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This paper studies the consumption response to an increase in the domestic value of foreign currency household debt during a large depreciation. We use detailed consumption survey data that follows households for four years around Hungary’s 2008 currency crisis. We find that, relative to similar local currency debtors, foreign currency debtors reduce consumption approximately one-for-one with increased debt service, suggesting a role for liquidity constraints. We document a variety of margins of adjustment to the shock. Foreign currency debtors reduce both the quantity and quality of expenditures, consistent with nonhomothetic preferences and “flight from quality.” We find no effect on overall household labor supply, consistent with a weak wealth effect on labor supply. However, a small subset of households adjusts labor supply toward foreign income streams. Affected households also boost home pro- duction, suggesting a shift in consumption from money-intensive to time-intensive goods.
We analyze the impact of decreases in available lending resources on quantitative and qualita- tive dimensions of firms’ patenting activities. We thereby make use of the European Banking Authority?s capital exercise to carve out the causal effect of bank lending on firm innovation. In order to do so we combine various datasets to derive information on firms’ financials, their patenting behaviors, as well as their relationships with their lenders. Building on this self- generated dataset, we provide support for the “less finance, less innovation” view. At the same time, we show that lower available financial resources for firms lead to improvement in the qualitative dimensions of their patents. Hence, we carve out a “less finance, less but better innovation” pattern.
We investigate the differential effect of the COVID-19 shock to the stock market shock on the share prices of firms with different levels of ESG (Environmental, Social and Governance) scores. Thereby, we analyse whether and to what extent better ESG ratings provided insurance for investors in the stocks of those firms during this shock. We focus our analysis on the European market in which ESG investment plays a particularly important role. Using a broad sample of listed firms we provide mixed evidence. On the one hand, we show that immediately after the start of the shock firms with a higher ESG score outperformed their peers. On the other hand, this effect faded less than six weeks later. Given the quick recovery of the market our finding supports the idea that ESG stocks provide limited insurance in severe crises.
Die BaFin hat im August 2021 eine Richtlinie für nachhaltige Investmentvermögen vorgelegt. Diese soll regeln, unter welchen Voraussetzungen ein Fonds als „nachhaltig“, „grün“ o.ä. bezeichnet und vermarktet werden darf. Zwar sind aufsichtsrechtliche Maßnahmen, die darauf abzielen, die Qualität von Informationen zu Nachhaltigkeitscharakteristika von Finanzprodukten zu erhöhen, grundsätzlich zu begrüßen. Der Erlass der konsultierten Richtlinie ist jedoch nicht zu befürworten. Im Lichte der einschlägigen unionsrechtlichen Regelwerke und Initiativen ist unklar, welchen informationellen Mehrwert diese rein nationale Maßnahme schaffen soll. Ferner bleibt auf Grundlage des Entwurfs unklar, anhand welcher Maßstäbe die „Nachhaltigkeit“ eines Investmentvermögens beurteilt werden soll, sodass das primäre Regelungsziel einer verbesserten Anlegerinformation nicht erreicht würde.
The US Tax Cuts and Jobs Act (TCJA) led to a drastic reduction in the corporate tax and improved the treatment of C corporations compared to S corporations. We study the differential effect of the TCJA on these types of corporations using key economic variables of US banks, such as the number of employees, average salaries and benefits, profit/loss before taxes, and net income. Our analysis suggests that the TCJA increased the net-of-tax profits of C corporation banks compared to S corporations and, to a lesser extent, their pre-tax profits. At the same time, the reform triggered no significantly differential effect on the employment and average wages.
Historically Central Bank Independence (CBI) was anything but the norm. CBI seems to contradict core principles of democracy. Most economists were also against CBI. After the Great Inflation of the 1970ies many empirical studies demonstrated that there is a strong negative correlation between the degree of CBI and the rate of inflation. In 1990 most major countries had endowed their central bank with the status of independence. Overburdening with elevated expectations and additional competences are threatening the reputation of central banks and undermining the case for CBI.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
This paper sets up an experimental asset market in the laboratory to investigate the effects of ambiguity on price formation and trading behavior in financial markets. The obtained trading data is used to analyze the effect of ambiguity on various market outcomes (the price level, volatility, trading activity, market liquidity, and the degree of speculative trading) and to test the quality of popular empirical market-based measures for the degree of ambiguity. We find that ambiguity decreases market prices and trading activity; ambiguity leads to lower market liquidity through wider bid-ask spreads; and ambiguity leads to less speculative trading. We also find that popular market-based measures of ambiguity used in the empirical literature do not seem to correctly capture the true degree of ambiguity.
We raise some critical points against a naïve interpretation of “green finance” products and strategies. These critical insights are the background against which we take a closer look at instruments and policies that might allow green finance to become more impactful. In particular, we focus on the role of a taxonomy and investor activism. We also describe the interaction of government policies with green finance practice – an aspect, which has been mostly neglected in policy debates but needs to be taken into account. Finally, the special case of green government bonds is discussed.
