Publications
List of all publications by our (post-) doctoral researchers and professors
List of all publications by IRTG professors AFTER May 2017
1. Moro RA, Härdle WK, Schäfer D (2017) Company rating with support vector machines. Statistics&risk modeling, Vol 34 Issue: 1-2 Pages: 55-67 DOI: doi 10.1515/strm-2012-1141
2. Liu R, Härdle WK, Zhang G (2017) Statistical Inference for Generalized Additive Partially Linear Model, J Multivariate Analysis, doi 10.1016/j.jmva.2017.07.011
3. Härdle WK, Osipenko M (2017) Dynamic Valuation of Weather Derivatives under Default Risk, International Journal of Financial Studies, doi 10.3390/ijfs5040023
4. Belomestny D, Härdle WK, Krymova E (2017) Sieve estimation of the minimal entropy martingale marginal density with application to pricing kernel estimation, International J of Theoretical and Applied Finance, DOI 10.1142/S0219024917500418
5. Chao SK, Härdle WK, Huang C (2018) Multivariate Factorisable Sparse Asymmetric Least Squares Regression. Comp Stat Data Analysis, doi 10.1016/j.csda.2017.12.001
6. Linton M, Teo EGS, Bommes E, Chen CYH, Härdle WK (2017) Dynamic Topic Modelling for Cryptocurrency Community Forums. p 355-372, Applied Quantitative Finance (Härdle, Chen, Overbeck eds) Springer Verlag, DOI 10.1007/978-3-662-54486-0
7. Härdle W K, Phoon KF, Lee D (2017) Credit Rating Score Analysis. p 223-244 Applied Quantitative Finance, (Härdle WK, Chen YH, Overbeck L eds), Springer Verlag, DOI 10.1007/978-3-662-54486-0
8. Chen CYH, Chiang CT, Härdle WK (2018) Downside risk and stock returns: An empirical analysis of the long-run and short-run dynamics from the G-7 Countries. J Banking and Finance, Volume 93, August 2018, pp. 21-32, DOI 10.1016/j.jbankfin.2018.05.012
9. Zharova A, Tellinger-Rice J, Härdle WK (2018) How to Measure the Performance of a Collaborative Research Center, Scientometrics, https://link.springer.com/article/10.1007/s11192-018-2910-8 DOI: https://doi.org/10.1007/s11192-018-2910-8
10. Winkelmann, L, Bibinger, M (2018) Common price and volatility jumps in noisy high-frequency data. Electronic Journal of Statistics, 12, 2018-2073, 2018
11. Chen CYH, Härdle WK, Okhrin Y (2018) Tail event driven networks of SIFIs. J Econometrics, DOI: https://doi.org/10.1016/j.jeconom.2018.09.016
12. Chen Y, Härdle WK, Qiang H, Majer, P (2018) Risk Related Brain Regions Detected with 3D Image FPCA, Statistics and Risk Modeling, DOI: https://doi.org/10.1515/strm-2017-0011
13. Ngoc MT, Osipenko M, Härdle WK, Burdejova P (2018) Principal Components in an Asymmetric Norm. J Multivariate Analysis 20181008 accepted
14. Trimborn S, Härdle WK (2018) CRIX an Index for Cryptocurrencies, Empirical Finance, DOI: https://doi.org/10.1016/j.jempfin.2018.08.004
15. Vomfell L, Härdle WK, Lessmann, S (2018) Improving Crime Count Forecasts Using Twitter and Taxi Data, Decision Support Systems, DOI:https://doi.org/10.1016/j.dss.2018.07.003
16. Bibinger M, Neely Ch, Winkelmann L (2019) Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book, DOI:https://doi.org/10.1016/j.jeconom.2019.01.001
17. Chua WS, Chen Y, Härdle WK (2019) Forecasting Limit Order Book Liquidity Supply-Demand Curves with Functional AutoRegressive Dynamics. Quantitative Finance, DOI: https://doi.org/10.1080/14697688.2019.1622290
18. Kostmann M, Härdle WK (2019) Forecasting in Blockchain-Based Local Energy Markets. Energies 2019, 12(14), 2718; https://doi.org/10.3390/en12142718
