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We examine the relationship between household wealth and self-control. Although self-control has been linked to consumption and financial behavior, its measurement remains an open issue. We employ a definition of self-control failure that follows literature in psychology, suggesting that three factors can render self-control defective: lack of planning, lack of monitoring, and lack of commitment to pre-set plans. Our measure combines those three ingredients and can be computed using a standard representative survey. We find that self-control failure is strongly associated with different household net wealth measures and with self-assessed financial distress.
We present novel evidence on the value of cross-border political access. We analyze data on meetings of US multinational enterprises (MNEs) with European Commission (EC) policymakers. Meetings with Commissioners are associated with positive abnormal equity returns. We study channels of value creation through political access in the areas of regulation and taxation. US enterprises with EC meetings are more likely to receive favorable outcomes in their European merger decisions and have lower effective tax rates on foreign income than their peers without meetings. Our results suggest that access to foreign policymakers is of substantial value for MNEs.
Private equity fund managers are typically required to invest their own money alongside the fund. We examine how this coinvestment affects the acquisition strategy of leveraged buyout funds. In a simple model, where the investment and capital structure decisions are made simultaneously, we show that a higher coinvestment induces managers to chose less risky firms and use more leverage. We test these predictions in a unique sample of private equity investments in Norway, where the fund manager's taxable wealth is publicly available. Consistent with the model, portfolio company risk decreases and leverage ratios increase with the coinvestment fraction of the manager's wealth. Moreover, funds requiring a relatively high coinvestment tend to spread its capital over a larger number of portfolio firms, consistent with a more conservative investment policy.
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.
This paper studies the interactions between corporate law and VC exits by acquisitions, an increasingly common source of VC-related litigation. We find that transactions by VC funds under liquidity pressure are characterized by (i) a substantially lower sale price; (ii) a greater probability of industry outsiders as acquirers; (iii) a positive abnormal return for acquirers. These features indicate the existence of fire sales, which satisfy VCs' liquidation preferences but hurt common shareholders, leaving board members with conflicting fiduciary duties and litigation risks. Exploiting an important court ruling that establishes the board’s fiduciary duties to common shareholders as a priority, we find that after the ruling maturing VCs become less likely to exit by fire sales and they distribute cash to their investors less timely. However, VCs experience more difficult fundraising ex-ante, highlighting the potential cost of a common-favoring regime. Overall the evidence has important implications for optimal fiduciary duty design in VC-backed start-ups.
This paper documents that resource reallocation across firms is an important mechanism through which creditor rights affect real outcomes. I exploit the staggered adoption of an international convention that provides globally consistent strong creditor protection for aircraft finance. After this reform, country-level productivity in the aviation sector increases by 12%, driven mostly by across-firm reallocation. Productive airlines borrow more, expand, and adopt new technology at the expense of unproductive ones. Such reallocation is facilitated by (i) easier and quicker asset redeployment; and (ii) the influx of foreign financiers offering innovative financial products to improve credit allocative efficiency. I further document an increase in competition and an improvement in the breadth and the quality of products available to consumers.
Schätzwerte mittelfristiger Gleichgewichtszinsen mit der Methode nach Laubach und Williams (2003) werden inzwischen vielfach in der Diskussion um die Geld- und Fiskalpolitik zitiert. Unter anderem wurden sie von Summers (2014a) als Evidenz für eine säkulare Stagnation angeführt und von Yellen (2015) zur Rechtfertigung der Nullzinspolitik verwendet. In diesem Papier nehmen wir eine umfangreiche Untersuchung und Sensitivitätsanalyse dieser Schätzwerte für die Vereinigten Staaten, Deutschland und den Euro-Raum vor. Aufgrund der hohen Unsicherheit und Sensitivität, die mit den Schätzwerten mittelfristiger Gleichgewichtszinsen mit der Laubach-Williams-Methode und ähnlichen Ansätzen verbunden ist, sollten diese Schätzungen nicht den Ausschlag für entscheidende Weichenstellungen in der Geld- und Fiskalpolitik geben.
The currrent debate on monetary and fiscal policy is heavily influenced by estimates of the equilibrium real interest rate. Beyer and Wieland re-estimate the U.S. equilibrium rate with the methodology of Laubach and Williams and further modifications. They provide new estimates for the United States, the euro area and Germany and subject them to sensitivity tests. Beyer and Wieland conclude that due to the great uncertainty and sensitivity, the observed decline in the estimates is not a reliable indicator of a need for expansionary monetary and fiscal policy. Yet, if those estimates are employed to determine the appropriate monetary policy stance, such estimates are better used together with the consistent estimate of the level of potential output.
Empirical estimates of equilibrium real interest rates are so far mostly limited to advanced economies, since no statistical procedure suitable for a large set of countries is available. This is surprising, as equilibrium rates have strong policy implications in emerging markets and developing economies as well; current estimates of the global equilibrium rate rely on only a few countries; and estimates for a more diverse set of countries can improve understanding of the drivers. The authors propose a model and estimation strategy that decompose ex ante real interest rates into a permanent and transitory component even with short samples and high volatility. This is done with an unobserved component local level stochastic volatility model, which is used to estimate equilibrium rates for 50 countries with Bayesian methods.
Equilibrium rates were lower in emerging markets and developing economies than in advanced economies in the 1980s, similar in the 1990s, and have been higher since 2000. In line with economic integration and rising global capital markets, synchronization has been rising over time and is higher among advanced economies. Equilibrium rates of countries with stronger trade linkages and similar demographic and economic trends are more synchronized.
In crisis times, insurance companies might feel the pressure to present an investment portfolio performance that is superior to the market, since investment portfolios back the claims of policyholders and serve as a signal for the claims’ safety. I investigate how a stock market crisis as experienced over the course of the Covid-19 pandemic influences insurance firms’ decisions on the allocation of their corporate bond portfolio. I find that insurers shift their portfolio holdings towards lower credit risk assets as financial market conditions tighten. This tendency seems to be restricted by the liquidity risk of high-yield assets, and the credit risk of lower-rated investment grade assets. Both effects lead to an increase in the fraction of less liquid assets during the crash and the recovery.
In times of crisis, insurance companies may invest into riskier assets to benefit from expected price recoveries. Using daily stock market data for 34 European insurers, I investigate how a stock market contraction, as experienced during the Covid-19 pandemic, affects insurers’ decision on the allocation of their corporate bond portfolio. I find that insurers shift their portfolio holdings pro-cyclically towards lower credit risk assets in the first month of the market contraction. As the crisis progresses, I find evidence for counter-cyclical investment behavior by insurers, which can neither be explained by credit rating downgrades of held bonds nor by hedging with CDS derivatives. The observed counter-cyclical investment behavior of insurers could be beneficial for the financial system in attenuating price declines, but excessive risk-taking by insurance companies over longer periods can also reinforce stress in the system.
This paper utilizes a comprehensive worker-firm panel for the Netherlands to quantifythe impact of ICT capital-skill complementarity on the finance wage premium after the Global Financial Crisis. We apply additive worker and firm fixed-effect models to account for unobserved worker- and firm-heterogeneity and show that firm fixed-effects correct for a downward bias in the estimated finance wage premium. Our results indicate a sizable finance wage premium for both fixed- and full-hourly wages. The complementarity between ICT capital spending and the share of high skill workers at the firm-level reduces the full-wage premium considerably and the fixed-wage premium almost entirely.