Climate change is one of the highest-ranking issues on the political and social agenda. Vulnerabilities of the world ecosystem laid bare by the COVID-19 pandemic and the potential damage for the human and business life made the need for urgent action clear once again. Corporations are one of the main actors that will play a major role in the decarbonisation of the economy. They need to put forward a net zero strategy and targets, transitioning to net-zero by 2050. Yet, an important but rather overlooked stakeholder group in the sustainability debates can pose a significant stumbling block in this transition: employees. Although climate action has huge benefits by ameliorating adverse environmental events and is expected to have overall positive impact on employment, net zero transition in companies, especially in certain sectors and regions, will cause substantial adverse employment effects for the workforce. This has the potential to slow down or even derail the necessary climate action in companies. In this regard, just transition is a promising concept, which calls for a swift and decisive climate action in corporations while taking account of and mitigating adverse effects for their workforce. If well implemented, it can accelerate net zero transition in companies. This potential clash of environmental (E) and social (S) aspects of ESG agenda, materialised in the companies’ net zero transition, and its potential remedy, just transition, have important implications for corporate governance and finance, especially for directors’ duties & executive remuneration, sustainability disclosures, institutional investors’ engagement and green finance.
We raise some critical points against a naïve interpretation of “green finance” products and strategies. These critical insights are the background against which we take a closer look at instruments and policies that might allow green finance to become more impactful. In particular, we focus on the role of a taxonomy and investor activism. We also describe the interaction of government policies with green finance practice – an aspect, which has been mostly neglected in policy debates but needs to be taken into account. Finally, the special case of green government bonds is discussed.
Analysing causality among oil prices and, in general, among financial and economic variables is of central relevance in applied economics studies. The recent contribution of Lu et al. (2014) proposes a novel test for causality— the DCC-MGARCH Hong test. We show that the critical values of the test statistic must be evaluated through simulations, thereby challenging the evidence in papers adopting the DCC-MGARCH Hong test. We also note that rolling Hong tests represent a more viable solution in the presence of short-lived causality periods.
This paper examines how the transmission of government portfolio risk arising from maturity operations depends on the stance of monetary/fiscal policy. Accounting for risk premia in the fiscal theory allows the government portfolio to affect the expected inflation, even in a frictionless economy. The effects of maturity rebalancing on expected inflation in the fiscal theory directly depend on the conditional nominal term premium, giving rise to an optimal debt maturity policy that is state dependent. In a calibrated macro-finance model, we demonstrate that maturity operations have sizable effects on expected inflation and output through our novel risk transmission mechanism.
Recent advances in natural language processing have contributed to the development of market sentiment measures through text content analysis in news providers and social media. The effectiveness of these sentiment variables depends on the imple- mented techniques and the type of source on which they are based. In this paper, we investigate the impact of the release of public financial news on the S&P 500. Using automatic labeling techniques based on either stock index returns or dictionaries, we apply a classification problem based on long short-term memory neural networks to extract alternative proxies of investor sentiment. Our findings provide evidence that there exists an impact of those sentiments in the market on a 20-minute time frame. We find that dictionary-based sentiment provides meaningful results with respect to those based on stock index returns, which partly fails in the mapping process between news and financial returns.
We present new statistical indicators of the structure and performance of US banks from 1990 to today, geographically disaggregated at the level of individual counties. The constructed data set (20 indicators for some 3150 counties over 31 years, for a total of about 2 million data points) conveys a detailed picture of how the geography of US banking has evolved in the last three decades. We consider the data as a stepping stone to understand the role banks and banking policies may have played in mitigating, or exacerbating, the rise of poverty and inequality in certain US regions.
Nach der Bundestagswahl am 26. September 2021 wird sich die künftige Bundesregierung mit einer Reihe drängender Herausforderungen befassen müssen. Aus Sicht des Leibniz-Instituts für Finanzmarktforschung SAFE haben die folgenden, miteinander verbundenen Einzelpunkte dabei Priorität:
1. Schaffung eines ordnungspolitischen Pakets zur Sicherung globaler Gemeinschaftsgüter, wie etwa des Klimas
2. Initiative zum Aufbau notwendiger Datensätze und Standards für eine zielgenaue Nachhaltigkeitsgestaltung an den Finanzmärkten
3. regulatorischer Fahrplan zur Erfassung, Ermöglichung und Einhegung einer digitalen Transformation des Finanzsystems
4. Vollendung der Bankenunion, insbesondere durch einen „europäischen Schlussstein“: der Schaffung einer einheitlichen Aufsicht und Letztabsicherung
5. Durchbrechung des „Doom-Loop“ zwischen Staaten und Banken in Europa, insbesondere durch Begrenzung des Umfangs, in dem eigene Staatsanleihen im Portfolio von Banken liegen dürfen
6. ernsthafter Versuch zur Schaffung eines einheitlichen und integren europäischen Kapitalmarkts mit einer Aufsicht nach US-Vorbild
7. Banken- und Kapitalmarktunion als wesentliche Bausteine für eine grundlegende Reform der Altersversorgung mit mehr Teilhabe aller Bürger:innen an der Leistungsentwicklung der Volkswirtschaft
Using loan-level data from Germany, we investigate how the introduction of model-based capital regulation affected banks’ ability to absorb shocks. The objective of this regulation was to enhance financial stability by making capital requirements responsive to asset risk. Our evidence suggests that banks ‘optimized’ model-based regulation to lower their capital requirements. Banks systematically underreported risk, with under reporting being more pronounced for banks with higher gains from it. Moreover, large banks benefitted from the regulation at the expense of smaller banks. Overall, our results suggest that sophisticated rules may have undesired effects if strategic misbehavior is difficult to detect.
