Markus Bibinger
Biographic Data
| ID | 8921407 |
|---|---|
| NAME | Markus Bibinger |
| GIVEN NAMES | Markus |
| FAMILY NAME | Bibinger |
| SIGNATURE | BIBINGER M |
| AFFILIATIONS | Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Straße 6, D-35032 Marburg, Germany () |
| ORCID | 0000-0001-8313-2460 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Modeling and Forecasting Realized Volatility with Multivariate Fractional Brownian Motion
A multivariate fractional Brownian motion (mfBm) with component-wise Hurst exponents is used to model and forecast realized volatility (RV). We investigate the interplay between correlation coefficients and Hurst exponents and propose a novel method to estimate model parameters, establishing its consistency and asymptotic normality. Additionally, we develop a time-reversibility test, which is typically not rejected by RV data. When the data gener…
Estimating the Spot Covariation of Asset Prices—Statistical Theory and Empirical Evidence
We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semimartingale log asset price process, which is subject to noise and nonsynchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM), which recently has been introduced by Bibinger et al.. We prove consistency and a point-wi…
No prominent works on this page.
Estimating the Spot Covariation of Asset Prices—Statistical Theory and Empirical Evidence
We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semimartingale log asset price process, which is subject to noise and nonsynchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM), which recently has been introduced by Bibinger et al.. We prove consistency and a point-wi…
Modeling and Forecasting Realized Volatility with Multivariate Fractional Brownian Motion
A multivariate fractional Brownian motion (mfBm) with component-wise Hurst exponents is used to model and forecast realized volatility (RV). We investigate the interplay between correlation coefficients and Hurst exponents and propose a novel method to estimate model parameters, establishing its consistency and asymptotic normality. Additionally, we develop a time-reversibility test, which is typically not rejected by RV data. When the data gener…
Financial Risk and Volatility Modeling (2 works) · Autocorrelation (1 work) · Complex Systems and Time Series Analysis (1 work) · Covariance (1 work) · Covariance matrix (1 work) · Detrended fluctuation analysis (1 work) · Econometrics (1 work) · Estimator (1 work) · Fractional Brownian motion (1 work) · Hurst exponent (1 work)