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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.
Life insurance convexity
(2021)
Life insurers massively sell savings contracts with surrender options which allow policyholders to withdraw a guaranteed amount before maturity. These options move toward the money when interest rates rise. Using data on German life insurers, we estimate that a 1 percentage point increase in interest rates raises surrender rates by 17 basis points. We quantify the resulting liquidity risk in a calibrated model of surrender decisions and insurance cash flows. Simulations predict that surrender options can force insurers to sell up to 3% of their assets, depressing asset prices by 90 basis points. The effect is amplified by the duration of insurers' investments, and its impact on the term structure of interest rates depends on life insurers' investment strategy.
Macro-finance theory predicts that financial fragility builds up when volatility is low. This “volatility paradox’” challenges traditional systemic risk measures. I explore a new dimension of systemic risk, spillover persistence, which is the average time horizon at which a firm’s losses increase future risk in the financial system. Using firm-level data covering more than 30 years and 50 countries, I document that persistence declines when fragility builds up: before crises, during stock market booms, and when banks take more risks. In contrast, persistence increases with loss amplification: during crises and fire sales. These findings support key predictions of recent macrofinance models.
The paper analyses the contagion channels of the European financial system through the stochastic block model (SBM). The model groups homogeneous connectivity patterns among the financial institutions and describes the shock transmission mechanisms of the financial networks in a compact way. We analyse the global financial crisis and European sovereign debt crisis and show that the network exhibits a strong community structure with two main blocks acting as shock spreader and receiver, respectively. Moreover, we provide evidence of the prominent role played by insurances in the spread of systemic risk in both crises. Finally, we demonstrate that policy interventions focused on institutions with inter-community linkages (community bridges) are more effective than the ones based on the classical connectedness measures and represents consequently, a better early warning indicator in predicting future financial losses.
This paper examines the relationship between oil movements and systemic risk of financial institution in major petroleum-based economies. We estimate ΔCoVaR for those institutions and observe the presence of elevated increases in its levels corresponding to the subprime and global financial crises. The results provide evidence in favor of risk measurement improvements by accounting for oil returns in the risk functions. The spread between the standard CoVaR and the CoVaR that includes oil absorbs in a time range longer than the duration of the oil shock. This indicates that the drop in the oil price has a longer effect on risk and requires more time to be discounted by the financial institutions. To support the analysis, we consider also the other major market-based systemic risk measures.
A counterparty credit limit (CCL) is a limit imposed by a financial institution to cap its maximum possible exposure to a specified counterparty. Although CCLs are designed to help institutions mitigate counterparty risk by selective diversification of their exposures, their implementation restricts the liquidity that institutions can access in an otherwise centralized pool. We address the question of how this mechanism impacts trade prices and volatility, both empirically and via a new model of trading with CCLs. We find empirically that CCLs cause little impact on trade. However, our model highlights that in extreme situations, CCLs could serve to destabilize prices and thereby influence systemic risk.
We provide a comprehensive analysis of the determinants of trading in the sovereign credit default swaps (CDS) market, using weekly data for single-name sovereign CDS from October 2008 to September 2015. We describe the anatomy of the sovereign CDS market, derive a law of motion for gross positions and their components, and identify the key factors that drive the cross-sectional and time-series properties of trading volume and net notional amounts outstanding. While a single principal component accounts for 54 percent of the variation in sovereign CDS spreads, the largest common factor explains only 7 percent of the variation in sovereign CDS net notional amounts outstanding. Moreover, unlike for CDS spreads, common global factors explain very little of the variation in sovereign CDS trading and net notional amounts outstanding, suggesting that it is driven primarily by idiosyncratic country risk. We analyze several local and regional channels that may explain the trading in sovereign CDS: (a) country-specific credit risk shocks, including changes in a country's credit rating and related outlook changes, (b) the announcement and issuance of domestic and international debt, (c) macroeconomic sentiment derived from conventional and unconventional monetary policy, macro-economic news and shocks, and (d) regulatory channels, such as changes in bank capital adequacy requirements. All our findings suggest that sovereign CDS are more likely used for hedging than for speculative purposes.
Understanding the shift from micro to macro-prudential thinking: a discursive network analysis
(2016)
While some economists argued for macro-prudential regulation pre-crisis, the macro-prudential approach and its emphasis on endogenously created systemic risk have only gained prominence post-crisis. Employing discourse and network analysis on samples of the most cited scholarly works on banking regulation as well as on systemic risk (60 sources each) from 1985 to 2014, we analyze the shift from micro to macro-prudential thinking in the shift to the post crisis period. Our analysis demonstrates that the predominance of formalism, particularly, partial equilibrium analysis along with the exclusion of historical and practitioners’ styles of reasoning from banking regulatory studies impeded economists from engaging seriously with the endogenous sources of systemic risk prior to the crisis. Post-crisis, these topics became important in this discourse, but the epistemological failures of banking regulatory studies pre-crisis were not sufficiently recognized. Recent attempts to conceptualize and price systemic risk as a negative externality point to the persistence of formalism and equilibrium thinking, with its attending dangers of incremental innovation due to epistemological barriers constrains theoretical progress, by excluding observed phenomena, which cannot yet be accommodated in mathematical models.
Common systemic risk measures focus on the instantaneous occurrence of triggering and systemic events. However, systemic events may also occur with a time-lag to the triggering event. To study this contagion period and the resulting persistence of institutions' systemic risk we develop and employ the Conditional Shortfall Probability (CoSP), which is the likelihood that a systemic market event occurs with a specific time-lag to the triggering event. Based on CoSP we propose two aggregate systemic risk measures, namely the Aggregate Excess CoSP and the CoSP-weighted time-lag, that reflect the systemic risk aggregated over time and average time-lag of an institution's triggering event, respectively. Our empirical results show that 15% of the financial companies in our sample are significantly systemically important with respect to the financial sector, while 27% of the financial companies are significantly systemically important with respect to the American non-financial sector. Still, the aggregate systemic risk of systemically important institutions is larger with respect to the financial market than with respect to non-financial markets. Moreover, the aggregate systemic risk of insurance companies is similar to the systemic risk of banks, while insurers are also exposed to the largest aggregate systemic risk among the financial sector.
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.
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.
In this paper we develop empirical measures for the strength of spillover effects. Modifying and extending the framework by Diebold and Yilmaz (2011), we quantify spillovers between sovereign credit markets and banks in the euro area. Spillovers are estimated recursively from a vector autoregressive model of daily CDS spread changes, with exogenous common factors. We account for interdependencies between sovereign and bank CDS spreads and we derive generalised impulse response functions. Specifically, we assess the systemic effect of an unexpected shock to the creditworthiness of a particular sovereign or country-specific bank index to other sovereign or bank CDSs between October 2009 and July 2012. Channels of transmission from or to sovereigns and banks are aggregated as a Contagion index (CI). This index is disentangled into four components, the average potential spillover: i) amongst sovereigns, ii) amongst banks, iii) from sovereigns to banks, and iv) vice-versa. We highlight the impact of policy-related events along the different components of the contagion index. The systemic contribution of each sovereign or banking group is quantified as the net spillover weight in the total net-spillover measure. Finally, the captured time-varying interdependence between banks and sovereigns emphasises the evolution of their strong nexus.