In this study, we analyze the trading behavior of banks with lending relationships. We combine detailed German data on banks’ proprietary trading and market making with lending information from the credit register and then examine how banks trade stocks of their borrowers around important corporate events. We find that banks trade more frequently and also profitably ahead of events when they are the main lender (or relationship bank) for the borrower. Specifically, we show that relationship banks are more likely to build up positive (negative) trading positions in the two weeks before positive (negative) news events, and also that they unwind these positions shortly after the event. This trading pattern is more pronounced for unscheduled earnings events, M&A transactions, and after borrower obtain new bank loans. Our results suggest that lending relationships endow banks with important information, highlighting the potential for conflicts of interest in banking, which has been a prominent concern in the regulatory debate.
Increasing the diversity of policy committees has taken center stage worldwide, but whether and why diverse committees are more effective is still unclear. In a randomized control trial that varies the salience of female and minority representation on the Federal Reserve’s monetary policy committee, the FOMC, we test whether diversity affects how Fed information influences consumers’ subjective beliefs. Women and Black respondents form unemployment expectations more in line with FOMC forecasts and trust the Fed more after this intervention. Women are also more likely to acquire Fed-related information when associated with a female official. White men, who are overrepresented on the FOMC, do not react negatively. Heterogeneous taste for diversity can explain these patterns better than homophily. Our results suggest more diverse policy committees are better able to reach underrepresented groups without inducing negative reactions by others, thereby enhancing the effectiveness of policy communication and public trust in the institution.
We identify strong cross-border institutions as a driver for the globalization of in-novation. Using 67 million patents from over 100 patent offices, we introduce novel measures of innovation diffusion and collaboration. Exploiting staggered bilateral in-vestment treaties as shocks to cross-border property rights and contract enforcement, we show that signatory countries increase technology adoption and sourcing from each other. They also increase R&D collaborations. These interactions result in techno-logical convergence. The effects are particularly strong for process innovation, and for countries that are technological laggards or have weak domestic institutions. Increased inter-firm rather than intra-firm foreign investment is the key channel.
Using hand-collected data on CEO appointments during shareholder activism campaigns, this study examines whether shareholder involvement in CEO recruiting affects frictions in CEO hiring decisions. The results indicate that appointments of CEOs who are recruited with shareholder activist influence are followed by more favorable stock market reactions and stronger profitability improvements than CEO appointments that also occur during activism campaigns but without the influence of activists. I find little evidence that shareholder activists increase hiring frictions by facilitating the recruiting of CEOs who will implement myopic corporate policies. Analyses of recruiting process characteristics reveal that activist influence is associated with more resources being dedicated to the CEO search process and with a higher propensity to recruit CEOs from outside the firm. These findings contribute to the CEO labor market literature, which tends to focus on the decision to remove incumbent CEOs but provides limited insights into CEO recruiting.
This paper argues that the key mechanisms protecting retail investors’ financial stake in their portfolio investments are indirect. They do not rely on actions by the investors or by any private actor directly charged with looking after investors’ interests. Rather, they are provided by the ecosystem that investors (are legally forced to) inhabit, as a byproduct of the mostly self-interested, mutually and legally constrained behavior of third parties without a mandate to help the investors (e.g., speculators, activists). This elucidates key rules, resolves the mandatory vs. enabling tension in corporate/securities law, and exposes passive investing’s fragile reliance on others’ trading.
Do required minimum distribution 401(k) rules matter, and for whom? Insights from a lifecylce model
(2021)
Tax-qualified vehicles helped U.S. private-sector workers accumulate $25Tr in retirement assets. An often-overlooked important institutional feature shaping decumulations from these retirement plans is the “Required Minimum Distribution” (RMD) regulation, requiring retirees to withdraw a minimum fraction from their retirement accounts or pay excise taxes on withdrawal shortfalls. Our calibrated lifecycle model measures the impact of RMD rules on financial behavior of heterogeneous households during their worklives and retirement. We show that proposed reforms to delay or eliminate the RMD rules should have little effects on consumption profiles but more impact on withdrawals and tax payments for households with bequest motives.
Expectations about economic variables vary systematically across genders. In the domain of inflation, women have persistently higher expectations than men. We argue that traditional gender roles are a significant factor in generating this gender expectations gap as they expose women and men to different economic signals in their daily lives. Using unique data on the participation of men and women in household grocery chores, their resulting exposure to price signals, and their inflation expectations, we document a tight link between the gender expectations gap and the distribution of grocery shopping duties. Because grocery prices are highly volatile, and consumers focus disproportionally on positive price changes, frequent exposure to grocery prices increases perceptions of current inflation and expectations of future inflation. The gender expectations gap is largest in households whose female heads are solely responsible for grocery shopping, whereas no gap arises in households that split grocery chores equally between men and women. Our results indicate that gender differences in inflation expectations arise due to social conditioning rather than through differences in innate abilities, skills, or preferences.
This paper aims at an improved understanding of the relationship between monetary policy and racial inequality. We investigate the distributional effects of monetary policy in a unified framework, linking monetary policy shocks both to earnings and wealth differentials between black and white households. Specifically, we show that, although a more accommodative monetary policy increases employment of black households more than white households, the overall effects are small. At the same time, an accommodative monetary policy shock exacerbates the wealth difference between black and white households, because black households own less financial assets that appreciate in value. Over multi-year time horizons, the employment effects are substantially smaller than the countervailing portfolio effects. We conclude that there is little reason to think that accommodative monetary policy plays a significant role in reducing racial inequities in the way often discussed. On the contrary, it may well accentuate inequalities for extended periods.
