Wolfgang Karl Härdle
欢迎 来到 我 的 网页 ! Welcome to my webpage!
沃夫冈是柏林洪堡大学经济商学院的终身教授, 统计与计量研究所,数据研究中心主任,数字资产研究所主任,以及厦门大学的外籍专家教授。
Me in 2D:

Financial Risk Meter (FRM):
“There is no rain above the clouds”
Motto
Join the Q2 Ecosystem For D.A.D. – Data. Analytics. Dissemination.
Research
My Erdös Number: 3 (Serfling -> Deheuvels -> Erdös)
My ORCiD: 00000001-5600-3014
Citations
Welcome to my Google scholar, RePEc and SSRN publication statistics
Career
- Professor of Statistics at Humboldt-Universität zu Berlin from 1992
- Visiting Professor at CentER, Tilburg University in 1992
- Ordinary Professor at CORE, Catholic University of Louvain in 1990-1992
- Visiting Professor at CORE, Universite Catholique de Louvain in 1989-1990
- Research associate at Bonn University in 1985-1989
- Research associate at Frankfurt University in 1983-1985
- Research associate at Heidelberg University in 1978-1983
- Habilitation in Statistics and Econometrics at Bonn University in 1988
- Doctorate (Dr. rer. nat.) At University Heidelberg in 1982
- Study at Fridericiana Universität Karlsruhe: Mathematics, Computer Science and Physics – graduated in 1978 as Diplom-Mathematiker
Honours
| 2025 – | Huawei Distinguished Guest Professor, University of Edinburgh |
| 2019 – | YuShan 玉山Scholar, Taiwan |
| 2015 – 2023 | Foreign Expert Professor, Xiamen University, China |
| 2009 – 2016 | Distinguished Visiting professor WISE, Xiamen University, China |
| 2008 | Founding Council Member of the Society for Financial Econometrics (SoFiE) |
Books and Proceedings
The biggest feature of the textbook “Applied Multivariate Statistical Analysis” by Professor Härdle and Professor Simar is the perfect combination of statistical theory and application. The book provides a large number of cases in the fields of finance and economics to illustrate relevant statistics. Quantitative theory, and readers can download the corresponding MATLAB or R language program to reproduce all the examples and graphics in the book, which is very helpful for readers to quickly understand and flexibly use high-dimensional data statistical analysis methods in practice. .
— Fan Jianqing, Chair Professor of Princeton University, Distinguished Professor of Chinese Academy of Sciences
- Chen YC, Härdle WK, Lu, HS (2025) Handbook of Blockchain Analytics. Springer Verlag, Berlin Heidelberg. ISBN 978-3-031-95417-7, e-ISBN 978-3-031-95418-4, Springer link
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
New Projects (last 3 years)
Publications (last 5 years)
- SHI MF, ZHANG CH, CHEN QQ, Härdle WK (2025). Modeling SSE 50 ETF Returns and Option Pricing: Evidence from a Score-Driven GARCH-Jump Approach. Mathematics, https://doi.org/10.3390/math13203332
- LIU YX, WANG ZH, ZHEN Y, Härdle WK, TIAN MZ (2025). Estimation and Model Selection Procedures in Generalized Functional Partially Additive Hybrid Model with Diverging Number of Covariates, Statistica Sinica, https://www3.stat.sinica.edu.tw/ss_newpaper/SS-2024-0358_na.pdf
- XIONG W, Härdle WK, WANG JR, YU KM, TIAN MZ (2025). Mode-Based Classifier: A Robust and flexible discriminant analysis for high dimensional data. Statistica Sinica, 35, 1391-1422 https://doi.org/10.5705/ss.202023.0014
- TENG HW, Härdle WK, Osterrieder J, Pele DT (2025). Digital Assets: Risks, Regulations, Mitigation, Financial Innovation 20250619 accepted https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4594467
- Pele DP, Bolovaneanu V, LIN MB, REN R, Ginavar AT, Spilak B, Alexandru VA, Toma F, Lessmann S, Härdle WK (2025). In the Beginning was the Word: LLM-VaR and LLM-ES. Expert Systems With Applications, https://doi.org/10.1016/j.eswa.2025.128676
