Sustainable Architecture for Finance in Europe (SAFE)
Refine
Year of publication
- 2021 (57) (remove)
Document Type
- Working Paper (57)
Has Fulltext
- yes (57)
Is part of the Bibliography
- no (57)
Keywords
- ESG (6)
- COVID-19 (4)
- Covid-19 (4)
- Green Finance (3)
- Sustainability (3)
- BRRD (2)
- Bank Capitalization (2)
- Bank Resolution (2)
- Climate Change (2)
- ETFs (2)
- Expectations (2)
- Forbearance (2)
- Non-performing Loans (2)
- Taxonomy (2)
- ambiguity (2)
- climate change (2)
- corporate governance (2)
- green finance (2)
- volatility (2)
- 401(k) plan (1)
- Activism (1)
- Activist Hedge Fund (1)
- Algorithmic transparency (1)
- Altersversorgung (1)
- Antitrust (1)
- Asset Management Companies (1)
- BaFin (1)
- Bank Bailout (1)
- Bank Recapitalization (1)
- Bank Supervision (1)
- Bankenunion (1)
- Banking Union (1)
- Belief up-dating (1)
- Beliefs (1)
- Board Appointments (1)
- Bond risk premia (1)
- Brexit (1)
- C corporations (1)
- Capital Purchase Program (1)
- Centrality (1)
- China (1)
- Consumer Welfare (1)
- Contractarian Model of Corporate Law (1)
- Corporate Social Responsibility (1)
- Crisis Management (1)
- DCC-GARCH (1)
- DSGE models (1)
- Deposit Insurance (1)
- Dictionary (1)
- Digitalisierung (1)
- Digitalized Markets (1)
- Disposition Effect (1)
- Dividend Payments (1)
- ESG Rating Agencies (1)
- Economic Governance (1)
- Equity Premium (1)
- Experiences (1)
- Explainable machine learning (1)
- Financial Crises (1)
- Financial Crisis (1)
- Financial Market Cycles (1)
- Financial Stability (1)
- Finanzstabilität (1)
- Fiscal theory of the price level (1)
- Formative experiences (1)
- Fund Flows (1)
- Gender Gap (1)
- Government debt (1)
- Granger Causality (1)
- High Frequency Data (1)
- High-frequency event study (1)
- Hong test (1)
- Household Finance (1)
- Index Funds (1)
- Information processing (1)
- International Finance (1)
- Investor Protection (1)
- Investor sentiment (1)
- Kapitalmarktunion (1)
- Klimawandel (1)
- LSTM neural networks (1)
- Lobbying (1)
- Machine learning (1)
- Mandatory Law (1)
- Market Efficiency (1)
- Market efficiency (1)
- Monetary Policy Surprises (1)
- NLP (1)
- Nachhaltigkeit (1)
- Network theory (1)
- Nonlinear solution methods (1)
- Obfuscation (1)
- Offenlegungspflichten (1)
- Oil market (1)
- Perceptions (1)
- Plaintiff Lawyers (1)
- Portfolio Rebalancing (1)
- Portfolio choice (1)
- Price Competition (1)
- Price Pressures (1)
- Private Equity (1)
- Public financial news (1)
- Quid-pro-quo Mechanism (1)
- Rational Inattention (1)
- Regulatory Capture (1)
- Regulierung (1)
- Resolution (1)
- Responsible investment (1)
- Retail Investor (1)
- Risk taking (1)
- S corporations (1)
- S&P 500 (1)
- Secondary Loan Markets (1)
- Social Conditioning (1)
- Social media (1)
- Socially responsible investing (1)
- Soziale Marktwirtschaft (1)
- Stock market (1)
- Supervisory Relief Measures (1)
- Sustainable Finance (1)
- Sustainable Investments (1)
- TARP (1)
- Tax Cuts and Jobs Act (1)
- Transparency (1)
- Twitter (1)
- Wirecard (1)
- XAI (1)
- age (1)
- ambiguity premium (1)
- anomalies (1)
- asset pricing (1)
- bank (1)
- banks (1)
- behavioral economics (1)
- belief effect (1)
- belief estimation (1)
- belief updating (1)
- benchmarks (1)
- bid-ask spread (1)
- bilateral investment treaties (1)
- bubbles (1)
- call auctions (1)
- capital markets (1)
- central banks (1)
- climate risk (1)
- compliance behavior (1)
- confirmatory biases (1)
- consumer protection (1)
- corporate taxation (1)
- credence goods (1)
- cross-border institutions (1)
- demographischer Wandel (1)
- designated market makers (1)
- discrimination (1)
- earnings management (1)
- employees (1)
- endogenous information acquisition (1)
- erm structure of interest rates (1)
- executive labor market (1)
- factor timing (1)
- financial advice (1)
- financial market (1)
- financial risk-taking (1)
- financing (1)
- fintech (1)
- globalization (1)
- health (1)
- honesty (1)
- household finance (1)
- household finance (1)
- income distribution (1)
- innovation (1)
- institutional investors (1)
- investment biases (1)
- investor behavior (1)
- investor preferences (1)
- investor segmentation (1)
- labels (1)
- laboratory experiment (1)
- laboratory experiments (1)
- lending (1)
- life cycle saving (1)
- lottery-type assets (1)
- mandatory disclosure (1)
- marginal propensity to consume (1)
- market discipline (1)
- market price (1)
- market-based (1)
- measure of ambiguity (1)
- media polarization (1)
- monetary policy (1)
- motivated beliefs (1)
- net zero transition (1)
- option prices (1)
- patents (1)
- persistence (1)
- private Vermögensbildung (1)
- protected values (1)
- racial inequality (1)
- retirement (1)
- saving (1)
- sentiment (1)
- shareholder activism (1)
- source dependence (1)
- spillover effects (1)
- staatliche Sozialversicherung (1)
- stock market crisis (1)
- supervision (1)
- sustainability (1)
- sustainable finance (1)
- tax cut (1)
- tax intervention (1)
- tax policy (1)
- taxonomies (1)
- technology diffusion (1)
- time series momentum (1)
- trading activity (1)
- trend chasing (1)
- valuation ratios (1)
- wealth distribution (1)
- wealth effects (1)
- workforce (1)
- financial literacy (1)
Institute
- House of Finance (HoF) (57) (remove)
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.