Our starting point is the following simple but potentially underappreciated observation: When assessing willingness to pay (WTP) for hedonic features of a product, the results of such measurement are influenced by the context in which the consumer makes her real or hypothetical choice or in which the questions to which she replies are set (such as in a contingent valuation analysis). This observation is of particular relevance when WTP regards sustainability, the “non-use value” of which does not derive from a direct (physical) sensation and where perceived benefits depend heavily on available information and deliberations. The recognition of such context sensitivity paves the way for a broader conception of consumer welfare (CW), and our proposed standard of “reflective WTP” may materially change the scope for private market initiatives with regards to sustainability, while keeping the analytical framework within the realm of the CW paradigm. In terms of practical implications, we argue, for instance, that actual purchasing decisions may prove insufficient to measure consumer appreciation of sustainability, as they may rather echo learnt but unreflected heuristics and may be subject to the specific shopping context, such as heavy price promotions. Also, while it may reflect current social norm, the latter may change considerably over time as more consumers adopt their behavior.
Extant research shows that CEO characteristics affect earnings management. This paper studies how investors infer a specific characteristic of CEOs, namely moral commitment to honesty, from earnings management and how this perception – in conjunction with their own social and moral preferences – shapes their investment choices. We conduct two laboratory experiments simulating investment choices. Our results show that participants perceive a CEO to be more committed to honesty when they infer that the CEO engaged less in earnings management. For investment decisions, a one standard deviation increase in a CEO's perceived commitment to honesty compared to another CEO reduces the relevance of differences in the CEOs’ claimed future returns by 40%. This effect is most prominent among investors with a proself value orientation. To prosocial investors, their own honesty values and those attributed to the CEO matter directly, while returns play a secondary role. Overall, perceived CEO honesty matters to different investors for distinct reasons.
We study the design features of disclosure regulations that seek to trigger the green transition of the global economy and ask whether such regulatory interventions are likely to bring about sufficient market discipline to achieve socially optimal climate targets.
We categorize the transparency obligations stipulated in green finance regulation as either compelling the standardized disclosure of raw data, or providing quality labels that signal desirable green characteristics of investment products based on a uniform methodology. Both categories of transparency requirements can be imposed at activity, issuer, and portfolio level.
Finance theory and empirical evidence suggest that investors may prefer “green” over “dirty” assets for both financial and non-financial reasons and may thus demand higher returns from environmentally-harmful investment opportunities. However, the market discipline that this negative cost of capital effect exerts on “dirty” issuers is potentially attenuated by countervailing investor interests and does not automatically lead to socially optimal outcomes.
Mandatory disclosure obligations and their (public) enforcement can play an important role in green finance strategies. They prevent an underproduction of the standardized high-quality information that investors need in order to allocate capital according to their preferences. However, the rationale behind regulatory intervention is not equally strong for all categories and all levels of “green” disclosure obligations. Corporate governance problems and other agency conflicts in intermediated investment chains do not represent a categorical impediment for green finance strategies.
However, the many forces that may prevent markets from achieving socially optimal equilibria render disclosure-centered green finance legislation a second best to more direct forms of regulatory intervention like global carbon taxation and emissions trading schemes. Inherently transnational market-based green finance concepts can play a supporting role in sustainable transition, which is particularly important as long as first-best solutions remain politically unavailable.
Many equity markets combine continuous trading and call auctions. Oftentimes designated market makers (DMMs) supply additional liquidity. Whereas prior research has focused on their role in continuous trading, we provide a detailed analysis of their activity in call auctions. Using data from Germany’s Xetra system, we find that DMMs are most active when they can provide the greatest benefits to the market, i.e., in relatively illiquid stocks and at times of elevated volatility. Their trades stabilize prices and they trade profitably.
This in-depth analysis provides evidence on differences in the practice of supervising large banks in the UK and in the euro area. It identifies the diverging institutional architecture (partially supranationalised vs. national oversight) as a pivotal determinant for a higher effectiveness of supervisory decision making in the UK. The ECB is likely to take a more stringent stance in prudential supervision than UK authorities. The setting of risk weights and the design of macroprudential stress test scenarios document this hypothesis. This document was provided by the Economic Governance Support Unit at the request of the ECON Committee.
This document was requested by the European Parliament's Committee on Economic and Monetary Affairs. It was originally published on the European Parliament’s webpage: www.europarl.europa.eu/RegData/etudes/IDAN/2021/689443/IPOL_IDA(2021)689443_EN.pdf
The crisis management and deposit insurance (CMDI) framework in the euro area requires a reset. Although its policy objectives remain valid, the means of achieving them do not. As the euro area comes the end of the long transition period taken to implement the BRRD/SRMR, it should take the opportunity to reset expectations about resolution.
Above all, resolution should be for the many, not just the few. There should be a single presumptive path for dealing with failed banks: the use of bail-in to facilitate orderly liquidation under a solvent-wind down strategy. This will protect deposits and set the stage – together with the backstop that the European Stability Mechanism provides to the Single Resolution Fund (SRF) -- for the transformation of the SRF into the Single Deposit Guarantee Scheme (SDGS). To avoid forbearance, responsibility for emergency liquidity assistance (ELA) should rest, not with national central banks, but with the ECB as a single lender of last resort. Finally, national deposit guarantee schemes should function as institutional protection schemes and become investors of last resort in their member banks. Together, these measures would complete Banking Union, promote market discipline, avoid imposing additional burdens on taxpayers, help untie the doom loop between weak banks and weak governments, strengthen the euro and enhance financial stability.