- FENG YH, Härdle WK (2025). A data-driven P-spline smoother and the P-Spline-GARCH models, Journal Nonparametric Statistics, https://doi.org/10.1080/10485252.2025.2516492
- Khowaja K, Saef D, Sizov S, Härdle WK (2025). Scenario based merger & acquisition forecasting. Management and Marketing, https://doi.org/10.2478/mmcks-2024-0026
- Gurgul V, Lessmann S, Härdle WKH (2025). Deep Learning and NLP in Cryptocurrency Forecasting: Integrating Financial, Blockchain, and Social Media Data. International Journal of Forecasting. https://doi.org/10.1016/j.ijforecast.2025.02.007
- NI XW, Härdle WK, XIE TJ, ZUO XZ (2025). CRRIX – A Machine Learning Based Regulatory Risk Index for Cryptocurrencies. Computational Statistics, https://doi.org/10.1007/s00180-025-01629-y
- Häusler K, Härdle WK (2025). ETF construction on CRIX. Financ. Innov. 11, 92 (2025). https://doi.org/10.1186/s40854-025-00762-3
- LIU F, Packham N, Härdle WK, Merkl R (2025). Option-based pricing of secured lending in P2P crypto markets. SSRN https://ssrn.com/abstract=4833721
- Krain L, ZUO XR, Härdle WK (2025). Cryptos Have Rough Volatility and Correlated Jumps. Economic Modelling, Digital Finance, https://doi.org/10.1007/s42521-025-00125-8
- Agakishiev I, Härdle WK, Becker DM, ZUO XR (2025). Regime switching forecasting for cryptocurrencies. Digital Finance, https://doi.org/10.1007/s42521-024-00123-2
- TIAN MZ, TAI LN, Tao L, PAN JX, TANG ML; YU KM, Härdle WK (2025). Fully nonparametric inverse probability weighting estimation with non ignorable missing data and its extension to missing quantile regression. Computational Statistics and Data Analysis, https://doi.org/10.1016/j.csda.2025.108127
- NI XW, Schillebeeckx S, Härdle WK (2025). On SGX’s Voyage to Corporate Sustainability: Exploring Emerging Topics in Multi-Industry Corpora. Management and Marketing, accepted 20240921 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4686328
- Ren R, Althof M, Härdle WK (2025). FINANCIAL RISK METER FOR CRYPTOCURRENCIES AND TAIL RISK NETWORK-BASED PORTFOLIO CONSTRUCTION. The Singapore Economic Review, 70(4), 901-927, DOI: https://doi.org/10.1142/S0217590822480010
- Härdle WK, XU X (2024). Localizing Multivariate CAViaR . Statistica Sinica, https://www3.stat.sinica.edu.tw/ss_newpaper/SS-2022-0397_na.pdf
- LIU HL, LI XM, CHEN FF, Härdle WKH, LIANG H (2024). A Comprehensive Comparison of Goodness-of-fit Tests for Logistic Regression Models. Statistics and Computing, Statistics and Computing https://doi.org/10.1007/s11222-024-10487-5
- Petukhina A, Klochkov Y, Härdle WK, Zhivotovskiy N (2024). Robustifying Markowitz. Journal of Econometrics, 239(2), 105387, DOI: https://doi.org/10.1016/j.jeconom.2022.12.006
- Ma S, Yu K, Tang ML, Pan J, Härdle WK, Tian M (2023). A Bayesian multistage spatio‐temporally dependent model for spatial clustering and variable selection. Statistics in Medicine, 42(26), 4794-4823, DOI: https://doi.org/10.1002/sim.9889
- Guo J, Liu F, Härdle WK, Zhang, X, Wang K, Zeng T, Tian M (2023). Sampling Importance Resampling Algorithm with Nonignorable Missing Response Variable Based on Smoothed Quantile Regression. Mathematics, 11(24), 4906, DOI: https://doi.org/10.3390/math11244906
- Chang YC, Teng HW, Härdle, WK (2023). Stochastic volatility dynamic hedging for Deribit BTC options. Yung-Chi Chang, Huei-Wen Teng, and Wolfgang Härdle. Stochastic volatility dynamic hedging of the inverse BTC option. Journal of Futures and Options, 16(2), 1-48, DOI: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4271856
