Matthias Reginald Fengler
Title
Prof. Dr.
Last Name
Fengler
First name
Matthias Reginald
Email
matthias.fengler@unisg.ch
ORCID
Phone
+41 71 224 2457
62 results
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Item type:Publication, A Non-Gaussian, Structure-Preserving Stochastic Volatility and Option Pricing Model in Discrete Time(Oxford University Press (OUP), 2026-03-20); ; Melnikov, AlexanderWe propose a novel stochastic volatility model based on the autoregressive gamma process that accommodates a structure-preserving change to the risk-neutral measure while relying on a non-Gaussian distribution for the return innovations. The model employs the Meixner (MXN) distribution, which enriches the return dynamics with conditional stochastic skewness and kurtosis. We propose a fast and accurate estimation method by combining the approximate maximum likelihood method of David S. Bates with a numerical integration technique suitable for highly oscillatory functions. We derive a closed-form discrete-time option pricing formula. The MXN model performs particularly well, compared to benchmarks within its class and of the generalized autoregressive conditional heteroskedasticity family, when calibrated directly to option data and when applied to option data with a high level of implied volatility, such as Bitcoin.Type:journal articleJournal:Journal of Financial EconometricsVolume:24Issue:2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Locally Adaptive Modeling of Unconditional HeteroskedasticityWe study local change point detection in variance using generalized likelihood ratio tests. Building on [24], we utilize the multiplier bootstrap to approximate the unknown, non-asymptotic distribution of the test statistic and introduce a multiplicative bias correction that improves upon the existing additive version. This proposed correction offers a clearer interpretation of the bootstrap estimators while significantly reducing computational costs. Simulation results demonstrate that our method performs comparably to the original approach. We apply it to the growth rates of U.S. inflation, industrial production, and Bitcoin returns.Type:journal articleJournal:The New England Journal of Statistics in Data Science - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Structural Volatility Impulse Response Analysis(2025-01-31); We make three contributions to the volatility impulse response function (VIRF) developed by Hafner and Herwartz (2006). First, we derive its law for multivariate GARCH models of the BEKK type. Second, we present a structural embedding of the VIRF, leveraging recent advancements in the identification of multivariate generalized autoregressive conditional heteroskedasticity models. Third, we show how to endow the VIRF with a causal interpretation. We illustrate the merits of a structural VIRF analysis by investigating the impacts of historical and out-of-sample shock scenarios on the U.S. equity, government bond, and foreign exchange markets.Type:journal articleJournal:Journal of Financial EconometricsScopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Unveiling themes in 10-K disclosures: A new topic modeling perspective(2025-07); Type:journal articleJournal:International Review of Financial AnalysisScopus© Citations 3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Consumer spending in Switzerland: insights from a novel transactional data index(Springer Science and Business Media LLC, 2025-12-30); ; ; Robert RohrkemperWe analyze transactional payment data to study consumption expenditure patterns in Switzerland. The high-frequency nature of the data enables credible identification of expenditure changes both across and within weeks, which is essential for business decisions and economic policy analysis. We construct a consumer spending index that is granular across regions and broad product categories, allowing for consistent analysis over multiple years. Using data starting in 2018, we demonstrate the index’s potential to (i) reveal expenditure patterns relevant for strategic decisions by businesses and consumers across weekdays and categories, and (ii) identify economically and statistically significant short-term effects of monetary policy shocks.Type:journal articleJournal:Swiss Journal of Economics and StatisticsVolume:161Issue:1Scopus© Citations 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Monitoring consumption Switzerland: data, background, and use cases(Springer Open, 2023-03-20); ; ; Lalive, RafaelType:journal articleJournal:Swiss Journal of Economics and StatisticsVolume:159:4Issue:2023Scopus© Citations 7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Measuring spot variance spillovers when (co)variances are time-varying – the case of multivariate GARCH modelsIn highly integrated markets, news spreads at a fast pace and bedevils risk monitoring and optimal asset allocation. We therefore propose global and disaggregated measures of variance transmission that allow one to assess spillovers locally in time. Key to our approach is the vector ARMA representation of the second-order dynamics of the popular BEKK model. In an empirical application to a four-dimensional system of US asset classes – equity, fixed income, foreign exchange and commodities – we illustrate the second-order transmissions at various levels of (dis)aggregation. Moreover, we demonstrate that the proposed spillover indices are informative on the value-at-risk violations of portfolios composed of the considered asset classesType:journal articleJournal:Oxford bulletin of economics and statisticsVolume:80Issue:1Scopus© Citations 9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, GARCH option pricing models with Meixner innovationsType:journal articleJournal:Review of Derivatives ResearchIssue:21Scopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Managing Risk with a Realized Copula ParameterA dynamic copula model is introduced, in which the copula structure is inferred from the realized covariance matrix estimated from within-day high-frequency data. The estimation is carried out in a method-of-moments fashion using Hoeding's lemma. Applying this procedure day by day gives rise to a time series of daily copula parameters which can be approximated by an autoregressive time series model. This allows one to capture time-varying dependence. In an application to portfolio risk-management, it is found that this time-varying realized copula model exhibits very good forecasting properties for the one-day ahead value at risk. The working paper version of this paper ("Realized Copula") is found on http://www1.vwa.unisg.ch/RePEc/usg/econwp/EWP-1214.pdfType:journal articleJournal:Computational Statistics & Data AnalysisVolume:100Scopus© Citations 21 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency dataAs a means of validating an option pricing model, we compare the ex-post intra-day realized variance of options with the realized variance of the associated underlying asset that would be implied using assumptions as in the Black and Scholes (BS) model, the Heston and the Bates model. Based on data for the S&P 500 index, we find that the BS model is strongly directionally biased due to the presence of stochastic volatility. The Heston model reduces the mismatch in realized variance between the two markets, but deviations are still significant. With the exception of short-dated options, we achieve best approximations after controlling for the presence of jumps in the underlying dynamics. Finally, we provide evidence that, although heavily biased, the realized variance based on the BS model contains relevant predictive information that can be exploited when option high-frequency data is not available.Type:journal articleJournal:Journal of Banking and FinanceVolume:61Scopus© Citations 7