This paper discusses policy implications of a potential surge in NPLs due to COVID-19. The study provides an empirical assessment of potential scenarios and draws lessons from previous crises for effective NPL treatment. The paper highlights the importance of early and realistic assessment of loan losses to avoid adverse incentives for banks. Secondary loan markets would help in this process and further facilitate bank resolution as laid down in the BRRD, which should be uphold even in extreme scenarios.
This in-depth analysis proposes ways to retract from supervisory COVID-19 support measures without perils for financial stability. It simulates the likely impact of the corona crisis on euro area banks’ capital and predicts a significant capital shortfall. We recommend to end accounting practices that conceal loan losses and sustain capital relief measures. Our in-depth analysis also proposes how to address the impending capital shortfall in resolution/liquidation and a supranational recapitalisation.
In this paper we put forward a legal argument in favour of granting more independence to BaFin, the German securities market supervisor. Following the Wirecard scandal, our reform proposal aims at strengthening the impartiality and credibility of the German supervisor and, as a consequence, at restoring capital market integrity. In order to achieve the necessary degree of democratic legitimacy for giving BaFin more independence and disassociating it from the Ministry of Finance, the paper sets out the necessary steps for a legal reform that creates accountability of BaFin vis-à-vis the Parliament, subjecting it to strict disclosure and reporting obligations.
Incentives, self-selection, and coordination of motivated agents for the production of social goods
(2021)
We study, theoretically and empirically, the effects of incentives on the self-selection and coordination of motivated agents to produce a social good. Agents join teams where they allocate effort to either generate individual monetary rewards (selfish effort) or contribute to the production of a social good with positive effort complementarities (social effort). Agents differ in their motivation to exert social effort. Our model predicts that lowering incentives for selfish effort in one team increases social good production by selectively attracting and coordinating motivated agents. We test this prediction in a lab experiment allowing us to cleanly separate the selection effect from other effects of low incentives. Results show that social good production more than doubles in the low- incentive team, but only if self-selection is possible. Our analysis highlights the important role of incentives in the matching of motivated agents engaged in social good production.
Managed portfolios that exploit positive first-order autocorrelation in monthly excess returns of equity factor portfolios produce large alphas and gains in Sharpe ratios. We document this finding for factor portfolios formed on the broad market, size, value, momentum, investment, prof- itability, and volatility. The value-added induced by factor management via short-term momentum is a robust empirical phenomenon that survives transaction costs and carries over to multi-factor portfolios. The novel strategy established in this work compares favorably to well-known timing strategies that employ e.g. factor volatility or factor valuation. For the majority of factors, our strategies appear successful especially in recessions and times of crisis.
We empirically examine the Capital Purchase Program (CPP) used by the US gov- ernment to bail out distressed banks with equity infusions during the Great Recession. We find strong evidence that a feature of the CPP – the government’s ability to ap- point independent directors on the board of an assisted bank that missed six dividend payments to the Treasury – helped attenuate bailout-related moral hazard. Banks were averse to these appointments – the empirical distribution of missed payments exhibits a sharp discontinuity at five. Director appointments by the Treasury led to improved bank performance, lower CEO pay, and higher stock market valuations.
This paper explores the interplay of feature-based explainable AI (XAI) tech- niques, information processing, and human beliefs. Using a novel experimental protocol, we study the impact of providing users with explanations about how an AI system weighs inputted information to produce individual predictions (LIME) on users’ weighting of information and beliefs about the task-relevance of information. On the one hand, we find that feature-based explanations cause users to alter their mental weighting of available information according to observed explanations. On the other hand, explanations lead to asymmetric belief adjustments that we inter- pret as a manifestation of the confirmation bias. Trust in the prediction accuracy plays an important moderating role for XAI-enabled belief adjustments. Our results show that feature-based XAI does not only superficially influence decisions but re- ally change internal cognitive processes, bearing the potential to manipulate human beliefs and reinforce stereotypes. Hence, the current regulatory efforts that aim at enhancing algorithmic transparency may benefit from going hand in hand with measures ensuring the exclusion of sensitive personal information in XAI systems. Overall, our findings put assertions that XAI is the silver bullet solving all of AI systems’ (black box) problems into perspective.
We focus on the role of social media as a high-frequency, unfiltered mass information transmission channel and how its use for government communication affects the aggregate stock markets. To measure this effect, we concentrate on one of the most prominent Twitter users, the 45th President of the United States, Donald J. Trump. We analyze around 1,400 of his tweets related to the US economy and classify them by topic and textual sentiment using machine learning algorithms. We investigate whether the tweets contain relevant information for financial markets, i.e. whether they affect market returns, volatility, and trading volumes. Using high-frequency data, we find that Trump’s tweets are most often a reaction to pre-existing market trends and therefore do not provide material new information that would influence prices or trading. We show that past market information can help predict Trump’s decision to tweet about the economy.