19. Klein N, Werwatz H, Kneib T (2019)Modelling regional patterns of inefficiency: A Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales. Journal of Econometrics Corresponding. https://doi.org/10.1016/j.jeconom.2019.07.003
20. Lux M, Härdle WK, Lessmann S (2019) Data Driven Value-at-Risk Forecasting using a SVR-GARCH-KDE Hybrid. Comp Stat Data Analysis, DOI: 10.1007/s00180-019-00934-7
21. Yu L, Härdle WK, Borke L, Benschop T (2019) An AI approach to measuring financial risk. The Singapore Economic Review, DOI: 10.1142/S0217590819500668
22. Qian Y, Härdle WK, Chen CYH (2019) Modelling Industry Interdependency Dynamics in a Network Context. Studies in Economics and Finance. DOI: https://doi.org/10.1108/SEF-07-2019-0272
23. Wu DD, Härdle WK (2020) Service Data Analytics and Business Intelligence. Computational Statistics. DOI: https://doi.org/10.1007/s00180-020-00968-2
24. Härdle WK, Harvey C, Reule RCG (2020) Understanding Cryptocurrencies. Journal of Financial Econometrics. DOI: https://doi.org/10.1093/jjfinec/nbz033
25. 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
26. Petukhina A, Reule RCG, Härdle WK (2020) Rise of the Machines? Intraday High-Frequency Trading Patterns of Cryptocurrencies. European Journal of Finance. https://doi.org/10.1080/1351847X.2020.1789684.
27. Hou AJ, Wang W, Chen CYH, Härdle WK (2020) Pricing Cryptocurrency options. Journal of Financial Econometrics. DOI: https://doi.org/10.1093/jjfinec/nbaa006
28. Dautel AJ, Härdle WK, Lessmann St, Seow WV (2020) Forex Exchange Rate Forecasting Using Deep Recurrent Neural Networks. Digital Finance, https://doi.org/10.1007/s42521-020-00019-x
29. Chernozhukov V, Härdle WK, Huang C, Wang W (2020) LASSO-Driven Inference in Time and Space, Annals of Statistics. arXiv:1806.05081
30. Chao SK, Härdle WK, Yuan M (2020) Factorisable Multitask Quantile Regression. Econometric Theory, 00, 2020, 1–23, https://doi.org/10.1017/S0266466620000304
31. Mihoci A, Althof M, Chen CYH, Härdle WK (2020) FRM Financial Risk Meter, Advances in Econometrics, The Econometrics of Networks, 42,ISBN: 9781838675769, https://doi.org/10.1108/S0731-905320200000042016
32. Kim KH, Chao SK, Härdle WK (2020) Simultaneous inference of the partially linear model with a multivariate unknown function. Journal of Statistical Planning and Inference, https://doi.org/10.1016/j.jspi.2020.10.007
33. Kim A, Trimborn S, Härdle WK (2021) VCRIX - a volatility index for crypto-currencies. International Review of Financial Analysis, https://doi.org/10.1016/j.irfa.2021.101915
34. Pele DT, Wesselhöft N, Härdle WK, Kolossiatis M, Yatracos Y (2021) A statistical Classification of Cryptocurrencies, European Journal of Finance, https://doi.org/10.1080/1351847X.2021.1960403
List of all publications by IRTG students AFTER May 2017
1. Benschop T, López Cabrera B (2017) Realized volatility of CO2 futures, SFB 649 Discussion paper 2017-025 (submitted to Energy Economics)
2. Shih-Kang Chao, Wolfgang K. Härdle, Chen Huang (2017) Multivariate Factorisable Sparse Asymmetric Least Squares Regression, Computational Statistics and Data Analysis, former SFB Discussion Paper 2016-058
3. Zbonakova L, Härdle WK, Wang W (2017) Time Varying Quantile Lasso. p 331-353, in Applied Quantitative Finance (Härdle, Chen, Overbeck eds) Springer Verlag, DOI 10.1007/978-3-662-54486-0
4. Audrino F, Huang C, Okhrin O (2017) Flexible HAR Model for Realized Volatility (R&R Studies in Nonlinear Dynamics & Econometrics). www.researchgate.net/publication/303862984_Flexible_HAR_Model_for_Realized_Volatility
