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Nikolaus Hautsch

Nikolaus Hautsch

D-Index & Metrics

Economics and Finance

D-Index
34
Citations
4943
World Ranking
3113
National Ranking
18

Overview

Nikolaus Hautsch is affiliated with the University of Vienna in Austria and contributes extensively to the field of Economics, Econometrics, and Finance. Their research work covers various subfields including Finance, Economics and Econometrics, Statistics and Probability, Electrical and Electronic Engineering, and Management Science and Operations Research.

Their scholarly output involves a focus on topics such as Financial Risk and Volatility Modeling, Market Dynamics and Volatility, Financial Markets and Investment Strategies, Stochastic Processes and Financial Applications, Energy Load and Power Forecasting, Stock Market Forecasting Methods, and Statistical Methods and Inference.

Hautsch has coauthored multiple papers with frequent collaborators such as Torben G. Andersen, Ilya Archakov, Alexander Ristig, Gökhan Cebiroğlu, and Rafael Reisenhofer. Their work appears in a variety of publication venues, with repeated contributions to the Journal of Econometrics, SSRN Electronic Journal, Journal of Financial Econometrics, arXiv (Cornell University), and the European Finance Review.

The scientist's recent papers include:

  • A Descriptive Study of High-Frequency Trade and Quote Option Data*, 2020, Journal of Financial Econometrics
  • Building trust takes time: limits to arbitrage for blockchain-based assets, 2024, European Finance Review
  • Local mispricing and microstructural noise: A parametric perspective, 2021, Journal of Econometrics
  • HARNet: A Convolutional Neural Network for Realized Volatility Forecasting, 2022, SSRN Electronic Journal
  • Maximum-Likelihood Estimation Using the Zig-Zag Algorithm, 2022, Journal of Financial Econometrics

Best Publications

  • Financial Network Systemic Risk Contributions

    Nikolaus Hautsch;Julia Schaumburg;Melanie Schienle

  • Modelling financial high frequency data using point processes

    Luc Bauwens;Nikolaus Hautsch

  • When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions

    Axel Groß-Klußmann;Nikolaus Hautsch

  • Econometrics of Financial High-Frequency Data

    Nikolaus Hautsch

  • The Market Impact of a Limit Order

    Nikolaus Hautsch;Nikolaus Hautsch;Ruihong Huang

  • Systemic risk spillovers in the European banking and sovereign network

    Frank Betz;Nikolaus Hautsch;Nikolaus Hautsch;Tuomas A. Peltonen;Melanie Schienle

  • A blocking and regularization approach to high dimensional realized covariance estimation

    Nikolaus Hautsch;Lada M. Kyj;Roel C. A. Oomen

  • Modelling Irregularly Spaced Financial Data: Theory and Practice of Dynamic Duration Models

    Nikolaus Hautsch

  • Stochastic conditional intensity processes

    Luc Bauwens;Nikolaus Hautsch

  • Modelling Irregularly Spaced Financial Data

    Nikolaus Hautsch

  • Order aggressiveness and order book dynamics

    Anthony D. Hall;Nikolaus Hautsch

  • Pre-averaging based estimation of quadratic variation in the presence of noise and jumps: Theory, implementation, and empirical evidence

    Nikolaus Hautsch;Mark Podolskij

  • Forecasting systemic impact in financial networks

    Nikolaus Hautsch;Julia Schaumburg;Julia Schaumburg;Melanie Schienle

  • Do High-Frequency Data Improve High-Dimensional Portfolio Allocations?

    Nikolaus Hautsch;Lada M. Kyj;Peter Malec

  • Bayesian Learning in Financial Markets: Testing for the Relevance of Information Precision in Price Discovery

    Nikolaus Hautsch;Dieter Hess

  • Modelling the buy and sell intensity in a limit order book market

    Anthony D. Hall;Nikolaus Hautsch

  • Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes

    Nikolaus Hautsch;Peter Malec;Melanie Schienle

  • Volatility Estimation on the Basis of Price Intensities

    Frank Gerhard;Frank Gerhard;Nikolaus Hautsch

  • Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model

    Nikolaus Hautsch

  • Bayesian inference in a Stochastic Volatility Nelson-Siegel model

    Nikolaus Hautsch;Fuyu Yang

  • The impact of macroeconomic news on quote adjustments, noise, and informational volatility

    Nikolaus Hautsch;Dieter E. Hess;David Veredas

  • Bayesian Learning in Financial Markets - Testing for the Relevance of Information Precision in Price Discovery

    Dieter Hess;Nikolaus Hautsch;Nikolaus Hautsch

  • Order Aggressiveness and Order Book Dynamics

    Nikolaus Hautsch;Nikolaus Hautsch;Tony Hall

Frequent Co-Authors

Wolfgang Karl Härdle
Wolfgang Karl Härdle Humboldt-Universität zu Berlin
Stefan Voigt
Stefan Voigt Universität Hamburg
Torben G. Andersen
Torben G. Andersen Northwestern University
Mason A. Porter
Mason A. Porter University of California, Los Angeles
Luc Bauwens
Luc Bauwens Université Catholique de Louvain
Michael Schneider
Michael Schneider RWTH Aachen University
Bernard S. Black
Bernard S. Black Northwestern University
Anna Dreber
Anna Dreber Stockholm School of Economics
Olivier Scaillet
Olivier Scaillet University of Geneva
Elie Bouri
Elie Bouri Lebanese American University

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