use of the hitting-time and gamma distributions. The hitting-time distribution was used for a problem that involved an expenditure rate, variance of expenditure and time when the funds are fully expensed. The gamma distribution was used in another application where the survivability value contributed to the life span and consequently a lower termination premium. It demonstrated that a fund with a higher rate of negative monthly performance can have a lower termination premium than another with a lower rate of negative performance due to the survivability value.The examples used in the article assumed that the termination premium was not included in the CAPM-based discount rate; if it was, the discount rate would have to be adjusted to remove the termination premium. A regression of returns on the risk-free rate and excess market returns is a possible test to determine whether the termination premium was included.

Forecasting directional movements of stock prices for intraday trading using LSTM and random forests
Pushpendu Ghosh,Ariel Neufeld,Jajati Keshari Sahoo

We employ both random forests and LSTM networks (more precisely CuDNNLSTM) as training methodologies to analyze their effectiveness in forecasting out-of-sample directional movements of constituent stocks of the S&P 500 from January 1993 till December 2018 for intraday trading. We introduce a multi-feature setting consisting not only of the returns with respect to the closing prices, but also with respect to the opening prices and intraday returns. As trading strategy, we use Krauss et al. (2017) and Fischer & Krauss (2018) as benchmark and, on each trading day, buy the 10 stocks with the highest probability and sell short the 10 stocks with the lowest probability to outperform the market in terms of intraday returns -- all with equal monetary weight. Our empirical results show that the multi-feature setting provides a daily return, prior to transaction costs, of 0.64% using LSTM networks, and 0.54% using random forests. Hence we outperform the single-feature setting in Fischer & Krauss (2018) and Krauss et al. (2017) consisting only of the daily returns with respect to the closing prices, having corresponding daily returns of 0.41% and of 0.39% with respect to LSTM and random forests, respectively.

Foreign Exchange Interventions Under a One-sided Target Zone Regime and the Swiss franc
Hertrich, Markus
From September 2011 to January 2015, the Swiss National Bank (SNB) implemented a minimum exchange rate regime (i.e. a one-sided target zone) vis-`a-vis the euro to fight deflationary pressures in the aftermath of the Great Financial Crisis. During this period of unconventional monetary policy, the SNB faced mounting criticism from the media and the public on the sizable balance sheet risks that it was incurring. Motivated by this episode, I present a structural model embedded within the target zone framework developed by Krugman (1991) that allows monetary authorities to determine ex-ante the maximum size of foreign exchange market interventions thatare expected to be necessary to implement and maintain a one-sided target zone. An empirical application of the proposed model to the aforementioned episode reveals that it is well suited to explain the actual size of these interventions and that, in January 2015, the SNB’s euro purchases might indeed have been large without the abandonment of the minimum exchange rate regime, which is consistent with the official statements of the SNB in the aftermath of that episode.

Global Challenges and Regulatory Strategies to Fintech
Gurrea-Martínez, Aurelio,Remolina, Nydia
The rise of new technologies has changed the operation, regulation and supervision of financial markets. This paper seeks to analyze the global challenges and regulatory strategies to fintech. In order to do so, it will start by analyzing the foundations and evolution of fintech. Then, it will provide an economic analysis of the different regulatory strategies adopted around the world to deal with financial innovation: from those involving bans, regulatory passivity, new legislation or permission on a case by case basis, to those consisting on a more interactive approach between innovators and regulators, such as the implementation of innovation offices, accelerators and sandboxes. It will be argued that the best regulatory approach will depend on two primary aspects. First, regulatory responses should depend on the type of fintech development, including cryptoassets, digital payments, and the use of artificial intelligence in the banking, insurance and capital markets industries. Second, one size does not fit all. Therefore, the optimal regulatory approach will depend on a variety of country-specific features, including the level of sophistication of the regulator, the development and size of their financial industry, the level of corruption existing in the country, and the goals and priorities of the financial regulator.  

How Much Income Inequality Is Too Much?
Jean-Philippe Bouchaud

We propose a highly schematic economic model in which, in some cases, wage inequalities lead to higher overall social welfare. This is due to the fact that high earners can consume low productivity, non essential products, which allows everybody to remain employed even when the productivity of essential goods is high and producing them does not require everybody to work. We derive a relation between heterogeneities in technologies and the minimum Gini coefficient required to maximize global welfare. Stronger inequalities appear to be economically unjustified. Our model may shed light on the role of non-essential goods in the economy, a topical issue when thinking about the post-Covid-19 world.

