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The pricing of digital art
(2023)
The intersection of recent advancements in generative artificial intelligence and blockchain technology has propelled digital art into the spotlight. Digital art pricing recognizes that owners derive utility beyond the artwork’s inherent value. We incorporate the consumption utility associated with digital art and model the stochastic discount factor and risk premiums. Furthermore, we conduct a calibration analysis to analyze the effects of shifts in the real and digital economy. Higher returns are required in a digital market upswing due to increased exposure to systematic risk and digital art prices are especially responsive to fluctuations in business cycles within digital markets.
This paper documents that the bond investments of insurance companies transmit shocks from insurance markets to the real economy. Liquidity windfalls from household insurance purchases increase insurers' demand for corporate bonds. Exploiting the fact that insurers persistently invest in a small subset of firms for identification, I show that these increases in bond demand raise bond prices and lower firms' funding costs. In response, firms issue more bonds, especially when their bond underwriters are well connected with investors. Firms use the proceeds to raise investment rather than equity payouts. The results emphasize the significant impact of investor demand on firms' financing and investment activities.
European insurers are allowed to make discretionary decisions in the calculation of Solvency II capital requirements. These choices include the design of risk models (ranging from a standard formula to a full internal model) and the use of long-term guarantees measures. This article examines the impact and the drivers of discretionary decisions with respect to capital requirements for market risks. In a first step of our analysis, we assess the risk profiles of 49 stock insurers using daily market data. In a second step, we exploit hand-collected Solvency II data for the years 2016 to 2020. We find that long-term guarantees measures substantially influence the reported solvency ratios. The measures are chosen particularly by less solvent insurers and firms with high interest rate and credit spread sensitivities. Internal models are used more frequently by large insurers and especially for risks for which the firms have already found adequate immunization strategies.
Gradient capital allocation, also known as Euler allocation, is a technique used to redistribute diversified capital requirements among different segments of a portfolio. The method is commonly employed to identify dominant risks, assessing the risk-adjusted profitability of segments, and installing limit systems. However, capital allocation can be misleading in all these applications because it only accounts for the current portfolio composition and ignores how diversification effects may change with a portfolio restructuring. This paper proposes enhancing the gradient capital allocation by adding “orthogonal convexity scenarios” (OCS). OCS identify risk concentrations that potentially drive portfolio risk and become relevant after restructuring. OCS have strong ties with principal component analysis (PCA), but they are a more general concept and compatible with common empirical patterns of risk drivers being fat-tailed and increasingly dependent in market downturns. We illustrate possible applications of OCS in terms of risk communication and risk limits.
Most insurers in the European Union determine their regulatory capital requirements based on the standard formula of Solvency II. However, there is evidence that the standard formula inaccurately reflects insurers’ risk situation and may provide misleading steering incentives. In the second pillar, Solvency II requires insurers to perform a so-called “Own Risk and Solvency Assessment” (ORSA). In their ORSA, insurers must establish their own risk measurement approaches, including those based on scenarios, in order to derive suitable risk assessments and address shortcomings of the standard formula. The idea of this paper is to identify scenarios in such a way that the standard formula in connection with the ORSA provides a reliable basis for risk management decisions. Using an innovative method for scenario identification, our approach allows for a simple but relatively precise assessment of marginal and even non-marginal portfolio changes. We numerically evaluate the proposed approach in the context of market risk employing an internal model from the academic literature and the Solvency Capital Requirement (SCR) calculation under Solvency II.
Testing frequency and severity risk under various information regimes and implications in insurance
(2023)
We build on Peter et al. (2017) who examined the benefit of testing frequency risk under various information regimes. We first consider testing only severity risk, and whether the principle of indemnity, i.e. the usual contract term that excludes claims payments above the resulting insured loss, affects the insurance contracts offered and purchased. Under information regimes which are less restrictive (in terms of obtaining and using customer information), it is possible for the insurer to offer different contracts for tested and untested individuals. In the absence of the principle of indemnity, individuals will test their severity risk and a separating equilibrium ensues. With the principle of indemnity, given an actuarially fair pooled contract, individuals will not test for severity under less restrictive information regimes; a pooling equilibrium thus ensues. Under more restrictive information regimes, the insurer offers separating contracts. Individuals will test for severity and purchase appropriate contracts. We also consider testing for both frequency and severity risk. The results here are more varied. The highest gain in efficiency from testing results from one of the more restrictive information regimes. Generally under all information regimes, there is a greater gain in efficiency without the principle of indemnity than with the principle of indemnity.