We propose a shrinkage and selection methodology specifically designed for network inference using high dimensional data through a regularised linear regression model with Spike-and-Slab prior on the parameters. The approach extends the case where the error terms are heteroscedastic, by adding an ARCH-type equation through an approximate Expectation-Maximisation algorithm. The proposed model accounts for two sets of covariates. The first set contains predetermined variables which are not penalised in the model (i.e., the autoregressive component and common factors) while the second set of variables contains all the (lagged) financial institutions in the system, included with a given probability. The financial linkages are expressed in terms of inclusion probabilities resulting in a weighted directed network where the adjacency matrix is built “row by row". In the empirical application, we estimate the network over time using a rolling window approach on 1248 world financial firms (banks, insurances, brokers and other financial services) both active and dead from 29 December 2000 to 6 October 2017 at a weekly frequency. Findings show that over time the shape of the out degree distribution exhibits the typical behavior of financial stress indicators and represents a significant predictor of market returns at the first lag (one week) and the fourth lag (one month).
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.
Using German and US brokerage data we find that investors are more likely to sell speculative stocks trading at a gain. Investors’ gain realizations are monotonically increasing in a stock’s speculativeness. This translates into a high disposition effect for speculative and a much lower disposition effect for non-speculative stocks. Our findings hold across asset classes (stocks, passive, and active funds) and explain cross-sectional differences in investor selling behavior which previous literature attributed primarily to investor demographics. Our results are robust to rank or attention effects and can be linked to realization utility and rolling mental account.
A tale of one exchange and two order books : effects of fragmentation in the absence of competition
(2018)
Exchanges nowadays routinely operate multiple, almost identically structured limit order markets for the same security. We study the effects of such fragmentation on market performance using a dynamic model where agents trade strategically across two identically-organized limit order books. We show that fragmented markets, in equilibrium, offer higher welfare to intermediaries at the expense of investors with intrinsic trading motives, and lower liquidity than consolidated markets. Consistent with our theory, we document improvements in liquidity and lower profits for liquidity providers when Euronext, in 2009, consolidated its order ow for stocks traded across two country-specific and identically-organized order books into a single order book. Our results suggest that competition in market design, not fragmentation, drives previously documented improvements in market quality when new trading venues emerge; in the absence of such competition, market fragmentation is harmful.
Using granular supervisory data from Germany, we investigate the impact of unconventional monetary policies via central banks’ purchase of corporate bonds. While this policy results in a loosening of credit market conditions as intended by policy makers, we document two unintended side effects. First, banks that are more exposed to borrowers benefiting from the bond purchases now lend more to high-risk firms with no access to bond markets. Since more loan write-offs arise from these firms and banks are not compensated for this risk by higher interest rates, we document a drop in bank profitability. Second, the policy impacts the allocation of loans among industries. Affected banks reallocate loans from investment grade firms active on bond markets to mainly real estate firms without investment grade rating. Overall, our findings suggest that central banks’ quantitative easing via the corporate bond markets has the potential to contribute to both banking sector instability and real estate bubbles.
We investigate how unconventional monetary policy, via central banks’ purchases of corporate bonds, unfolds in credit-saturated markets. While this policy results in a loosening of credit market conditions as intended by policymakers, we report two unintended side effects. First, the policy impacts the allocation of credit among industries. Affected banks reallocate loans from investment-grade firms active on bond markets almost entirely to real estate asset managers. Other industries do not obtain more loans, particularly real estate developers and construction firms. We document an increase in real estate prices due to this policy, which fuels real estate overvaluation. Second, more loan write-offs arise from lending to these firms, and banks are not compensated for this risk by higher interest rates. We document a drop in bank profitability and, at the same time, a higher reliance on real estate collateral. Our findings suggest that central banks’ quantitative easing has substantial adverse effects in credit-saturated economies.
Climate risk has become a major concern for financial institutions and financial markets. Yet, climate policy is still in its infancy and contributes to increased uncertainty. For example, the lack of a sufficiently high carbon price and the variety of definitions for green activities lower the value of existing and new capital, and complicate risk management. This column argues that it would be welfare-enhancing if policy changes were to follow a predictable longer-term path. Accordingly, the authors suggest a role for financial regulation in the transition.
This paper investigates systemic risk in the insurance industry. We first analyze the systemic contribution of the insurance industry vis-à-vis other industries by applying 3 measures, namely the linear Granger causality test, conditional value at risk and marginal expected shortfall, on 3 groups, namely banks, insurers and non-financial companies listed in Europe over the last 14 years. We then analyze the determinants of the systemic risk contribution within the insurance industry by using balance sheet level data in a broader sample. Our evidence suggests that i) the insurance industry shows a persistent systemic relevance over time and plays a subordinate role in causing systemic risk compared to banks, and that ii) within the industry, those insurers which engage more in non-insurance-related activities tend to pose more systemic risk. In addition, we are among the first to provide empirical evidence on the role of diversification as potential determinant of systemic risk in the insurance industry. Finally, we confirm that size is also a significant driver of systemic risk, whereas price-to-book ratio and leverage display counterintuitive results.
During the last IAIS Global Seminar in June 2017, IAIS disclosed the agenda for a gradual shift in the systemic risk assessment methodology from the current Entity Based Approach (EBA) to a new Activity Based Approach(ABA). The EBA, which was developed in the aftermath of the 2008/2009 financial crisis, defines a list of Global Systemically Important Insurers (G-SIIs) based on a pre-defined set of criteria related to the size of the institution. These G-SIIs are subject to additional regulatory requirements since their distress or disorderly failure would potentially cause significant disruption to the global financial system and economic activity. Even if size is still a needed element of a systemic risk assessment, the strong emphasis put on the too-big-to-fail approach in insurance, i.e. EBA, might be partially missing the underlying nature of systemic risk in insurance. Not only certain activities, including insurance activities such as life or non-life lines of business, but also common exposures or certain managerial practices such as leverage or funding structures, tend to contribute to systemic risk of insurers but are not covered by the current EBA (Berdin and Sottocornola, 2015). Therefore, we very much welcome the general development of the systemic risk assessment methodology, even if several important questions still need to be answered.
This paper investigates systemic risk in the insurance industry. We first analyze the systemic contribution of the insurance industry vis-à-vis other industries by applying 3 measures, namely the linear Granger causality test, conditional value at risk and marginal expected shortfall, on 3 groups, namely banks, insurers and non-financial companies listed in Europe over the last 14 years. We then analyze the determinants of the systemic risk contribution within the insurance industry by using balance sheet level data in a broader sample. Our evidence suggests that i) the insurance industry shows a persistent systemic relevance over time and plays a subordinate role in causing systemic risk compared to banks, and that ii) within the industry, those insurers which engage more in non-insurance-related activities tend to pose more systemic risk. In addition, we are among the first to provide empirical evidence on the role of diversification as potential determinant of systemic risk in the insurance industry. Finally, we confirm that size is also a significant driver of systemic risk, whereas price-to-book ratio and leverage display counterintuitive results.
A stochastic forward-looking model to assess the profitability and solvency of european insurers
(2016)
In this paper, we develop an analytical framework for conducting forward-looking assessments of profitability and solvency of the main euro area insurance sectors. We model the balance sheet of an insurance company encompassing both life and non-life business and we calibrate it using country level data to make it representative of the major euro area insurance markets. Then, we project this representative balance sheet forward under stochastic capital markets, stochastic mortality developments and stochastic claims. The model highlights the potential threats to insurers solvency and profitability stemming from a sustained period of low interest rates particularly in those markets which are largely exposed to reinvestment risks due to the relatively high guarantees and generous profit participation schemes. The model also proves how the resilience of insurers to adverse financial developments heavily depends on the diversification of their business mix. Finally, the model identifies potential negative spillovers between life and non-life business thorugh the redistribution of capital within groups.