We define a sentiment indicator that exploits two contrasting views of return predictability, and study its properties. The indicator, which is based on option prices, valuation ratios and interest rates, was unusually high during the late 1990s, reflecting dividend growth expectations that in our view were unreasonably optimistic. We interpret it as helping to reveal irrational beliefs about fundamentals. We show that our measure is a leading indicator of detrended volume, and of various other measures associated with financial fragility. We also make two methodological contributions. First, we derive a new valuation-ratio decomposition that is related to the Campbell and Shiller (1988) loglinearization, but which resembles the traditional Gordon growth model more closely and has certain other advantages for our purposes. Second, we introduce a volatility index that provides a lower bound on the market's expected log return.
The pricing of an ambiguous asset, whose cash flow stream is uncertain, may be affected by three factors: the belief regarding the realization likelihood of cash flows, the subjective attitude towards risk, and the attitude towards ambiguity. While previous literature looks at the total price discount under ambiguity, this paper investigates with laboratory experiments how much effect each factor can induce. We apply both non-parametric and parametric methods to cleanly separate the belief effects, the risk premiums, and the ambiguity premiums from each other. Both methods lead to similar results: Overall, subjects have substantial ambiguity aversion, and ambiguity premiums account for the largest price deviation component when the degree of ambiguity is high. As information accumulates, ambiguity premiums decrease. We also find that beliefs do influence prices under ambiguity. This is not because beliefs are biased towards either good or bad scenarios per se, but because subjects display sticky belief updating as new information becomes available. The clear separation performed in this paper between belief and attitude also enables a more accurate estimation of the parameter of ambiguity aversion compared to previous studies, since the effect of beliefs is partialled out. Overall, we find empirically that both factors, belief and attitude towards ambiguity, are important factors in pricing under ambiguity.
The salience of ESG ratings for stock pricing: evidence from (potentially) confused investors
(2021)
We exploit the a modification to Sustainanlytics’ environmental, social, and governance (ESG) rating methodology, which is subsequently adopted by Morningstar, to study whether ESG ratings are salient for stock pricing. We show that the inversion of the rating scale but not new information leads some investors to make incorrect assessments about the meaning of the change in ESG ratings. They buy (sell) stocks they misconceive as ESG upgraded (downgraded) even when the opposite is true. This trading behavior exerts transitory price pressure on affected stocks. Our paper highlights the importance of ESG ratings for investors and consequently for asset prices.
Dieser Artikel behandelt das Zusammenspiel von staatlich organisierten sozialen Sicherungssystemen und der privaten Eigenvorsorge durch Vermögensbildung als Grundpfeiler der sozialen Marktwirtschaft in Deutschland. Die jährlichen Ausgaben der verschiedenen staatlichen Sicherungssysteme belaufen sich auf rund ein Drittel des erwirtschafteten Bruttosozialprodukts, wobei die umlagefinanzierten Alterssicherungssysteme für die Arbeitsnehmer den größten Anteil ausmachen. Sachvermögen in Form von selbst genutzten Wohnungen sowie Finanzvermögen in Form von Bankeinlagen und Ansprüche gegen private Versicherungen machen den größten Anteil der Eigenversorge aus. Aufgrund des niedrigen Zinsniveaus sowie des demografischen Wandels der Gesellschaft wird die Eigenvorsorge durch Anlagen an den internationalen Wertpapiermärkten sowohl für Selbständige als auch Arbeitsnehmer immer bedeutender.
We show that financial advisors recommend more costly products to female clients, based on minutes from about 27,000 real-world advisory meetings and client portfolio data. Funds recommended to women have higher expense ratios controlling for risk, and women less often receive rebates on upfront fees for any given fund. We develop a model relating these findings to client stereotyping, and empirically verify an additional prediction: Women (but not men) with higher financial aptitude reject recommendations more frequently. Women state a preference for delegating financial decisions, but appear unaware of associated higher costs. Evidence of stereotyping is stronger for male advisors.
We conducted a large-scale household survey in November 2020 to study how altering the time frame of a message (temporal framing) regarding an imminent positive income shock affects consumption plans. The income shock derives from the abolishment of the German solidarity surcharge on personal income taxes, effective in January 2021. We randomize across survey participants whether their extra disposable income is presented in Euros per month, Euros per year, or Euros per ten year-period. Our main findings are as follows: In General, we find our respondents’ intended Marginal Propensity to Consume (MPC) is 28.2%. Across all three treatments, the MPC is a positive function of age and being female while it is a negative function of the income increase’s size, self- control, and being unemployed. Temporal framing effects are statistically and economically highly significant as we find the monthly treatment groups’ average MPC 5.6 and 8.7 percentage points higher compared to the yearly and 10-yearly treatment groups. We will be able to analyze the real consumption behavior of households throughout 2021 based on re-surveying the participants as well as by using transaction-based bank data.
How people form beliefs is crucial for understanding decision-making un- der uncertainty. This is particularly true in a situation such as a pandemic, where beliefs will affect behaviors that impact public health as well as the aggregate economy. We conduct two survey experiments to shed light on potential biases in belief formation, focusing in particular on the tone of information people choose to consume and how they incorporate this information into their beliefs. In the first experiment, people express their preferences over pandemic-related articles with optimistic and pessimistic headlines, and are then randomly shown one of the articles. We find that respondents with more pessimistic prior beliefs about the pandemic are substantially more likely to prefer pessimistic articles, which we interpret as evidence of confirmation bias. In line with this, respondents assigned to the less preferred article rate it as less reliable and informative (relative to those who prefer it); they also discount information from the article when it is less preferred. We further find that these motivated beliefs end up impacting incentivized behavior. In a second experiment, we study how partisan views interact with information selection and processing. We find strong evidence of source dependence: revealing the news source further distorts information acquisition and processing, eliminating the role of prior beliefs in article choice.
