Markus Huggenberger
Title
Prof. Dr.
Last Name
Huggenberger
First name
Markus
Email
markus.huggenberger@unisg.ch
ORCID
Phone
+41 71 224 7962
13 results
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Item type:Publication, Multivariate crash risk(2022); This paper investigates whether multivariate crash risk (MCRASH), defined as exposure to extreme realizations of multiple systematic factors, is priced in the cross-section of expected stock returns. We derive an extended linear model with a positive premium for MCRASH, and we empirically confirm that stocks with high MCRASH earn significantly higher future returns than stocks with low MCRASH. The premium is not explained by linear factor exposures, alternative downside risk measures, or stock characteristics. Extending market-based definitions of crash risk to other well-established factors helps to determine the cross-section of expected stock returns without further expanding the factor zoo.Type:journal articleJournal:Journal of Financial EconomicsVolume:145Issue:1Scopus© Citations 24 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Risk pooling and solvency regulation: A policyholder's perspective(2022-12); Albrecht, PeterType:journal articleJournal:Journal of Risk and InsuranceVolume:89Issue:4Scopus© Citations 4 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The fundamental theorem of mutual insuranceThe essence of mutual insurance is the notion that re-distributing risk in a pool of risks is more beneficial than taking the risk alone. Interpreting ‘more beneficial’ as an increase in utility and considering sequences of exchangeable risks, we are able to formalize this notion from the policyholder’s perspective and demonstrate its validity for various alternative preference functionals (e.g., expected utility, Choquet expected utility, and distortion risk measures). To obtain this result, we exploit that for a sequence of exchangeable risks the corresponding sequence of arithmetical averages is a reversed martingale. We conclude that pooling risks is fundamental for understanding the mechanisms of insurance because it favourably affects the utility of policyholders, and we refer to this phenomenon as the ‘utility-improving effect of risk pooling’. Moreover, we demonstrate that the utility of the policyholder is (strictly) increasing with the size of the risk poolType:journal articleJournal:Insurance: Mathematics and EconomicsVolume:75Scopus© Citations 19 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Cost of Capital Estimates for Insurance Stocks with Jump Risk Premia: Evidence from U.S. Life and P&C Insurers(2026-07-28); ; We estimate the cost of capital of insurance companies based on a high-frequency factor model that captures jump risk and time-varying factor loadings. Using a large panel of intraday returns, we obtain cost of equity estimates for U.S. property and casualty (P&C) insurers and life insurers over the period 2004 to 2020. We find that P&C and life insurers exhibit markedly different continuous and jump risk exposures, reflecting differences in their business models. We confirm prior findings that P&C insurers’ cost of equity is below the U.S. market average. In contrast, the evidence for life insurers is mixed. While cost of equity estimates for life insurers are higher when using traditional specifications based on the market factor alone, the estimates decrease markedly when additional risk factors and jump components are included. Overall, our findings suggest that cost of capital estimates for insurance companies should take systematic jump risk exposure into account.Type:conference paper - Some of the metrics are blocked by yourconsent settings
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Item type:Publication, Stochastic Dominance and Financial Pricing in Peer-to-Peer Insurance(2025-06); Type:conference contribution - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Stochastic Dominance and Financial Pricing in Peer-to-Peer Insurance(2025-03); Type:conference contribution