A stochastic forward-looking model to assess the profitability and solvency of European insurers
(2016)
In this paper, we develop an analytical framework for conducting forward-looking assessments of profitability and solvency of the main euro area insurance sectors. We model the balance sheet of an insurance company encompassing both life and non-life business and we calibrate it using country level data to make it representative of the major euro area insurance markets. Then, we project this representative balance sheet forward under stochastic capital markets, stochastic mortality developments and stochastic claims. The model highlights the potential threats to insurers solvency and profitability stemming from a sustained period of low interest rates particularly in those markets which are largely exposed to reinvestment risks due to the relatively high guarantees and generous profit participation schemes. The model also proves how the resilience of insurers to adverse financial developments heavily depends on the diversification of their business mix. Finally, the model identifies potential negative spillovers between life and non-life business thorugh the redistribution of capital within groups.
This paper investigates the effects of a rise in interest rate and lapse risk of endowment life insurance policies on the liquidity and solvency of life insurers. We model the book and market value balance sheet of an average German life insurer, subject to both GAAP and Solvency II regulation, featuring an existing back book of policies and an existing asset allocation calibrated by historical data. The balance sheet is then projected forward under stochastic financial markets. Lapse rates are modeled stochastically and depend on the granted guaranteed rate of return and prevailing level of interest rates. Our results suggest that in the case of a sharp increase in interest rates, policyholders sharply increase lapses and the solvency position of the insurer deteriorates in the short-run. This result is particularly driven by the interaction between a reduction in the market value of assets, large guarantees for existing policies, and a very slow adjustment of asset returns to interest rates. A sharp or gradual rise in interest rates is associated with substantial and persistent liquidity needs, that are particularly driven by lapse rates.
Low interest rates are becoming a threat to the stability of the life insurance industry, especially in countries such as Germany, where products with relatively high guaranteed returns sold in the past still represent a prominent share of the total portfolio. This contribution aims to assess and quantify the effects of the current low interest rate phase on the balance sheet of a representative German life insurer, given the current asset allocation and the outstanding liabilities. To do so, we generate a stochastic term structure of interest rates as well as stock market returns to simulate investment returns of a stylized life insurance business portfolio in a multi-period setting. Based on empirically calibrated parameters, we can observe the evolution of the life insurers' balance sheet over time with a special focus on their solvency situation. To account for different scenarios and in order to check the robustness of our findings, we calibrate different capital market settings and different initial situations of capital endowment. Our results suggest that a prolonged period of low interest rates would markedly affect the solvency situation of life insurers, leading to relatively high cumulative probability of default for less capitalized companies.
Low interest rates are becoming a threat to the stability of the life insurance industry, especially in countries such as Germany, where products with relatively high guaranteed returns sold in the past still represent a prominent share of the total portfolio. This contribution aims to assess and quantify the effects of the current low interest rate phase on the balance sheet of a representative German life insurer, given the current asset allocation and the outstanding liabilities. To do so, we generate a stochastic term structure of interest rates as well as stock market returns to simulate investment returns of a stylized life insurance business portfolio in a multi-period setting. Based on empirically calibrated parameters, we can observe the evolution of the life insurers’ balance sheet over time with a special focus on their solvency situation. To account for different scenarios and in order to check the robustness of our findings, we calibrate different capital market settings and different initial situations of capital endowment. Our results suggest that a prolonged period of low interest rates would markedly affect the solvency situation of life insurers, leading to a relatively high cumulative probability of default, especially for less capitalized companies. In addition, the new reform of the German life insurance regulation has a beneficial effect on the cumulative probability of default, as a direct consequence of the reduction of the payouts to policyholders.
In this paper I assess the effect of interest rate risk and longevity risk on the solvency position of a life insurer selling policies with minimum guaranteed rate of return, profit participation and annuitization option at maturity. The life insurer is assumed to be based in Germany and therefore subject to German regulation as well as to Solvency II regulation. The model features an existing back book of policies and an existing asset allocation calibrated on observed data, which are then projected forward under stochastic financial markets and stochastic mortality developments. Different scenarios are proposed, with particular focus on a prolonged period of low interest rates and strong reduction in mortality rates. Results suggest that interest rate risk is by far the greatest threat for life insurers, whereas longevity risk can be more easily mitigated and thereby is less detrimental. Introducing a dynamic demand for new policies, i.e. assuming that lower offered guarantees are less attractive to savers, show that a decreasing demand may even be beneficial for the insurer in a protracted period of low interest rates. Introducing stochastic annuitization rates, i.e. allowing for deviations from the expected annuitization rate, the solvency position of the life insurer worsen substantially. Also profitability strongly declines over time, casting doubts on the sustainability of traditional life business going forward with the low interest rate environment. In general, in the proposed framework it is possible to study the evolution over time of an existing book of policies when underlying financial market conditions and mortality developments drastically change. This feature could be of particular interest for regulatory and supervisory authorities within their financial stability mandate, who could better evaluate micro- and macro-prudential policy interventions in light of the persistent low interest rate environment.
This paper examines how networks of professional contacts contribute to the development of the careers of executives of North American and European companies. We build a dynamic model of career progression in which career moves may both depend upon existing networks and contribute to the development of future networks. We test the theory on an original dataset of nearly 73 000 executives in over 10 000 _rms. In principle professional networks could be relevant both because they are rewarded by the employer and because they facilitate job mobility. Our econometric analysis suggests that, although there is a substantial positive correlation between network size and executive compensation, with an elasticity of around 20%, almost all of this is due to unobserved individual characteristics. The true causal impact of networks on compensation is closer to an elasticity of 1 or 2% on average, all of this due to enhanced probability of moving to a higher-paid job. And there appear to be strongly diminishing returns to network size.
Coming early to the party
(2017)
We examine the strategic behavior of High Frequency Traders (HFTs) during the pre-opening phase and the opening auction of the NYSE-Euronext Paris exchange. HFTs actively participate, and profitably extract information from the order flow. They also post "flash crash" orders, to gain time priority. They make profits on their last-second orders; however, so do others, suggesting that there is no speed advantage. HFTs lead price discovery, and neither harm nor improve liquidity. They "come early to the party", and enjoy it (make profits); however, they also help others enjoy the party (improve market quality) and do not have privileges (their speed advantage is not crucial).
Do competition and incentives offered to designated market makers (DMMs) improve market liquidity? Using data from NYSE Euronext Paris, we show that an exogenous increase in competition among DMMs leads to a significant decrease in quoted and effective spreads, mainly through a reduction in adverse selection costs. In contrast, changes in incentives, through small changes in rebates and requirements for DMMs, do not have any tangible effect on market liquidity. Our results are of relevance for designing optimal contracts between exchanges and DMMs and for regulatory market oversight.
We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to market quality, defined by price discovery and liquidity provision, in the opening auction. We use a unique dataset from the Tokyo Stock Exchange (TSE) based on server-IDs and find that HFTs dynamically alter their presence in different stocks and on different days. In spite of the lack of immediate execution, about one quarter of HFTs participate in the pre-opening period, and contribute significantly to market quality in the pre-opening period, the opening auction that ensues and the continuous trading period. Their contribution is largely different from that of the other HFTs during the continuous period.