Life insurance convexity
(2023)
Life insurers sell savings contracts with surrender options, which allow policyholders to prematurely receive guaranteed surrender values. These surrender options move toward the money when interest rates rise. Hence, higher interest rates raise surrender rates, as we document empirically by exploiting plausibly exogenous variation in monetary policy. Using a calibrated model, we then estimate that surrender options would force insurers to sell up to 2% of their investments during an enduring interest rate rise of 25 bps per year. We show that these fire sales are fueled by surrender value guarantees and insurers’ long-term investments.
Between 2016 and 2022, life insurers in several European countries experienced negative longterm interest rates, which put pressure on their business models. The aim of this paper is to empirically investigate the impact of negative interest rates on the stock performance of life insurers. To measure the sensitivities, I estimate the level, slope, and curvature of the yield curve using the Nelson-Siegel model and empirical proxies. Panel regressions show that the effect of changes in the level is up to three times greater in a negative interest rate environment than in a positive one. Thus, a 1ppt decline in long-term interest rates reduces the stock returns of European life insurers by up to 10ppt when interest rates are below 0%. I also show that the relationship between the level and the sensitivity to interest rates is convex, and that life insurers benefit from rising interest rates across all maturity types.
Central clearing counterparties (CCPs) were established to mitigate default losses resulting from counterparty risk in derivatives markets. In a parsimonious model, we show that clearing benefits are distributed unevenly across market participants. Loss sharing rules determine who wins or loses from clearing. Current rules disproportionately benefit market participants with flat portfolios. Instead, those with directional portfolios are relatively worse off, consistent with their reluctance to voluntarily use central clearing. Alternative loss sharing rules can address cross-sectional disparities in clearing benefits. However, we show that CCPs may favor current rules to maximize fee income, with externalities on clearing participation.
Der Beitrag bietet eine Einführung in das Thema „Vertrauen als Topos der Plattformregulierung“. Dazu wird in einem ersten Schritt das allgemeine Verhältnis zwischen dem sozialen Tatbestand „Vertrauen“ und dem Recht als das einer komplementären, wechselseitigen Wirkungsverstärkung beschrieben. Im Hinblick auf die vertrauensfördernde Rolle des Rechts wird in einem zweiten Schritt zwischen der Funktion des Vertrauens bzw. der Vertrauenswürdigkeit als Tatbestandselement einer Vorschrift und den hieran geknüpften Rechtsfolgen unterschieden. Auf der Basis dieser Grundlagen gibt der Aufsatz in einem dritten Schritt einen Überblick über Bezugnahmen auf „Vertrauen“ in der deutschen und europäischen Plattformregulierung seit 2015. Hierzu zählen sektorale Regelungen gegen Hasskriminalität und Desinformation sowie zum Schutz des Urheberrechts, die 2022 in den horizontal angelegten Digital Services Act mündeten, der ein insgesamt „vertrauenswürdiges Online-Umfeld“ gewährleisten soll. Viertens stellt der Beitrag ein abstrakt-analytisches Konzept des Vertrauens vor, das sich gut zur Analyse der aufgezählten Vertrauensbeziehungen und ihrer rechtlichen Regelungen eignet. Ein abschließender Ausblick deutet die Proliferation des Vertrauenstopos als Ausdruck einer Vertrauenskrise im digitalen Zeitalter. Die erstrebte Vertrauenswürdigkeit des Online-Umfelds bildet ein normatives Minimum, das über gesetzliche Verhaltenspflichten und Privilegien für vertrauenswürdige Akteure der Zivilgesellschaft erreicht werden soll. Ob dies gelingt und überhaupt wünschenswert ist, ist freilich offen. Die juristische Auseinandersetzung mit dem Topos des Vertrauens in der Digital- und Plattformregulierung hat gerade erst begonnen.