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Advanced machine learning has achieved extraordinary success in recent years. “Active” operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the “known unknown” or even the “unknown unknown.” While machine learning has been tested successfully in the regime of the “known,” heuristics typically provide better results for an active operational risk management (in the sense of forecasting). However, precursors in existing data can open a chance for machine learning to provide early warnings even for the regime of the “unknown unknown.”
The current discussion about a “risk culture” in financial services was triggered by the recent series of financial crises. The last decade saw a long list of hubris, misconduct and criminal activities by human beings on a single or even a collective basis in banks, in the industry or in the whole economy. As a counter-reaction, financial authorities called for a guidance by a “new” risk culture in financial institutions based on a set of abstract, formal, and normative governance processes. While traditional risk research in economics and in banking was focused on the statistical aspects of risk as the probability of loss multiplied by the amount of loss, culture is a paraphrase for the behavior in collectives and dynamics of organization found in human societies. Therefore, a “risk culture” should link the normative concepts of risk with the positive “real-world” decision-making in financial services. This paper will describe a novel view on “risk culture” from the perspective of human beings interacting in dynamical and intertemporal commercial relations. In this context “risk” is perceived by economic agents ex−ante as the consequence of the time lag between the present and the uncertain future development (compared to a probability distribution calculated by observers ex−post). For all those individual decisions—to be made under uncertainty—future “risk” includes the so-called “normal accidents”, i.e., failures that will happen at some uncertain point in time but are inevitable, and the only questions are when failure will happen and how to maintain function in the first line of defense. Finally, the shift from an abstract definition of “risk” as a probability distribution to a role model of “honorable merchants” as a benchmark for significant individual decision-making with individual responsibilities for the uncertain future outcome provides a new framework to discuss the responsibilities in the financial industry.
SAFE Newsletter : 2018, Q4
(2018)
Higher capital ratios are believed to improve system-wide financial stability through three main channels: (i) higher loss-absorption capacity, (ii) lower moral hazard, (iii) stabilization of the financial cycle if capital ratios are increased during good times. We examine these mechanisms in a laboratory asset market experiment with indebted participants. We find support for the loss-absorption channel: higher capital ratios reduce the bankruptcy rate. However, we do not find support for the moral hazard channel. Higher capital ratios (insignificantly) increase asset price bubbles, an aggregate measure of excessive risk-taking. Additional evidence suggests that bankruptcy aversion explains this surprising result. Finally, the evidence supports the idea that higher capital ratios in good times stabilize the financial cycle.
Zum ersten Mal wurde in Deutschland eine groß angelegte wissenschaftliche Studie zur Machbarkeit und zum Nutzen einer säulenübergreifenden Renteninformationsplattform durchgeführt, unter realen Bedingungen und mit mehreren tausend Teilnehmern. Die beiden zentralen Ergebnisse sind, dass ein elektronisches Rentencockpit auch in Deutschland technisch machbar ist und beträchtlichen individuellen Zusatznutzen für die Bürgerinnen und Bürger stiften würde. Die Langfristanalysen der Pilotstudie zeigen, dass selbst die einmalige Schaffung von Rententransparenz für viele Teilnehmer Anlass genug ist, ihren Rentenplan zu überdenken und sich aktiv mit ihrer Altersvorsorge auseinanderzusetzen und ihr Verhalten zu ändern. Teilnehmer mit Zugang zu einem elektronischen Rentencockpit fühlen sich nach der Studie deutlich besser informiert und neigen dazu ihr Sparverhalten stärker anzupassen als Personen ohne Zugang. Die außerordentlich hohe Bereitschaft zur Teilnahme und die Antworten in den Online-Befragungen sind zudem Beleg für den großen Bedarf an systemgestützter, individueller Rententransparenz. Soll ein Rentencockpit Verbreitung in Deutschland finden, scheint eine automatisierte, elektronische Bereitstellung von Vertragsdaten von Seiten der Rententräger jedoch unabdingbar, da die eigenständige Suche und teilmanuelle Bereitstellung von Standmitteilungen für die meisten Studienteilnehmer ein großes Hindernis darstellt.
Much ado about nothing : a study of differential pricing and liquidity of short and long term bonds
(2018)
Are yields of long-maturity bonds distorted by demand pressure of clientele investors, regulatory effects, or default, flight-to-safety or liquidity premiums? Using data on German nominal bonds between 2005 and 2015, we study the differential pricing and liquidity of short and long maturity bonds. We find statistically significant, but economically negligible segmentation in yields and some degree of liquidity segmentation of short-term versus long-term bonds. These results have important policy implications for the e17.5 trillion European pension and insurance industries: long maturity bond yields seem appropriate for the valuation of long-term liabilities.
A number of recent studies have concluded that consumer spending patterns over the month are closely linked to the timing of income receipt. This correlation is interpreted as evidence of hyperbolic discounting. I re-examine patterns of spending in the diary sample of the U.S. Consumer Expenditure Survey, incorporating information on the timing of the main consumption commitment for most households - their monthly rent or mortgage payment. I find that non-durable and food spending increase with 30-48% on the day housing payments are made, with smaller increases in the days after. Moreover, households with weekly, biweekly and monthly income streams but the same timing of rent/mortgage payments have very similar consumption patterns. Exploiting variation in income, I find that households with extra liquidity decrease non-durable spending around housing payments, especially those households with a large budget share of housing.
Asset transaction prices sampled at high frequency are much staler than one might expect in the sense that they frequently lack new updates showing zero returns. In this paper, we propose a theoretical framework for formalizing this phenomenon. It hinges on the existence of a latent continuous-time stochastic process pt valued in the open interval (0; 1), which represents at any point in time the probability of the occurrence of a zero return. Using a standard infill asymptotic design, we develop an inferential theory for nonparametrically testing, the null hypothesis that pt is constant over one day. Under the alternative, which encompasses a semimartingale model for pt, we develop non-parametric inferential theory for the probability of staleness that includes the estimation of various integrated functionals of pt and its quadratic variation. Using a large dataset of stocks, we provide empirical evidence that the null of the constant probability of staleness is fairly rejected. We then show that the variability of pt is mainly driven by transaction volume and is almost unaffected by bid-ask spread and realized volatility.
Through the lens of market participants' objective to minimize counterparty risk, we provide an explanation for the reluctance to clear derivative trades in the absence of a central clearing obligation. We develop a comprehensive understanding of the benefits and potential pitfalls with respect to a single market participant's counterparty risk exposure when moving from a bilateral to a clearing architecture for derivative markets. Previous studies suggest that central clearing is beneficial for single market participants in the presence of a sufficiently large number of clearing members. We show that three elements can render central clearing harmful for a market participant's counterparty risk exposure regardless of the number of its counterparties: 1) correlation across and within derivative classes (i.e., systematic risk), 2) collateralization of derivative claims, and 3) loss sharing among clearing members. Our results have substantial implications for the design of derivatives markets, and highlight that recent central clearing reforms might not incentivize market participants to clear derivatives.