This paper analyses whether the post-crisis regulatory reforms developed by global-standard-setting bodies have created appropriate incentives for different types of market participants to centrally clear Over-The-Counter (OTC) derivative contracts. Beyond documenting the observed facts, we analyze four main drivers for the decision to clear: 1) the liquidity and riskiness of the reference entity; 2) the credit risk of the counterparty; 3) the clearing member’s portfolio net exposure with the Central Counterparty Clearing House (CCP) and 4) post trade transparency. We use confidential European trade repository data on single-name Sovereign Credit Derivative Swap (CDS) transactions, and show that for all the transactions reported in 2016 on Italian, German and French Sovereign CDS 48% were centrally cleared, 42% were not cleared despite being eligible for central clearing, while 9% of the contracts were not clearable because they did not satisfy certain CCP clearing criteria. However, there is a large difference between CCP clearing members that clear about 53% of their transactions and non-clearing members, even those that are subject to counterparty risk capital requirements, that almost never clear their trades. Moreover, we find that diverse factors explain clearing members’ decision to clear different CDS contracts: for Italian CDS, counterparty credit risk exposures matter most for the decision to clear, while for French and German CDS, margin costs are the most important factor for the decision. Clearing members use clearing to reduce their exposures to the CCP and largely clear contracts when at least one of the traders has a high counterparty credit risk.
This paper empirically analyses whether post-global financial crisis regulatory reforms have created appropriate incentives to voluntarily centrally clear over-the-counter (OTC) derivative contracts. We use confidential European trade repository data on single-name sovereign credit default swap (CDS) transactions and show that both seller and buyer manage counterparty exposures and capital costs, strategically choosing to clear when the counterparty is riskier. The clearing incentives seem particularly responsive to seller credit risk, which is in line with the notion that counterparty credit risk (CCR) is asymmetric in CDS contracts. The riskiness of the underlying reference entity also impacts the decision to clear as it affects both CCR capital charges for OTC contracts and central counterparty clearing house (CCP) margins for cleared contracts. Lastly, we find evidence that when a transaction helps netting positions with the CCP and hence lower margins, the likelihood of clearing is higher.
We show that High Frequency Traders (HFTs) are not beneficial to the stock market during flash crashes. They actually consume liquidity when it is most needed, even when they are rewarded by the exchange to provide immediacy. The behavior of HFTs exacerbate the transient price impact, unrelated to fundamentals, typically observed during a flash crash. Slow traders provide liquidity instead of HFTs, taking advantage of the discounted price. We thus uncover a trade-o↵ between the greater liquidity and efficiency provided by HFTs in normal times, and the disruptive consequences of their trading activity during distressed times.
This Paper gives an overview of the German banking system and current challenges it is facing. It starts with an overview of the so-called ‘Three-Pillar-Banking-System’ and a detailed description of the current structure of the banking system in Germany. A brief comparison of the banking system in Germany with the ones in other European countries points out its uniqueness. The consequences of the financial crisis of 2007/2008 and further challenges for the German banking system are discussed, as well as the the ongoing debate around the question whether the strong government involvement should be sustained.
In this paper we investigate the implications of providing loan officers with a compensation structure that rewards loan volume and penalizes poor performance versus a fixed wage unrelated to performance. We study detailed transaction information for more than 45,000 loans issued by 240 loan officers of a large commercial bank in Europe. We examine the three main activities that loan officers perform: monitoring, originating, and screening. We find that when the performance of their portfolio deteriorates, loan officers increase their effort to monitor existing borrowers, reduce loan origination, and approve a higher fraction of loan applications. These loans, however, are of above-average quality. Consistent with the theoretical literature on multitasking in incomplete contracts, we show that loan officers neglect activities that are not directly rewarded under the contract, but are in the interest of the bank. In addition, while the response by loan officers constitutes a rational response to a time allocation problem, their reaction to incentives appears myopic in other dimensions.
In this paper, we investigate how the introduction of complex, model-based capital regulation affected credit risk of financial institutions. Model-based regulation was meant to enhance the stability of the financial sector by making capital charges more sensitive to risk. Exploiting the staggered introduction of the model-based approach in Germany and the richness of our loan-level data set, we show that (1) internal risk estimates employed for regulatory purposes systematically underpredict actual default rates by 0.5 to 1 percentage points; (2) both default rates and loss rates are higher for loans that were originated under the model-based approach, while corresponding risk-weights are significantly lower; and (3) interest rates are higher for loans originated under the model-based approach, suggesting that banks were aware of the higher risk associated with these loans and priced them accordingly. Further, we document that large banks benefited from the reform as they experienced a reduction in capital charges and consequently expanded their lending at the expense of smaller banks that did not introduce the model-based approach. Counter to the stated objectives, the introduction of complex regulation adversely affected the credit risk of financial institutions. Overall, our results highlight the pitfalls of complex regulation and suggest that simpler rules may increase the efficacy of financial regulation.
In this paper, we investigate how the introduction of complex, model-based capital regulation affected credit risk of financial institutions. Model-based regulation was meant to enhance the stability of the financial sector by making capital charges more sensitive to risk. Exploiting the staggered introduction of the model-based approach in Germany and the richness of our loan-level data set, we show that (1) internal risk estimates employed for regulatory purposes systematically underpredict actual default rates by 0.5 to 1 percentage points; (2) both default rates and loss rates are higher for loans that were originated under the model-based approach, while corresponding risk-weights are significantly lower; and (3) interest rates are higher for loans originated under the model-based approach, suggesting that banks were aware of the higher risk associated with these loans and priced them accordingly. Further, we document that large banks benefited from the reform as they experienced a reduction in capital charges and consequently expanded their lending at the expense of smaller banks that did not introduce the model-based approach. Counter to the stated objectives, the introduction of complex regulation adversely affected the credit risk of financial institutions. Overall, our results highlight the pitfalls of complex regulation and suggest that simpler rules may increase the efficacy of financial regulation.
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 paper, we examine how the institutional design affects the outcome of bank bailout decisions. In the German savings bank sector, distress events can be resolved by local politicians or a state-level association. We show that decisions by local politicians with close links to the bank are distorted by personal considerations: While distress events per se are not related to the electoral cycle, the probability of local politicians injecting taxpayers’ money into a bank in distress is 30 percent lower in the year directly preceding an election. Using the electoral cycle as an instrument, we show that banks that are bailed out by local politicians experience less restructuring and perform considerably worse than banks that are supported by the savings bank association. Our findings illustrate that larger distance between banks and decision makers reduces distortions in the decision making process, which has implications for the design of bank regulation and supervision.
In this paper, we examine how the institutional design affects the outcome of bank bailout decisions. In the German savings bank sector, distress events can be resolved by local politicians or a state-level association. We show that decisions by local politicians with close links to the bank are distorted by personal considerations: While distress events per se are not related to the electoral cycle, the probability of local politicians injecting taxpayers’ money into a bank in distress is 30 percent lower in the year directly preceding an election. Using the electoral cycle as an instrument, we show that banks that are bailed out by local politicians experience less restructuring and perform considerably worse than banks that are supported by the savings bank association. Our findings illustrate that larger distance between banks and decision makers reduces distortions in the decision making process, which has implications for the design of bank regulation and supervision.