This paper studies the behavior of competing firms in a duopoly with rational inattentive consumers. Firms play a sequential game in which they decide to obfuscate their individual prices before competing on price. Probabilistic demand functions are endogenously determined by the consumers’ optimal information strategy, which depends on the firms’ obfuscation choice and the consumers’ unrestricted prior beliefs. We show that the game may result in an obfuscation equilibrium with high prices where both firms obfuscate and a transparency equilibrium with low prices and no obfuscation, providing an argument for market regulation. Lower information costs and asymmetric prior beliefs about prices reduce the probability of an obfuscation equilibrium. Using data on Sweden, we document a decrease in price complexity and corresponding prices in the market for mobile phone subscriptions in the last two decades. Our model rationalizes these changes and explains why complexity and high prices persist in some but not all digitalized markets.
The disposition effect is implicitly assumed to be constant over time. However, drivers of the disposition effect (preferences and beliefs) are rather countercyclical. We use individual investor trading data covering several boom and bust periods (2001-2015). We show that the disposition effect is countercyclical, i.e. is higher in bust than in boom periods. Our findings are driven by individuals being 25% more likely to realize gains in bust than in boom periods. These changes in investors’ selling behavior can be linked to changes in investors’ risk aversion and in their beliefs across financial market cycles.
The centrality of the United States in the global financial system is taken for granted, but its response to recent political and epidemiological events has suggested that China now holds a comparable position. Using minute-by-minute data from 2012 to 2020 on the financial performance of twelve country-specific exchange-traded funds, we construct daily snapshots of the global financial network and analyze them for the centrality and connectedness of each country in our sample. We find evidence that the U.S. was central to the global financial system into 2018, but that the U.S.-China trade war of 2018–2019 diminished its centrality, and the Covid-19 outbreak of 2019–2020 increased the centrality of China. These indicators may be the first signals that the global financial system is moving from a unipolar to a bipolar world.
Smart(phone) investing? A within investor-time analysis of new technologies and trading behavior
(2021)
Using transaction-level data from two German banks, we study the effects of smartphones on investor behavior. Comparing trades by the same investor in the same month across different platforms, we find that smartphones increase purchasing of riskier and lottery-type assets and chasing past returns. After the adoption of smartphones, investors do not substitute trades across platforms and buy also riskier, lottery-type, and hot investments on other platforms. Using smartphones to trade specific assets or during specific hours contributes to explain our results. Digital nudges and the device screen size do not mechanically drive our results. Smartphone effects are not transitory.
The FOMC risk shift
(2021)
We identify a component of monetary policy news that is extracted from high-frequency changes in risky asset prices. These surprises, which we call “risk shifts”, are uncorrelated, and therefore complementary, to risk-free rate surprises. We show that (i) risk shifts capture the lion’s share of stock price movements around FOMC announcements; (ii) that they are accompanied by significant investor fund flows, suggesting that investors react heterogeneously to monetary policy news; and (iii) that price pressure amplifies the stock market response to monetary policy news. Our results imply that central bank information effects are overshadowed by short-term dynamics stemming from investor rebalancing activities and are likely to be more difficult to identify than previously thought.
Broad, long-term financial and economic datasets are a scarce resource, in particular in the European context. In this paper, we present an approach for an extensible, i.e. adaptable to future changes in technologies and sources, data model that may constitute a basis for digitized and structured long- term, historical datasets. The data model covers specific peculiarities of historical financial and economic data and is flexible enough to reach out for data of different types (quantitative as well as qualitative) from different historical sources, hence achieving extensibility. Furthermore, based on historical German company and stock market data, we discuss a relational implementation of this approach.
Der Einsatz von Künstliche Intelligenz (KI) – Technologien eröffnet viele Chancen, birgt aber auch viele Risiken – insbesondere in der Finanzbranche. Dieses Whitepaper gibt einen Überblick über den aktuellen Stand der Anwendung und Regulierung von KI-Technologien in der Finanzbranche, und diskutiert Chancen und Risiken von KI. KI findet in der Finanzbranche zahlreiche Anwendungsgebiete. Dazu gehören Chatbots, intelligente Assistenten für Kunden, automatischer Hochfrequenzhandel, automatisierte Betrugserkennung, Überwachung der Compliance, Gesichtserkennungssoftware zur Kundenidentifikation u. v. m. Auch Finanzaufsichtsbehörden setzen zunehmend KI-Anwendungen ein, um große und komplexe Datenmengen (Big Data) automatisiert und skalierbar auf Muster zu untersuchen und ihren Aufsichtspflichten nachzukommen.
Die Regulierung von KI in der Finanzbranche ist ein Balanceakt. Auf der einen Seite gibt es eine Notwendigkeit Flexibilität zu gewährleisten, um Innovationen nicht einzudämmen und im internationalen Wettbewerb nicht abgehängt zu werden. Strenge Auflagen können in diesem Zusammenhang als Barriere für die erfolgreiche Weiter-)Entwicklung von KI-Applikationen in der Finanzbranche wirken. Auf der anderen Seite müssen Persönlichkeitsrechte geschützt und Entscheidungsprozesse nachvollziehbar bleiben. Die fehlende Erklärbarkeit und Interpretierbarkeit von KI-Modellen entsteht in erster Linie durch Intransparenz bei einem Großteil heutiger KI-Anwendungen, bei welchen zwar die Natur der Ein- und Ausgaben beobachtbar und verständlich ist, nicht jedoch die genauen Verarbeitungsschritte dazwischen (Blackbox Prinzip).
