SAFE working paper
https://safe-frankfurt.de/de/publikationen/working-papers.html
Refine
Year of publication
- 2021 (31) (remove)
Document Type
- Working Paper (31)
Language
- English (31) (remove)
Has Fulltext
- yes (31)
Is part of the Bibliography
- no (31)
Keywords
- COVID-19 (4)
- ESG (4)
- ETFs (2)
- ambiguity (2)
- climate change (2)
- green finance (2)
- volatility (2)
- Algorithmic transparency (1)
- Bank Bailout (1)
- Bank Recapitalization (1)
Institute
- Center for Financial Studies (CFS) (31) (remove)
314
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.
322
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.
321
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.
318
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.
315
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.
305
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.
304
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.
301
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
309
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.
324
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.
323
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.
329
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.
307
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.
317
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.
312
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.
300
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.
325
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.
306
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.
303
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.
302
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.