Interbank Risk Assessment â€" A Simulation Approach
Jager, Maximilian,Siemsen, Thomas,Vilsmeier, Johannes
We introduce a novel simulation-based network approach, which provides full-fledged distributions of potential interbank losses. Based on those distributions we propose measures for (i) systemic importance of single banks, (ii) vulnerability of single banks, and (iii) vulnerability of the whole sector. The framework can be used for the calibration of macro-prudential capital charges, the assessment of systemic risks in the banking sector, and for the calculation of banks' interbank loss distributions in general. Our application to German regulatory data from End-2016 shows that the German interbank network was at that time in general resilient to the default of large banks, i.e. did not exhibit substantial contagion risk. Even though up to four contagion defaults could occur due to an exogenous shock, the system-wide 99.9% VaR barely exceeds 1.5% of banks' CET 1 capital. For single institutions, however, we found indications for elevated vulnerabilities and hence the need for a close supervision.

Learning Agents in Black-Scholes Financial Markets: Consensus Dynamics and Volatility Smiles
Tushar Vaidya,Carlos Murguia,Georgios Piliouras

Black-Scholes (BS) is the standard mathematical model for option pricing in financial markets. Option prices are calculated using an analytical formula whose main inputs are strike (at which price to exercise) and volatility. The BS framework assumes that volatility remains constant across all strikes, however, in practice it varies. How do traders come to learn these parameters? We introduce natural models of learning agents, in which they update their beliefs about the true implied volatility based on the opinions of other traders. We prove convergence of these opinion dynamics using techniques from control theory and leader-follower models, thus providing a resolution between theory and market practices. We allow for two different models, one with feedback and one with an unknown leader.

Levels 2 and 3 Instruments and Stock Price Crash Risk: Evidence From European Banks
Carboni, Marika,Fiordelisi, Franco,Girardone, Claudia,Ricci, Ornella
Financial instruments in levels 2 and 3 for accounting purposes are complex and opaque products and their evaluation is problematic. The amount of these assets held by banks in Europe is exceptionally high (€3 trillion in 2019) and there is no empirical evidence as to the extent, if at all, to which investors perceive them as risky instruments. Focusing on stock price crash risk, we provide evidence of a significant difference in the relationship between these instruments and risk depending on whether they are classified as levels 2 or 3. Specifically, level 3 assets and liabilities appear positively linked to bank risk, while there is no similar evidence for level 2 instruments. Our results are robust to various risk measures, including value-at-risk and expected shortfall. A key implication that emerges from this study is that stability requires more defined boundaries between level 2 and level 3 financial instruments and a reduction of the opportunities for managerial discretion.

Long-run risk sensitive impulse control
Damian Jelito,Marcin Pitera,Łukasz Stettner

In this paper we consider long-run risk sensitive average cost impulse control applied to a continuous-time Feller-Markov process. Using the probabilistic approach, we show how to get a solution to a suitable continuous-time Bellman equation and link it with the impulse control problem. The optimal strategy for the underlying problem is constructed as a limit of dyadic impulse strategies by exploiting regularity properties of the linked risk sensitive optimal stopping value functions. In particular, this shows that the discretized setting could be used to approximate near optimal strategies for the underlying continuous time control problem, which facilitates the usage of the standard approximation tools. For completeness, we present examples of processes that could be embedded into our framework.

Management Connection and Firm Performance: Evidence from the Global Financial Crisis
Pham, Man
This chapter revisits the relationship between the connection CEOs develop with other top executives through appointment decisions and firm performance where the 2008-2009 financial crisis acts as a negative exogenous shock to internal trust. Contrary to the conventional wisdom that less CEO-independent management team harms firm performance, I find novel evidence of a positive association between management connection and crisis-period stock returns using a difference-in-differences design. This baseline finding is robust to various identification strategies with alternative measures of management connection, alternative samples, and placebo tests. Further analysis reveals that the relationship is more pronounced in firms that face more information uncertainty or have more complex business structure. The evidence suggests that management connection in fostering mutual trust between CEOs and subordinate executives helps facilitate effective collaboration and increases firm performance amid the crisis of trust.

Mortality and Healthcare: a Stochastic Control Analysis under Epstein-Zin Preferences
Joshua Aurand,Yu-Jui Huang

This paper studies optimal consumption, investment, and healthcare spending under Epstein-Zin preferences. Given consumption and healthcare spending plans, Epstein-Zin utilities are defined over an agent's random lifetime, partially controllable by the agent as healthcare reduces mortality growth. To the best of our knowledge, this is the first time Epstein-Zin utilities are formulated on a controllable random horizon, via an infinite-horizon backward stochastic differential equation with superlinear growth. A new comparison result is established for the uniqueness of associated utility value processes. In a Black-Scholes market, the stochastic control problem is solved through the related Hamilton-Jacobi-Bellman (HJB) equation. The verification argument features a delicate containment of the growth of the controlled morality process, which is unique to our framework, relying on a combination of probabilistic arguments and analysis of the HJB equation. In contrast to prior work under time-separable utilities, Epstein-Zin preferences largely facilitate calibration. In four countries we examined, the model-generated mortality closely approximates actual mortality data; moreover, the calibrated efficacy of healthcare is in broad agreement with empirical studies on healthcare across countries.