We investigate the default probability, recovery rates and loss distribution of a portfolio of securitised loans granted to Italian small and medium enterprises (SMEs). To this end, we use loan level data information provided by the European DataWarehouse platform and employ a logistic regression to estimate the company default probability. We include loan-level default probabilities and recovery rates to estimate the loss distribution of the underlying assets. We find that bank securitised loans are less risky, compared to the average bank lending to small and medium enterprises.
We investigate the default probability, recovery rates and loss distribution of a portfolio of securitised loans granted to Italian small and medium enterprises (SMEs). To this end, we use loan level data information provided by the European DataWarehouse platform and employ a logistic regression to estimate the company default probability. We include loan-level default probabilities and recovery rates to estimate the loss distribution of the underlying assets. We find that bank securitised loans are less risky, compared to the average bank lending to small and medium enterprises.
The great financial crisis and the euro area crisis led to a substantial reform of financial safety nets across Europe and – critically – to the introduction of supranational elements. Specifically, a supranational supervisor was established for the euro area, with discrete arrangements for supervisory competences and tasks depending on the systemic relevance of supervised credit institutions. A resolution mechanism was created to allow the frictionless resolution of large financial institutions. This resolution mechanism has been now complemented with a funding instrument.
While much more progress has been achieved than most observers could imagine 12 years ago, the banking union remains unfinished with important gaps and deficiencies. The experience over the past years, especially in the area of crisis management and resolution, has provided impetus for reform discussions, as reflected most lately in the Eurogroup statement of 16 June 2022.
This Policy Insight looks primarily at the current and the desired state of the banking union project. The key underlying question, and the focus here, is the level of ambition and how it is matched with effective legal and regulatory tools. Specifically, two questions will structure the discussions:
What would be a reasonable definition and rationale for a ‘complete’ banking union? And what legal reforms would be required to achieve it?
Banking union is a case of a new remit of EU-level policy that so far has been established on the basis of long pre-existing treaty stipulations, namely, Article 127(6) TFEU (for banking supervision) and Article 114 TFEU (for crisis management and deposit insurance). Could its completion be similarly carried out through secondary law? Or would a more comprehensive overhaul of the legal architecture be required to ensure legal certainty and legitimacy?
Since 2014 the ECB has implemented a massive expansion of monetary policy including large-scale asset purchases and negative policy rates. As the euro area economy has improved and inflation has risen, questions concerning the future normalization of monetary policy are starting to dominate the public debate.
The study argues that the ECB should develop a strategy for policy normalization and communicate it very soon to prepare the ground for subsequent steps towards tightening. It provides analysis and makes proposals concerning key aspects of this strategy. The aim is to facilitate the emergence of expectations among market participants that are consistent with a smooth process of policy normalization.
The global financial crisis (as well as the European sovereign debt crisis) has led to a substantial redesign of rules and institutions – aiming in particular at underwriting financial stability. At the same time, the crisis generated a renewed interest in properly appraising systemic financial vulnerabilities. Employing most recent data and applying a variety of largely only recently developed methods we provide an assessment of indicators of financial stability within the Euro Area. Taking a “functional” approach, we analyze comprehensively all financial intermediary activities, regardless of the institutional roof – banks or non-bank (shadow) banks – under which they are conducted. Our results reveal a declining role of banks (and a commensurate increase in non-bank banking). These structural shifts (between institutions) are coincident with regulatory and supervisory reforms (implemented or firmly anticipated) as well as a non-standard monetary policy environment. They might, unintendedly, actually imply a rise in systemic risk. Overall, however, our analyses suggest that financial imbalances have been reduced over the course of recent years. Hence, the financial intermediation sector has become more resilient. Nonetheless, existing (equity) buffers would probably not suffice to face substantial volatility shocks.
Non-bank (-balance sheet) based financial intermediation has become considerably more important over the last couple of decades. For the U.S., this trend has been discussed ever since the mid-1990s. As a consequence, traditional monetary transmission mechanisms, mainly operating through bank balance sheets, have apparently become less relevant. This in particular applies to the bank lending channel. Concurrently, recent theoretical and empirical work uncovered a "risk-taking channel" of monetary policy. This mechanism is not confined to traditional banks but has been found to operate also across the spectrum of financial intermediaries and intermediation devices, including securitization and collateralized lending/borrowing. In addition, recent empirical evidence suggests that the increasing importance of shadow-banking activities might have given rise to a so-called "waterbed effect". This is a mediating mechanisms, dampening or counteracting typically to be expected reactions to monetary policy impulses. Employing flow-of-funds data, we can document also for the Euro Area that a trend towards non-bank (not necessarily more 'market'-based) intermediation has occurred. This is, however, a fairly recent development, substantially weaker than in the U.S. Nonetheless, analyzing the response of Euro Area bank and nonbank financial intermediaries to monetary policy impulses, we find some notable behavioral differences between mainly deposit-funded and more 'market'-based financial intermediaries. We also detect, inter alia, the existence of a (still) fairly weak, but potentially policyrelevant, "waterbed" effect.
Euro area shadow banking activities in a low-interest-rate environment: a flow-of-funds perspective
(2016)
Very low policy rates as well as the substantial redesign of rules and supervisory institutions have changed background conditions for the Euro Area’s financial intermediary sector substantially. Both policy initiatives have been targeted at improving societal welfare. And their potential side effects (or costs) have been discussed intensively, in academic as well as policy circles. Very low policy rates (and correspondingly low market rates) are likely to whet investors’ risk taking incentives. Concurrently, the tightened regulatory framework, in particular for banks, increases the comparative attractiveness of the less regulated, so-called shadow banking sector. Employing flow-of-funds data for the Euro Area’s non-bank banking sector we take stock of recent developments in this part of the financial sector. In addition, we examine to which extent low interest rates have had an impact on investment behavior. Our results reveal a declining role of banks (and, simultaneously, an increase in non-bank banking). Overall intermediation activity, hence, has remained roughly at the same level. Moreover, our findings also suggest that non-bank banks have tended to take positions in riskier assets (particularly in equities). In line with this observation, balance-sheet based risk measures indicate a rise in sector-specific risks in the non-bank banking sector (when narrowly defined).
Die Studie untersucht die Frage, ob der Gesetzgeber des ARUG die Ziele erreicht hat, die mit der Reform des Rechts der Anfechtung von HVBeschlüssen verfolgt wurden. Darüber hinaus gehend soll die Entwicklung der Beschlußmängelklagen seit der letzten Studie der Verfasser hierzu nachgezeichnet werden. Unsere Studie zeigt, daß seit Inkrafttreten des ARUG ein deutlicher Rückgang der Beschlußmängelklagen und Freigabeverfahren zu verzeichnen ist. Dagegen ist der Anteil der von „Berufsklägern“ erhobenen Klagen und Nebeninterventionen gleich geblieben, wobei sich die Anzahl der Personen in der Gruppe der „Berufskläger“ nochmals vergrößert hat. Das ARUG hat insoweit keine erkennbare Wirkung gehabt...
Unternehmen und Ethik
(2010)
Die noch nicht völlig überwundene Finanzmarktkrise hat nicht nur den Gesetzgeber auf den Plan gerufen. Auch die Frage nach der Ethik der Akteure wird vielfach erörtert. Haben von Gier getriebene Finanzmarktakteure nicht nur Rechtsregeln, sondern auch ethische Normen, die Grundsätze des Wirtschaftens ehrbarer Kaufleute, gewissenlos beiseite geschoben, um sich zu bereichern? Wie läßt sich die Beachtung dieser Normen künftig sichern? Diese aktuelle Debatte soll Anlaß zu einigen allgemeineren Betrachtungen zum Thema „Unternehmen und Ethik“ sein.
