Markus Bibinger

Finance · 2011–2017

A researcher in the Science corpus: 6 papers; trusts 50 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Finance — 88 citations into it; #4,563 of 10,518 by trust here, #5,165 by citations
• Economics and Econometrics — 55 citations into it; #15,175 of 23,481 by trust here, #21,405 by citations
• Statistics and Probability — 26 citations into it; #5,687 of 12,932 by trust here, #4,809 by citations
• Management Science and Operations Research — 11 citations into it
• Mathematical Physics — 7 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Control and Systems Engineering — 5 citations into it
• Global and Planetary Change — 5 citations into it

Whom Markus Bibinger trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Lan Zhang
2. Ole E. Barndorff-Nielsen
3. Jean Jacod
4. Yacine Aït-Sahalia
5. Torben G. Andersen
6. Takaki Hayashi
7. D. Xiu
8. Mark Podolskij
9. Cecilia Mancini
10. Markus Reiß

Who trusts Markus Bibinger overall

1. Florian Hildebrandt
2. Nikolaus Hautsch
3. Asger Lunde
4. Mathias Trabs
5. Markus Pelger
6. Peter Malec
7. Masaaki Fukasawa
8. Markus Reiß
9. Yacine Aït-Sahalia
10. N. Shephard

Papers from Markus Bibinger's perspective

Ordered by how strongly the researchers Markus Bibinger trusts endorse each paper. Same corpus, a different order for every researcher.

1. Separating Microstructure Noise from Volatility
2. Econometric analysis of realized volatility and its use in estimating stochastic volatility models
3. Econometric Analysis of Realised Covariation: High Frequency Covariance, Regression and Correlation in Financial Economics
4. Designing Realised Kernels to Measure the Ex-Post Variation of Equity Prices in the Presence of Noise
5. Realized Variance and Market Microstructure Noise
6. On covariance estimation of non-synchronously observed diffusion processes
7. MODELING AND FORECASTING REALIZED VOLATILITY
8. Testing for Jumps in a Discretely Observed Process
9. ANOVA for diffusions and Itô processes
10. Estimating Covariation: Epps Effect, Microstructure Noise

Their papers

• Estimating the Quadratic Covariation Matrix from Noisy Observations: Local Method of Moments and Efficiency (2013) — 104 citations
• An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory (2011) — 70 citations
• Econometrics of co-jumps in high-frequency data with noise (2015) — 58 citations
• Volatility estimation for stochastic PDEs using high-frequency observations (2017) — 62 citations
• Estimating the Spot Covariation of Asset Prices—Statistical Theory and Empirical Evidence (2014) — 57 citations
• Notes on the sum and maximum of independent exponentially distributed random variables with different scale parameters (2013) — 49 citations