On Capital Allocation under Information Constraints
Christoph J. Börner,Ingo Hoffmann,Fabian Poetter,Tim Schmitz

Attempts to allocate capital across a selection of different investments are often hampered by the fact that investors' decisions are made under limited information (no historical return data) and during an extremely limited timeframe. Nevertheless, in some cases, rational investors with a certain level of experience are able to ordinally rank investment alternatives through relative assessments of the probabilities that investments will be successful. However, to apply traditional portfolio optimization models, analysts must use historical (or simulated/expected) return data as the basis for their calculations. This paper develops an alternative portfolio optimization framework that is able to handle this kind of information (given by an ordinal ranking of investment alternatives) and to calculate an optimal capital allocation based on a Cobb-Douglas function, which we call the Sorted Weighted Portfolio (SWP). Considering risk-neutral investors, we show that the results of this portfolio optimization model usually outperform the output generated by the (intuitive) Equally Weighted Portfolio (EWP) of different investment alternatives, which is the result of optimization when one is unable to incorporate additional data (the ordinal ranking of the alternatives). To further extend this work, we show that our model can also address risk-averse investors to capture correlation effects.

Once índices bursátiles 2007- 15 abril 2020 y desempleo en 30 países 2000-2020 (Eleven Stock Market Indices 2007- April 15, 2020 and Unemployment in 30 Countries 2000-2020)
Fernandez, Pablo,de Apellániz, Eduardo
Spanish Abstract: Se compara la evolución de once índices bursátiles en el periodo 2007- 15 abril 2020 y se comparan los descensos de la “crisis del coronavirus” y los de la crisis de 2007… (financiera en algunos países, política-regulatoria-inmobiliaria-financiera en otros…), que en algunos países puede darse por solucionada y en otros todavía no.El índice menos rentable en 2019-2020 fue el español IBEX 35.También se muestra la evolución del desempleo en 30 países en el periodo 2000-2020. Los dos países con mayor desempleo en Febrero de 2013 y Febrero de 2020 fueron Grecia y España.English Abstract: The evolution of eleven stock market indices in the period 2007-15 April 2020 is compared and the declines of the “coronavirus crisis” are compared with those of the 2007 crisis… (financial in some countries, policy-regulatory-real estate-financial in others ...), which in some countries may be considered resolved and in others not yet. The least profitable index in 2019-2020 was the Spanish IBEX 35. The evolution of unemployment in 30 countries in the period 2000-2020 is also shown. The two countries with the highest unemployment in February 2013 and February 2020 were Greece and Spain.

Option Pricing with Mixed Levy Subordinated Price Process and Implied Probability Weighting Function
Abootaleb Shirvani,Yuan Hu,Svetlozar T. Rachev,Frank J. Fabozzi

It is essential to incorporate the impact of investor behavior when modeling the dynamics of asset returns. In this paper, we reconcile behavioral finance and rational finance by incorporating investor behavior within the framework of dynamic asset pricing theory. To include the views of investors, we employ the method of subordination which has been proposed in the literature by including business (intrinsic, market) time. We define a mixed Levy subordinated model by adding a single subordinated Levy process to the well-known log-normal model, resulting in a new log-price process. We apply the proposed models to study the behavioral finance notion of "greed and fear" disposition from the perspective of rational dynamic asset pricing theory. The greedy or fearful disposition of option traders is studied using the shape of the probability weighting function. We then derive the implied probability weighting function for the fear and greed deposition of option traders in comparison to spot traders. Our result shows the diminishing sensitivity of option traders. Diminishing sensitivity results in option traders overweighting the probability of big losses in comparison to spot traders.