Whatever it takes to understand a central banker : embedding their words using neural networks
(2023)
Dictionary approaches are at the forefront of current techniques for quantifying central bank communication. In this paper, the author propose a novel language model that is able to capture subtleties of messages such as one of the most famous sentences in central bank communications when ECB President Mario Draghi stated that "within [its] mandate, the ECB is ready to do whatever it takes to preserve the euro".
The authors utilize a text corpus that is unparalleled in size and diversity in the central bank communication literature, as well as introduce a novel approach to text quantication from computational linguistics. This allows them to provide high-quality central bank-specific textual representations and demonstrate their applicability by developing an index that tracks deviations in the Fed's communication towards inflation targeting. Their findings indicate that these deviations in communication significantly impact monetary policy actions, substantially reducing the reaction towards inflation deviation in the US.
High-frequency changes in interest rates around FOMC announcements are a standard method of measuring monetary policy shocks. However, some recent studies have documented puzzling effects of these shocks on private-sector forecasts of GDP, unemployment, or inflation that are opposite in sign to what standard macroeconomic models would predict. This evidence has been viewed as supportive of a „Fed information effect“ channel of monetary policy, whereby an FOMC tightening (easing) communicates that the economy is stronger (weaker) than the public had expected.
The authors show that these empirical results are also consistent with a „Fed response to news“ channel, in which incoming, publicly available economic news causes both the Fed to change monetary policy and the private sector to revise its forecasts. They provide substantial new evidence that distinguishes between these two channels and strongly favors the latter; for example, regressions that include the previously omitted public macroeconomic news, high-frequency stock market responses to Fed announcements, and a new survey that they conduct of individual Blue Chip forecasters all indicate that the Fed and private sector are simply responding to the same public news, and that there is little if any role for a „Fed information effect“.
The authors estimate perceptions about the Fed's monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions is time-varying and cyclical: high during tightening episodes but low during easings. Forecasters update their perceptions about the policy rule in response to monetary policy actions, measured by high-frequency interest rate surprises, suggesting that forecasters have imperfect information about the rule. The perceived rule impacts asset prices crucial for monetary policy transmission, driving how interest rates respond to macroeconomic news and explaining term premia in long-term interest rates.
Conditional yield skewness is an important summary statistic of the state of the economy. It exhibits pronounced variation over the business cycle and with the stance of monetary policy, and a tight relationship with the slope of the yield curve. Most importantly, variation in yield skewness has substantial forecasting power for future bond excess returns, high-frequency interest rate changes around FOMC announcements, and consensus survey forecast errors for the ten-year Treasury yield. The COVID pandemic did not disrupt these relations: historically high skewness correctly anticipated the run-up in long-term Treasury yields starting in late 2020. The connection between skewness, survey forecast errors, excess returns, and departures of yields from normality is consistent with a theoretical framework where one of the agents has biased beliefs.
Recent regulatory measures such as the European Union’s AI Act re-quire artificial intelligence (AI) systems to be explainable. As such, under-standing how explainability impacts human-AI interaction and pinpoint-ing the specific circumstances and groups affected, is imperative. In this study, we devise a formal framework and conduct an empirical investiga-tion involving real estate agents to explore the complex interplay between explainability of and delegation to AI systems. On an aggregate level, our findings indicate that real estate agents display a higher propensity to delegate apartment evaluations to an AI system when its workings are explainable, thereby surrendering control to the machine. However, at an individual level, we detect considerable heterogeneity. Agents possess-ing extensive domain knowledge are generally more inclined to delegate decisions to AI and minimize their effort when provided with explana-tions. Conversely, agents with limited domain knowledge only exhibit this behavior when explanations correspond with their preconceived no-tions regarding the relationship between apartment features and listing prices. Our results illustrate that the introduction of explainability in AI systems may transfer the decision-making control from humans to AI under the veil of transparency, which has notable implications for policy makers and practitioners that we discuss.
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.
Using experimental data from a comprehensive field study, we explore the causal effects of algorithmic discrimination on economic efficiency and social welfare. We harness economic, game-theoretic, and state-of-the-art machine learning concepts allowing us to overcome the central challenge of missing counterfactuals, which generally impedes assessing economic downstream consequences of algorithmic discrimination. This way, we are able to precisely quantify downstream efficiency and welfare ramifications, which provides us a unique opportunity to assess whether the introduction of an AI system is actually desirable. Our results highlight that AI systems’ capabilities in enhancing welfare critically depends on the degree of inherent algorithmic biases. While an unbiased system in our setting outperforms humans and creates substantial welfare gains, the positive impact steadily decreases and ultimately reverses the more biased an AI system becomes. We show that this relation is particularly concerning in selective-labels environments, i.e., settings where outcomes are only observed if decision-makers take a particular action so that the data is selectively labeled, because commonly used technical performance metrics like the precision measure are prone to be deceptive. Finally, our results depict that continued learning, by creating feedback loops, can remedy algorithmic discrimination and associated negative effects over time.
Advances in Machine Learning (ML) led organizations to increasingly implement predictive decision aids intended to improve employees’ decision-making performance. While such systems improve organizational efficiency in many contexts, they might be a double-edged sword when there is the danger of a system discontinuance. Following cognitive theories, the provision of ML-based predictions can adversely affect the development of decision-making skills that come to light when people lose access to the system. The purpose of this study is to put this assertion to the test. Using a novel experiment specifically tailored to deal with organizational obstacles and endogeneity concerns, we show that the initial provision of ML decision aids can latently prevent the development of decision-making skills which later becomes apparent when the system gets discontinued. We also find that the degree to which individuals 'blindly' trust observed predictions determines the ultimate performance drop in the post-discontinuance phase. Our results suggest that making it clear to people that ML decision aids are imperfect can have its benefits especially if there is a reasonable danger of (temporary) system discontinuances.
In current discussions on large language models (LLMs) such as GPT, understanding their ability to emulate facets of human intelligence stands central. Using behavioral economic paradigms and structural models, we investigate GPT’s cooperativeness in human interactions and assess its rational goal-oriented behavior. We discover that GPT cooperates more than humans and has overly optimistic expectations about human cooperation. Intriguingly, additional analyses reveal that GPT’s behavior isn’t random; it displays a level of goal-oriented rationality surpassing human counterparts. Our findings suggest that GPT hyper-rationally aims to maximize social welfare, coupled with a strive of self-preservation. Methodologically, our esearch highlights how structural models, typically employed to decipher human behavior, can illuminate the rationality and goal-orientation of LLMs. This opens a compelling path for future research into the intricate rationality of sophisticated, yet enigmatic artificial agents.
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.
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.
How does group identity affect belief formation? To address this question, we conduct a series of online experiments with a representative sample of individuals in the US. Using the setting of the 2020 US presidential election, we find evidence of intergroup preference across three distinct components of the belief formation cycle: a biased prior belief, avoid-ance of outgroup information sources, and a belief-updating process that places greater (less) weight on prior (new) information. We further find that an intervention reducing the salience of information sources decreases outgroup information avoidance by 50%. In a social learn-ing context in wave 2, we find participants place 33% more weight on ingroup than outgroup guesses. Through two waves of interventions, we identify source utility as the mechanism driving group effects in belief formation. Our analyses indicate that our observed effects are driven by groupy participants who exhibit stable and consistent intergroup preferences in both allocation decisions and belief formation across all three waves. These results suggest that policymakers could reduce the salience of group and partisan identity associated with a policy to decrease outgroup information avoidance and increase policy uptake.
