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Florian Weigert
Former Member
Title
Prof. Dr.
Last Name
Weigert
First name
Florian
Phone
+41 71 224 7014
21 results
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Item type:Publication, A Bayesian Stochastic Discount Factor for the Cross-Section of Individual Equity Options(2025-10-06); ; ; We utilize Bayesian model averaging to estimate a stochastic discount factor (SDF) for single-stock options. A Bayesian model averaging SDF outperforms reduced-form benchmark models in-sample and out-of-sample in pricing option return anomalies and portfolios. We document that the SDF is dense in characteristics with the impliedrealized volatility spread, option return momentum, and jump risk emerging as the most likely included factors. Noteworthy, we find that (i) our results remain largely robust after controlling for transaction costs and (ii) characteristics linked to behavioral biases gain in importance for options with high retail trading volume.Type:journal articleJournal:Journal of Financial and Quantitative AnalysisScopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Option Return Predictability with Machine Learning and Big Data(Oxford University Press, 2023-02); Drawing upon more than 12 million observations over the period from 1996 to 2020, we nd that allowing for nonlinearities signi cantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. The nonlinear machine learning models generate statistically and economically sizeable pro ts in the long-short portfolios of equity options even after accounting for transaction costs. Although option-based characteristics are the most important standalone predictors, stock-based measures o er substantial incremental predictive power when considered alongside option-based characteristics. Finally, we provide compelling evidence that option return predictability is driven by informational frictions and option mispricing.Type:journal articleJournal:Review of Financial StudiesVolume:36Issue:9Scopus© Citations 82 - Some of the metrics are blocked by yourconsent settings
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
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Item type:Publication, Crash Sensitivity and Cross-Section of Expected Stock ReturnsThis paper examines whether investors receive compensation for holding crash-sensitive stocks. We capture the crash sensitivity of stocks by their lower tail dependence (LTD) with the market based on copulas. We find that stocks with weak LTD serve as a hedge during crises, but, overall, stocks with strong LTD have higher average future returns. This effect cannot be explained by traditional risk factors and is different from the impact of beta, downside beta, coskewness, and cokurtosis. Our findings are consistent with results from the empirical option pricing literature and support the notion that investors are crash-averse.Type:journal articleJournal:Journal of Financial and Quantitative AnalysisVolume:53Issue:3Scopus© Citations 103 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Tail Risk in Hedge Funds : A Unique View from Portfolio HeldingsWe develop a new tail risk measure for hedge funds to examine the impact of tail risk on fund performance and to identify the sources of tail risk. We find that tail risk affects the cross-sectional variation in fund returns, and investments in both, tail-sensitive stocks as well as options, drive tail risk. Moreover, managerial incentives and discretion as well as exposure to funding liquidity shocks are important determinants of tail risk. We find evidence that is consistent with funds being able to time tail risk exposure prior to the recent financial crisis.Type:journal articleJournal:Journal of Financial EconomicsVolume:125Issue:3Scopus© Citations 109 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Does Foreign Information Predict the Returns of Multinational Firms Worldwide?We investigate whether value-relevant foreign information only gradually dilutes into stock prices of multinational firms worldwide. Using an international sample of firms from 22 developed countries, we find that a portfolio strategy based on firms' foreign sales information yields future returns of more than 10% p.a. globally. The return spread due to foreign information is substantial across different geographical regions and cannot be explained by traditional risk factors, firm characteristics, and industry momentum. Our results are in line with limited attention of investors being the main driver of this effect worldwide.Type:journal articleJournal:Review of FinanceVolume:21Issue:6Scopus© Citations 11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Does female management influence firm performance?
Evidence from Luxembourg banksType:journal articleJournal:Financial Markets and Portfolio ManagementVolume:30Issue:2Scopus© Citations 23 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Crash Aversion and the Cross-Section of Expected Stock Returns WorldwideThis paper examines whether investors receive compensation for holding stocks with a strong sensitivity to extreme market downturns in a sample covering forty countries. Worldwide, stocks with strong crash sensitivity deliver average returns of more than 7% p.a. higher than stocks with weak crash sensitivity. The effect is robust across geographical subsamples and is not explained by systematic risk factors and alternative firm characteristics. I show that the risk premium is particularly pronounced in countries that display negative market skewness, high income per capita, and rank high on Hofstede's individualism index.Type:journal articleJournal:The Review of Asset Pricing StudiesVolume:6Issue:1Scopus© Citations 28 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Empirical Analysis of Multivariate Copula ModelsType:journal articleJournal:Quantitative FinanceVolume:9/7
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