Quantum Annealing Algorithm for Expected Shortfall based Dynamic Asset Allocation
Samudra Dasgupta,Arnab Banerjee

The 2008 mortgage crisis is an example of an extreme event. Extreme value theory tries to estimate such tail risks. Modern finance practitioners prefer Expected Shortfall based risk metrics (which capture tail risk) over traditional approaches like volatility or even Value-at-Risk. This paper provides a quantum annealing algorithm in QUBO form for a dynamic asset allocation problem using expected shortfall constraint. It was motivated by the need to refine the current quantum algorithms for Markowitz type problems which are academically interesting but not useful for practitioners. The algorithm is dynamic and the risk target emerges naturally from the market volatility. Moreover, it avoids complicated statistics like generalized pareto distribution. It translates the problem into qubit form suitable for implementation by a quantum annealer like D-Wave. Such QUBO algorithms are expected to be solved faster using quantum annealing systems than any classical algorithm using classical computer (but yet to be demonstrated at scale).

Semi-closed form prices of barrier options in the Hull-White model
Andrey Itkin,Dmitry Muravey

In this paper we derive semi-closed form prices of barrier (perhaps, time-dependent) options for the Hull-White model, ie., where the underlying follows a time-dependent OU process with a mean-reverting drift. Our approach is similar to that in (Carr and Itkin, 2020) where the method of generalized integral transform is applied to pricing barrier options in the time-dependent OU model, but extends it to an infinite domain (which is an unsolved problem yet). Alternatively, we use the method of heat potentials for solving the same problems. By semi-closed solution we mean that first, we need to solve numerically a linear Volterra equation of the first kind, and then the option price is represented as a one-dimensional integral. Our analysis shows that computationally our method is more efficient than the backward and even forward finite difference methods (if one uses them to solve those problems), while providing better accuracy and stability.

The Corporate Bond Market Reaction to the COVID-19 Crisis
Nozawa, Yoshio,Qiu, Yancheng
Using transaction data in the first quarter of 2020, we document how credit spreads of U.S. corporate bonds react to notable news during the COVID-19 pandemic. We find that corporate bonds issued by firms with a stronger tie with China react more to the lock-down of Wuhan in January 2020. The response of credit spreads, stock returns and bond illiquidity measures suggest that the bond market reaction to the Federal Reserve's announcement of the corporate bond purchase program on March 23, 2020 reflects lower default risk of borrowers rather than improved liquidity.

The Credit Debt Moratorium by COVID-19 as a Minimum Measure (La Moratoria De Deuda Crediticia Por COVID-19, Una Medida De Mínimos)
Zunzunegui, Fernando
Among the measures adopted by the Spanish government to face the economic crisis caused by the state of alarm of COVID-19, the moratorium on credit debt stands out. With this measure, it is about taking a leap in time to overcome the break and restart economic life. It is not a social rescue as in the financial crisis of 2008, it is a measure of re-engagement in activity. It is about giving a break to the most affected debtors to overcome the impasse. This article analyses the measure, its scope and limitations, making some critical considerations. We are facing an urgent regulation carried out in a hasty manner that has had to be modified within a few days to fill gaps and complete its scope. It is a minimum measure, which banks must take advantage of to overcome this temporary standstill in economic life and which particularly affects credit debt.

The EU Policy Response to the Current Pandemic Crisis through the Lens of the Eurogroup Report of 9 April 2020: Overview and Assessment (Cut-Off Date: 14 April 2020)
Gortsos, Christos
The purpose of this article is to briefly overview the Eurogroup Report of 9 April 2020 “on the comprehensive economic policy response to the COVID-19 pandemic” and assess its content. It is structured in 5 Sections: after the introductory remarks (in Section I), the coordinated actions taken until the Report’s publication are briefly reviewed in Section II, including measures taken by Members States, the (European) Commission, the European Central Bank and the European Banking Authority. Section III deals with the additional crisis response instruments, as proposed by the Commission, the European Investment Bank and the Eurogroup itself, as well the measures planned for preparing the ground for recovery. Section IV presents some further commitments undertaken by the Eurogroup and Section V contains the assessment.

The Effect of Product Market Competition and Financing Constraints on Dividend Payout
Abdoh, Hussein ,Maghyereh, Aktham Issa
We examine how product market competition and financing constraints influence firm payout policy. Using Compustat firms for the period 1996 to 2017, we show that competition decreases firms’ propensity to make payouts via dividends more if the firm is financially constrained. These results are consistent with the hypothesis that in the presence of financing constraints, creating internally generated funds (through the reduction of dividends) is more important for firms positioned in competitive markets.

The Effectiveness of Social Media and Press Release Transparency to Detect Indications of Financial Fraud
Astutik, Danik,Harymawan, Iman,Nasih, Mohammad
The purpose of this study is to investigate whether the transparency of social media and press releases can detect the financial fraud. This study uses 723 observational samples from 369 companies listed on the Indonesia Stock Exchange from 2015 to 2016. This study shows that social media transparency has negative and significant effects on the indication of financial fraud. However, there is no significant association between press release coverage and an indication of financial fraud. For investors, the results of this study indicate that social media transparency is one determinant that can be used to detect the indications of fraudulent acts on financial statements by the firms.