- Li X, Liang H, Härdle WK, Liang H (2023). Model checking for generalized partially linear models. TEST, 1-18, DOI: https://doi.org/10.1007/s11749-023-00897-4
- Li X, Liang H, Härdle WK, Liang H (2023). Use generalized linear models or generalized partially linear models?. Statistics and Computing, 33(5), 101, DOI: https://doi.org/10.1007/s11222-023-10278-4
- Wang Z, Bai Y, Härdle WK, & Tian M (2023). Smoothed quantile regression for partially functional linear models in high dimensions. Biometrical Journal, 65(7), 2200060, DOI: https://doi.org/10.1002/bimj.202200060
- Yu L, Härdle WK, Borke L, Benschop T (2023). An AI approach to measuring financial risk. The Singapore Economic Review, 68(05), 1529-1549, DOI: https://doi.org/10.1142/S0217590819500668
- Pele DT, Wesselhöfft N, Härdle WK, Kolossiatis M, Yatracos YG (2023). Are cryptos becoming alternative assets?. The European Journal of Finance, 29(10), 1064-1105, DOI: https://doi.org/10.1080/1351847X.2021.1960403
- Matic JL, Packham N, Härdle WK (2023). Hedging cryptocurrency options. Review of Derivatives Research, 26(1), 91-133, DOI: https://doi.org/10.1007/s11147-023-09194-6
- Winkel J, Härdle WK (2023). Pricing Kernels and Risk Premia implied in Bitcoin Options. Risks 11: 85, DOI: https://doi.org/10.3390/risks11050085
- Liu F, Packham N, Lu MJ, Härdle WK (2023). Hedging cryptos with Bitcoin futures. Quantitative Finance, 23(5), 819-841, DOI: https://doi.org/10.1080/14697688.2023.2187316
- Liang J, Härdle WK, & Tian M (2023). Imputed quantile tensor regression for near-sited spatial-temporal data. Computational Statistics & Data Analysis, 182, 107713, DOI: https://doi.org/10.1016/j.csda.2023.107713
- Li E, Pan J, Tang M, Yu K, Härdle WK, Dai X, Tian M (2023). Weighted competing risks quantile regression models and variable selection. Mathematics, 11(6), 1295, DOI: https://doi.org/10.3390/math11061295
- Zinovyeva E, Reule RC, Härdle WK (2023). Understanding smart contracts: Hype or hope?. In FinTech Research and Applications: Challenges and Opportunities (pp. 3-91), DOI: https://doi.org/10.1142/9781800612723_0001
- Wang R, Althof M, Härdle WK (2023). A financial risk meter for China. Emerging Markets Review, 56, 101052, DOI: https://doi.org/10.1016/j.ememar.2023.101052
- Khowaja K, Shcherbatyy M, Härdle WK (2023). Surrogate Models for Optimization of Dynamical Systems. In: Belomestny, D., Butucea, C., Mammen, E., Moulines, E., Reiß, M., Ulyanov, V.V. (eds) Foundations of Modern Statistics. FMS 2019. Springer Proceedings in Mathematics & Statistics, vol 425. Springer, DOI: https://doi.org/10.1007/978-3-031-30114-8_16
- Zharova A, Härdle WK, Lessmann S (2022). Data-driven support for policy and decision-making in university research management: A case study from Germany. European Journal of Operational Research, DOI: https://doi.org/10.1016/j.ejor.2022.10.016
- Amor SB, Althof M, Härdle WK (2022). Financial Risk Meter for emerging markets. Research in International Business and Finance, 60, 101594, DOI: https://doi.org/10.1016/j.ribaf.2021.101594
- Chen S, Härdle WK, Wang W (2022). The common and specific components of inflation expectations across European countries. Empirical Economics, 62(2), 553-580, DOI: https://doi.org/10.1007/s00181-021-02027-1
- Chen CYH, Fengler MR, Härdle WK, Liu Y (2022). Media-expressed tone, option characteristics, and stock return predictability. Journal of Economic Dynamics and Control, 134, 104290, DOI: https://doi.org/10.1016/j.jedc.2021.104290