Using a novel experimental design, I test how the exposure to information about a group’s relative performance causally affects the members’ level of identification and thereby their propensity to harm affiliates of comparison groups. I find that both, being informed about a high and poor relative performance of the ingroup similarly fosters identification. Stronger ingroup identification creates increased hostility against the group of comparison. In cases where participants learn about poor relative performance, there appears to be a direct level effect additionally elevating hostile discrimination. My findings shed light on a specific channel through which social media may contribute to intergroup fragmentation and polarization.
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.
Sehen sich Banken mit Engpässen auf einem Finanzierungsmarkt konfrontiert, weichen sie auf andere Finanzierungsquellen aus, was den Wettbewerb verschärft: Banken, die nicht direkt vom eigentlichen Finanzierungsengpass betroffen sind, können ebenso davon erfasst werden, was sich stark auf die Realwirtschaft auswirkt.
We examine how a firms' investment behavior affects the investment of a neighboring firm. Economic theory yields ambiguous predictions regarding the direction of firm peer effects and consistent with earlier work, we find that firms display similar investment behavior within an area using OLS analysis. Exploiting time-variation in the rise of U.S. states' corporate income taxes and utilizing heterogeneity in firms' exposure to increases in corporate income tax rates, we identify the causal impact of local firms' investments. Using this as an instrumental variable in a 2SLS estimation, we find that an increases in local firms' investment reduces the investment of a local peer firm. This effect is more pronounced if local competition among firms is stronger and supports theories that firm investments are strategic substitutes due to competition.
What are the aggregate and distributional consequences of the relationship be-tween an individual’s social network and financial decisions? Motivated by several well-documented facts about the influence of social connections on financial decisions, we build and calibrate a model of stock market participation with a social network that emphasizes the interplay between connectivity and network structure. Since connections to informed agents help spread information, there is a pivotal role for factors that determine sorting among agents. An increase in the average number of connections raises the average participation rate, mostly due to richer agents. A higher degree of sorting benefits richer agents by creating clusters where information spreads more efficiently. We show empirical evidence consistent with the importance of connectivity and sorting. We discuss several new avenues for future research into the aggregate impact of peer effects in finance.
Peer effects can lead to better financial outcomes or help propagate financial mistakes across social networks. Using unique data on peer relationships and portfolio composition, we show considerable overlap in investment portfolios when an investor recommends their brokerage to a peer. We argue that this is strong evidence of peer effects and show that peer effects lead to better portfolio quality. Peers become more likely to invest in funds when their recommenders also invest, improving portfolio diversification compared to the average investor and various placebo counterfactuals. Our evidence suggests that social networks can provide good advice in settings where individuals are personally connected.
Liquidity derivatives
(2022)
It is well established that investors price market liquidity risk. Yet, there exists no financial claim contingent on liquidity. We propose a contract to hedge uncertainty over future transaction costs, detailing potential buyers and sellers. Introducing liquidity derivatives in Brunnermeier and Pedersen (2009) improves financial stability by mitigating liquidity spirals. We simulate liquidity option prices for a panel of NYSE stocks spanning 2000 to 2020 by fitting a stochastic process to their bid-ask spreads. These contracts reduce the exposure to liquidity factors. Their prices provide a novel illiquidity measure refllecting cross-sectional commonalities. Finally, stock returns significantly spread along simulated prices.
Industry classification groups firms into finer partitions to help investments and empirical analysis. To overcome the well-documented limitations of existing industry definitions, like their stale nature and coarse categories for firms with multiple operations, we employ a clustering approach on 69 firm characteristics and allocate companies to novel economic sectors maximizing the within-group explained variation. Such sectors are dynamic yet stable, and represent a superior investment set compared to standard classification schemes for portfolio optimization and for trading strategies based on within-industry mean-reversion, which give rise to a latent risk factor significantly priced in the cross-section. We provide a new metric to quantify feature importance for clustering methods, finding that size drives differences across classical industries while book-to-market and financial liquidity variables matter for clustering-based sectors.
We investigate the relationship between anchoring and the emergence of bubbles in experimental asset markets. We show that setting a visual anchor at the fundamental value (FV) in the first period only is sufficient to eliminate or to significantly reduce bubbles in laboratory asset markets. If no FV-anchor is set, bubble-crash patterns emerge. Our results indicate that bubbles in laboratory environments are primarily sparked in the first period. If prices are initiated around the FV, they stay close to the FV over the entire trading horizon. Our insights can be related to initial public offerings and the interaction between prices set on pre-opening markets and subsequent intra-day price dynamics.
We investigate the relationship between anchoring and the emergence of bubbles in experimental asset markets. We show that setting a visual anchor at the fundamental value (FV) in the first period only is sufficient to eliminate or to significantly reduce bubbles in laboratory asset markets. If no FV-anchor is set, bubble-crash patterns emerge. Our results indicate that bubbles in laboratory environments are primarily sparked in the first period. If prices are initiated around the FV, they stay close to the FV over the entire trading horizon. Our insights can be related to initial public offerings and the interaction between prices set on pre-opening markets and subsequent intra-day price dynamics.
Do markets correct individual behavioral biases? In an experimental asset market, we compare the outcomes of a standard market economy to those of a an island economy that removed market interactions. We observe asset price bubbles in the market economy while prices are stable in the island economy. We also find that subjects took more risk following larger losses, resulting in larger prices and consistent with a gambling for resurrection motive. This motive can translate into bubbles in the market economy because higher prices increase average losses and thus reinforce the desire to resurrect. By contrast, the absence of such a strategic complementarity in island economies can explain the more stable outcome. These results suggest that markets do not correct behavioral biases, rather the contrary.
Previous research has documented strong peer effects in risk taking, but little is known about how such social influences affect market outcomes. The consequences of social interactions are hard to isolate in financial data, and theoretically it is not clear whether peer effects should increase or decrease risk sharing. We design an experimental asset market with multiple risky assets and study how exogenous variation in real-time information about the portfolios of peer group members affects aggregate and individual risk taking. We find that peer information ameliorates under-diversification that occurs in a market without such information. One reason is that peer information increases risk aversion and induces a concern for relative income position that may reduce or amplify risk taking, depending on whether the context highlights the most or least successful trader. Thus, contrary to conventional wisdom, we show that social interactions may help to reduce earnings volatility in financial markets, and we discuss implications for institutional design.
In an experimental setting in which investors can entrust their money to traders, we investigate how compensation schemes affect liquidity provision and asset prices. Investors face a trade-off between risk and return. At the benefit of a potentially higher return, they can entrust their money to a trader. However this investment is risky, as the trader might not be trustworthy. Alternatively, they can opt for a safe but low return. We study how subjects solve this trade-off when traders are either liable for losses or not, and when their bonuses are either capped or not. Limited liability introduces a conflict of interest because it makes traders value the asset more than investors. To limit losses, investors should thus restrict liquidity provision to force traders to trade at a lower price. By contrast, bonus caps make traders value the asset less than investors. This should encourage liquidity provision and decrease prices. In contrast to these predictions, we find that under limited liability investors contribute to asset price bubbles by increasing liquidity provision and that caps fail to tame bubbles. Overall, giving investors skin in the game fosters financial stability.