The Impact of Uncertainty and Certainty Shocks
Schüler, Yves S.
I propose a Bayesian quantile VAR to identify and assess the impact of uncertainty and certainty shocks, unifying Bloom's (2009) two identification steps into one. I find that an uncertainty shock widens the conditional distribution of future real economic activity growth, in line with a risk shock. Conversely, a certainty shock (a shock strongly decreasing uncertainty) narrows the conditional distribution of future real activity growth. In addition to the difference in signs, I show that the two shocks are different shocks. Each shock impacts the real economy uniquely. I support this with the underlying events: For instance, uncertainty shocks relate to events such as Black Monday and 9/11, but also to fears about future negative economic outcomes. In contrast, certainty shocks often link to phases of irrational exuberance. Commonly, no distinction is made between uncertainty and certainty shocks. I show that uncertainty shocks become more important if distinguished from certainty shocks.

The Sandbox Paradox: Balancing the Need to Facilitate Innovation with the Risk of Regulatory Privilege
Knight, Brian,Mitchell, Trace
In recent years, “regulatory sandboxes” have gained a great deal of attention from policymakers, regulators, and regulatory scholars. Regulatory sandboxes are closed testing environments in which specific firms are able to experiment with new and innovative business models or products with reduced regulatory burden or expedited regulatory decisions. Sandbox advocates support or defend regulatory sandboxes as a way to promote entrepreneurialism and innovation within the financial sector while still maintaining mechanisms for consumer protection and regulatory oversight. Opponents of sandboxes tend to focus on the potential risk to the consumers who use the services being tested in the sandbox. However, there is a third group affected by regulatory sandboxes: the competitors of firms in the sandbox. By definition, regulatory sandboxes grant certain advantages to specific firms without extending those same privileges to other firms. The goal of this paper is to examine the potential regulatory advantages sandboxes offer, consider the possible risks and costs associated with those advantagesâ€"including the potential to distort the market and incentivize cronyismâ€"and propose best practices that policymakers could use to mitigate those costs.

The rise of science in low-carbon energy technologies
Kerstin Hötte,Anton Pichler,François Lafond

Successfully combating climate change will require substantial technological improvements in Low-Carbon Energy Technologies (LCETs). An efficient allocation of R&D budgets to accelerate technological advancement necessitates a better understanding of how LCETs rely on scientific knowledge. In this paper, we sketch for the first time the evolution of knowledge bases for key LCETs and show how technological interdependencies change in time. We use data covering almost all US patents as well as scientific articles published in the past two centuries to quantify the history of LCETs and their dependence on science. We show how the drivers of low-carbon innovations shifted from Hydro and Wind energy to Nuclear fission, and more recently to Solar PV and back to Wind. Our analysis demonstrates that 1) LCETs rely increasingly on science, 2) Solar PV and Nuclear fusion depend heavily on science, while Hydro energy does not, 3) renewable and nuclear energy technologies rely on a strikingly different kind of science, and 4) there is a remarkable convergence of scientific knowledge bases of renewables over recent decades. These findings suggest a need for technology-specific research policies, although targeted research in renewables is likely to cross-fertilize a wider range of LCETs.

Unconventional Monetary Policy Shocks in the Euro Area and the Sovereign-Bank Nexus
Hristov, Nikolay,Hülsewig, Oliver,Scharler, Johann
We explore the effects of the ECB’s unconventional monetary policy on the banks’ sovereign debt portfolios. In particular, using panel vector autoregressive (VAR) models we analyze whether banks increased their domestic government bond holdings in response to non-standard monetary policy shocks, thereby possibly promoting the sovereign-bank nexus, i.e. the exposure of banks to the debt issued by the national government. Our results suggest that euro area crisis countries’ banks enlarged their exposure to domestic sovereign debt after innovations related to unconventional monetary policy. Moreover, the restructuring of sovereign debt portfolios was characterized by a home bias.

What Quants Can Learn from the COVID Crisis
Lipton, Alex,Lopez de Prado, Marcos
Many quantitative firms have suffered substantial losses as a result of the COVID-19 selloff. In this note, we highlight three lessons that quantitative researchers could learn from this crisis. First, researchers should develop more nowcasting methods, and pay less attention to forecasts. Second, researchers should use backtesting for deconstructing theories, not for optimizing trading rules. Third, all-weather strategies are more likely to be false, and it is a safer bet to develop strategies for well-defined market regimes.