Dieses Spannungsfeld zeigt sich auch im aktuellen regulatorischen Ansatz verschiedener Behörden. So werden einerseits die positiven Seiten von KI betont, wie Effizienz- und Effektivitätsgewinne sowie Rentabilitäts- und Qualitätssteigerungen (Bundesregierung, 2019) oder neue Methoden der Gefahrenanalyse in der Finanzmarktregulierung (BaFin, 2018a). Andererseits, wird darauf verwiesen, dass durch KI getroffene Entscheidungen immer von Menschen verantwortet werden müssen (EU Art. 22 DSGVO) und demokratische Rahmenbedingungen des Rechtsstaats zu wahren seien (FinTechRat, 2017).
Für die Zukunft sehen wir die Notwendigkeit internationale Regularien prinzipienbasiert, vereinheitlicht und technologieneutral weiterzuentwickeln, ohne dabei die Entwicklung neuer KIbasierter Geschäftsmodelle zu bremsen. Im globalen Wettstreit sollte Europa bei der Regulierung des KI-Einsatzes eine Vorreiterrolle einnehmen und damit seine demokratischen Werte der digitalen Freiheit, Selbstbestimmung und das Recht auf Information weltweit exportieren. Förderprogramme sollten einen stärkeren Fokus auf die Entwicklung nachhaltiger und verantwortungsvoller KI in Banken legen. Dazu zählt insbesondere die (Weiter-)Entwicklung breit einsetzbarer Methoden, die es erlauben, menschen-interpretierbare Erklärungen für erzeugte Ausgaben bereitzustellen und Problemen wie dem Blackbox Prinzip entgegenzuwirken.
Aus Sicht der Unternehmen in der Finanzbranche könnte eine Kooperation mit BigTech-Unternehmen sinnvoll sein, um gemeinsam das Potential der Technologie bestmöglich ausschöpfen zu können. Nützlich wäre auch ein gemeinsames semantisches Metadatenmodell zur Beschreibung der in der Finanzbranche anfallenden Daten. In Zukunft könnten künstliche Intelligenzen Daten aus sozialen Netzwerken berücksichtigen oder Smart Contracts aushandeln. Eine der größten Herausforderungen der Zukunft wird das Anwerben geeigneten Personals darstellen.
Although the elderly are more vulnerable to COVID-19, the empirical evidence suggests that they do not behave more cautiously in the pandemic than younger individuals. This theoretical model argues that some individuals might not comply with the COVID-19 measures to reassure themselves that they are not vulnerable, and that the incentives for such self-signaling can be stronger for the elderly. The results suggest that communication strategies emphasizing the dangers of COVID-19 could backfire and reduce compliance among the elderly.
We study risk taking in a panel of subjects in Wuhan, China - before, during the COVID-19 crisis, and after the country reopened. Subjects in our sample traveled for semester break in January, generating variation in exposure to the virus and quarantine in Wuhan. Higher exposure leads subjects to reduce planned risk taking, risky investments, and optimism. Our findings help unify existing studies by showing that aggregate shocks affect general preferences for risk and economic expectations, while heterogeneity in experience further affect risk taking through beliefs about individuals’ own outcomes such as luck and sense of control.
JEL Classification: G50, G51, G11, D14, G41
With the second wave of the Covid-19 pandemic in full swing, banks face a challenging environment. They will need to address disappointing results and adverse balance sheet restatements, the intensity of which depends on the evolution of the euro area economies. At the same time, vulnerable banks reinforce real economy deficiencies. The contribution of this paper is to provide a comparative assessment of the various policy responses to address a looming banking crisis. Such a crisis will fully materialize when non-performing assets drag down banks simultaneously, raising the specter of a full-blown systemic crisis. The policy responses available range from forbearance, recapitalization (with public or private resources), asset separation (bad banks, at national or EU level), to debt conversion schemes. We evaluate these responses according to a set of five criteria that define the efficacy of each. These responses are not mutually exclusive, in practice, as they have never been. They may also go hand in hand with other restructuring initiatives, including potential consolidation in the banking sector. Although we do not make a specific recommendation, we provide a framework for policymakers to guide them in their decision making.
This policy white paper shows, using data on European Commission (EC) lobby meetings, that financial institutions and finance trade associations have substantial access to EC policymakers. While lobbying could transfer policy-relevant information and expertise to policymakers, it could also result in the capture of policymakers by the industry, which could harm consumers and taxpayers. How could policymakers prevent regulatory capture, but retain the benefits of the sector expertise in policy decisions? Awareness of regulatory capture by policymakers is one of the most important remedies. This paper provides an overview of the origins of the regulatory capture theory and recent academic evidence. The paper shows that regulatory capture could emerge in a variety of institutions and policy areas but is not ubiquitous and depends on the incentives of policymakers and the policy environment. Subsequently, the paper discusses various measures to prevent regulatory capture, such as more transparency, diverse expert groups, and cooling-off periods.