Flows of funds run by banks or by firms that belong to the same financial group as a bank are less volatile and less sensitive to bad past performance. This enables bank-affiliated funds to better weather distress and to hold lower precautionary cash buffers in comparison with their unaffiliated peers. Banks provide liquidity support to distressed affiliated funds by buying shares of those funds that are experiencing large outflows. This, in turn, diminishes the severity of strategic complementarities in investors’ redemptions. Liquidity support and other benefits of bank affiliation are conditional on the financial health of the parent company. Distress in the banking system spills over to the mutual fund sector via ownership links. Our research high-lights substantial dependencies between the banking system and the asset management industry, and identifies an important channel via which financial stability risks depend on the organisational structure of the financial sector.
This paper analyzes the current implementation status of sustainability and taxonomy-aligned disclosure under the Sustainable Finance Disclosure Regulation (SFDR) as well as the development of the SFDR categorization of funds offered via banks in Germany. Examining data provided by WM Group, which consists of more than 10,000 investment funds and 2,000 index funds between September 2022 and March 2023, we have observed a significant proportion of Article 9 (dark green) funds transitioning to Article 8 (light green) funds, particularly among index funds. As a consequence of this process, the profile of the SFDR classes has sharpened, which reflects an increased share of sustainable investments in the group of Article 9 funds. When differentiating between environmental and social investments, the share of environmental investments increased, but the share of social investments decreased in the group of Article 9 funds at the beginning of 2023. The share of taxonomy-aligned investments is very low, but slightly increasing for Article 9 funds. However, by March 2023 only around 1,000 funds have reported their sustainability proportions and this picture might change due to legal changes which require all funds in the scope of the SFDR to report these proportions in their annual reports being published after 1 January 2023.
We study self- and cross-excitation of shocks in the Eurozone sovereign CDS market. We adopt a multivariate setting with credit default intensities driven by mutually exciting jump processes, to capture the salient features observed in the data, in particular, the clustering of high default probabilities both in time (over days) and in space (across countries). The feedback between jump events and the intensity of these jumps is the key element of the model. We derive closed-form formulae for CDS prices, and estimate the model by matching theoretical prices to their empirical counterparts. We find evidence of self-excitation and asymmetric cross-excitation. Using impulse-response analysis, we assess the impact of shocks and a potential policy intervention not just on a single country under scrutiny but also, through the effect on cross-excitation risk which generates systemic sovereign risk, on other interconnected countries.
Reforms or bankruptcy?
(2011)
Almost 20 Greek academic economists from renowned universities in Europe and the US have prepared a one-page statement regarding the Greek crisis. In their statement the economic experts call upon the Greek public to accept the economic program of structural reforms, privatization, efficient tax collection, and shrinking of the public sector proposed and financed by the EU partners and the IMF. Among the signatories are this year's Nobel Prize winner Christopher Pissarides and Michalis Haliassos, Director of the Center for Financial Studies and Professor for Macroeconomics and Finance at the House of Finance.
The paper compares provision of public infrastructure via public-private partnerships (PPPs) with provision under government management. Due to soft budget constraints of government management, PPPs exert more effort and therefore have a cost advantage in building infrastructure. At the same time, hard budget constraints for PPPs introduce a bankruptcy risk and bankruptcy costs. Consequently, if bankruptcy costs are high, PPPs may be less efficient than public management, although this does not result from PPPs’ higher interest costs.
Governments, economists and intellectuals have called for common European bonds or increased own EU funds to address the recession induced by Covid19. Unfortunately, the German government, joined by the other members of the “Frugal Four” (Austria, Finland, the Netherlands), has categorically rejected to look into any such measures and favours using the ESM. This reaction created a déjà vu experience for citizens and governments of the heavily affected southern Member States of the EU. The proposal to use the ESM raises fears of another wave of austerity amounting to yet another lost decade for economic, social, and ecological development in Europe.
The case for corona bonds
(2020)
Corona bonds are feasible and important to preserve the European project. We set out a number of principles that might serve as a blueprint for the European institutions. Importantly, Corona bonds could be issued through a new public law entity and include all the safeguards required for the protection of the fundamental values of the EU. This proposal is pragmatic in the sense that it facilitates the choice European leaders have to make now; necessary to secure the resilience of the European Union. The political risks are significantly higher now than in 2010. The gargantuan challenge of tackling the combined impact of climate change, migration, digitalization, geopolitical shifts, and the spread of autocracy, requires leadership and joint action by the Council and the Eurogroup.
Cryptocurrencies provide a unique opportunity to identify how derivatives impact spot markets. They are fully fungible, trade across multiple spot exchanges at different prices, and futures contracts were selectively introduced on bitcoin (BTC) exchange rates against the USD in December 2017. Following the futures introduction, we find a significantly greater increase in cross-exchange price synchronicity for BTC--USD relative to other exchange rate pairs, as demonstrated by an increase in price correlations and a reduction in arbitrage opportunities and volatility. We also find support for an increase in price efficiency, market quality, and liquidity. The evidence suggests that futures contracts allowed investors to circumvent trading frictions associated with short sale constraints, arbitrage risk associated with block confirmation time, and market segmentation. Overall, our analysis supports the view that the introduction of BTC--USD futures was beneficial to the bitcoin spot market by making the underlying prices more informative.
Abundant studies show that individuals often struggle and frequently fail to form a correct perception of how much they are worth in terms of income or net wealth, both in absolute terms and relative to others. The authors find that wealth misperception arises even in a frictionless environment. They show that this wealth misperception is related to low cognitive abilities and inattention, and that subjects who misperceive wealth have a greater tendency to borrow and spend out of gains. A standard optimal consumption choice model, enriched with a rational but inattentive agent à la Gabaix aligns the key experimental findings.
The complexities of geopolitical events, financial and fiscal crises, and the ebb and flow of personal life circumstances can weigh heavily on individuals’ minds as they make critical economic decisions. To investigate the impact of cognitive load on such decisions, the authors conducted an incentivized online experiment involving a representative sample of 2,000 French households. The results revealed that exposure to a taxing and persistent cognitive load significantly reduced consumption, particularly for individuals under the threat of furlough, while simultaneously increasing their account balances, particularly for those not facing such employment uncertainty. These effects were not driven by supply constraints or a worsening of credit constraints. Instead, cognitive load primarily affected the optimality of the chosen policy rules and impaired the ability of the standard economic model to accurately predict consumption patterns, although this effect was less pronounced among college-educated subjects
We consider the continuous-time portfolio optimization problem of an investor with constant relative risk aversion who maximizes expected utility of terminal wealth. The risky asset follows a jump-diffusion model with a diffusion state variable. We propose an approximation method that replaces the jumps by a diffusion and solve the resulting problem analytically. Furthermore, we provide explicit bounds on the true optimal strategy and the relative wealth equivalent loss that do not rely on quantities known only in the true model. We apply our method to a calibrated affine model. Our findings are threefold: Jumps matter more, i.e. our approximation is less accurate, if (i) the expected jump size or (ii) the jump intensity is large. Fixing the average impact of jumps, we find that (iii) rare, but severe jumps matter more than frequent, but small jumps.
We design, field and exploit survey data from a representative sample of the French population to examine whether informative social interactions enter householdsístockholding decisions. Respondents report perceptions about their circle of peers with whom they interact about Önancial matters, their social circle and the population. We provide evidence for the presence of an information channel through which social interactions ináuence perceptions and expectations about stock returns, and financial behavior. We also find evidence of mindless imitation of peers in the outer social circle, but this does not permeate as many layers of financial behavior as informative social interactions do.
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.