- Spilak B, Härdle WK (2022). Tail-Risk Protection: Machine Learning Meets Modern Econometrics. In: Lee, CF., Lee, A.C. (eds) Encyclopedia of Finance. Springer, Cham. https://doi.org/10.1007/978-3-030-91231-4_94
- Petukhina A, Trimborn S, Härdle WK, Elendner H (2021). Investing with cryptocurrencies–evaluating their potential for portfolio allocation strategies. Quantitative Finance, 21(11), 1825-1853, DOI: https://doi.org/10.1080/14697688.2021.1880023
- Kim A, Trimborn S, Härdle WK (2021). VCRIX—A volatility index for crypto-currencies. International Review of Financial Analysis, 78, 101915. DOI: https://doi.org/10.1016/j.irfa.2021.101915
- Pele DT, Wesselhöft N, Härdle WK, Kolossiatis M, Yatracos Y (2021) A statistical Classification of Cryptocurrencies, European Journal of Finance, DOI: https://dx.doi.org/10.2139/ssrn.3548462
- Härdle WK, Lopez Cabrera B, Melzer, A (2021). Pricing Wind Power Futures. J R Stat Soc Series C. 2021;00:1–20. https://doi.org/10.1111/rssc.12499
- Chen CYH, Härdle WK, Klochkov E (2021). SONIC: SOcial Networks with Influencers and Communities, J of Econometrics, https://doi.org/10.1016/j.jeconom.2021.02.008
- Petukhina A, Trimborn S, Härdle WK, Elendner H (2021). Investing with cryptocurrencies – evaluating the potential of portfolio allocation strategies, Quantitative Finance, https://doi.org/10.1080/14697688.2021.1880023
- Lin MB, Khowaja K, Chen CYH, Härdle WK (2020). Blockchain mechanism and distributional characteristics of cryptos, Advances in Quantitative Analysis of Finance & Accounting (AQAFA), Vol. 18, https://doi.org/10.2139/ssrn.3784776
- Kim KH, Chao SK, Härdle WKH (2020). Simultaneous Inference of the Partially Linear Model with a Multivariate Unknown Function. Journal of Statistical Planning and Inference, Vol. 213, 93-105, DOI: https://doi.org/10.1016/j.jspi.2020.10.007
- Chen S, Härdle WK, Wang W (2020). Inflation Co-movement across Countries in Multi-maturity Term Structure: An Arbitrage-Free Approach, Empirical Econometrics, to appear
- Zinovyeva E, Härdle WK, Lessmann S (2020). Antisocial Online Behavior Detection Using Deep Learning, Decision Support Systems, https://doi.org/10.1016/j.dss.2020.113362
- Chernozhukov V, Härdle WK, Huang C, Wang W (2020). LASSO-Driven Inference in Time and Space, Annals of Statistics, DOI: https://doi.org/10.1214/20-AOS2019
- Dautel AJ, Härdle WK, Lessmann St, Seow WV (2020). Forex Exchange Rate Forecasting Using Deep Recurrent Neural Networks. Digital Finance, DOI: https://doi.org/10.1007/s42521-020-00019-x
- Hou AJ, Wang W, Chen CYH, Härdle WK, (2020). Pricing Cryptocurrency options. J Financial Econometrics, Vol. 18, No. 2, 250–279, DOI: https://doi.org/10.1093/jjfinec/nbaa006
- Chao SK, Härdle WK, Yuan M (2020). Factorisable Multi-Task Quantile Regression, J Econometric Theory, Vol. 37, No. 4, 794 – 816, DOI: https://doi.org/10.1017/S0266466620000304
- Adamyan L, Efimov, K, Chen CYH, Härdle WK (2020). Adaptive Weights Clustering of Research Papers., Digital Finance, DOI: https://doi.org/10.1007/s42521-020-00017-z
- Yu L, Härdle WK, Borke L, Benschop T (2020). An AI approach to Measuring Financial Risk., Singapore Economic Review, DOI: https://doi.org/10.1142/S0217590819500668
- Chen CYH, Härdle WK, Mihoci A (2020). TERES – Tail Event Risk Expectile based Shortfall, Quantitative Finance, DOI: https://doi.org/10.1080/14697688.2020.1786151
- Chen S, Härdle WK, Wang L (2020). Estimation and Determinants of Chinese Banks’ Total Factor Efficiency: A New Vision Based on Unbalanced Development of Chinese Banks and Their Overall Risk., Computational Statistics, DOI: https://doi.org/10.1007/s00180-019-00951-6





