5. Chao S-K, Härdle WK, Huang C (2017) Multivariate Factorizable Expectile Regression with Application to fMRI Data (accepted Computational Statistics and Data Analysis), doi.org/10.1016/j.csda.2017.12.001
6. Efimov K, Adamyan L, Spokoiny V (2017) Adaptive Nonparametric Clustering, (Journal of Royal Statistical Society, submitted) arxiv.org/abs/1709.09102
7. Adamyan L, Efimov K, Chen YC, Härdle WK (2017) Adaptive Weights Clustering of Research Papers. SFB Discussion Paper 2017-013 (Submitted to Computational Statistics)
8. Liu R, Härdle WK, Zhang G (2017) Statistical Inference for Generalized Additive Partially Linear Model, J Multivariate Analysis, doi 10.1016/j.jmva.2017.07.011
9. Trimborn S, Härdle WK (2018) CRIX an Index for Cryptocurrencies, Empirical Finance, DOI: https://doi.org/10.1016/j.jempfin.2018.08.004
10. Wesselhöfft N, Härdle WK (2019) Risk-Constrained Kelly Portfolios Under Alpha-Stable Laws, Computational Economics, DOI: http://dx.doi.org/10.1007/s10614-019-09913-y
11. Klochkov Y, Zhivotovskiy N (2020) Uniform Hanson-Wright type concentration inequalities for unbounded entries via the entropy method, Electronic Journal of Probability, https://projecteuclid.org/euclid.ejp/1581130826
12. Chao SK, Härdle WK, Yuan M (2020) Factorisable Multitask Quantile Regression. Econometric Theory, 00, 2020, 1–23, https://doi.org/10.1017/S0266466620000304
13. Zinovyeva EZ, Reule RCG, Härdle WK (2022) Understanding Smart Contracts: Hype or Hope? To appear in “FinTech Research and Applications: Challenges and Opportunities”
(Transformations in Banking, Finance and Regulation series) by World Scientific Publishing, arXiv:2103.08447
Publications from doctoral researchers receiving IRTG funds from the DFG BEFORE 2017
a) Publications in Journals
1. Chen S, Chen CYH, Härdle WKH, Lee TM, Ong B (2017) A first econometric analysis of the CRIX family, in Handbook of Blockchain, Digital Finance and Inclusion, Vol 1, Cryptocurrency, FinTech, InsurTech , and Regulation, David LEE Kuo Chuen Robert Deng, eds. ISBN: 9780128104415, Academic Press, Elsevier
2. Elender H, Trimborn S (2016) The Cross-Section of Crypto-Currencies as Financial Assets, in: Handbook of Blockchain, Digital Finance and Inclusion, Vol 1, Cryptocurrency, FinTech, InsurTech , and Regulation, David LEE Kuo Chuen Robert Deng, eds. ISBN: 9780128104415, Academic Press, Elsevier
3. Härdle W, Huang C (2016) Discussion on "Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings" by Werner Ehm, Tilmann Gneiting, Alexander Jordan and Fabian Krüger. Journal of the Royal Statistical Society: Series B Statistical Methodology 78 (3), 545.
4. Härdle W, Huang C, Chao S (2016) Factorisable Sparse Tail Event Curves with Expectiles. Oberwolfach Report No. 12/2016: New Developments in Functional and Highly Multivariate Statistical Methodology, 26 - 29.
5. Härdle W K, Lee Kuo Chuen D, Nasekin S, Ni X, Petukhina A (2015) Tail Event Driven Asset Allocation: evidence from equity and mutual funds’ markets. Journal of Asset Management (Accepted).
6. Härdle W, Wang W, Yu L (2016) TENET - Tail Event driven NETwork risk. Journal of Econometrics, 192 (2), 499 – 513, DOI: 10.1016/j.jeconom.2016.02.013.
7. Kalinina A, Suvorikova A, Spokoiny V, Gelfand M (2016) Detection of homologous recombination in closely related strains. J Bioinform Comput Biol 14 (2), 1641001, DOI: 10.1142/S0219720016410018.
8. Suvorikova A, Spokoiny V (2016) Multiscale change point detection. Teoriya Veroyatnostei i ee Primeneniya (TVP; Theory of Probability and Its Applications) [in Russian] (Accepted).
b) SFB discussion papers and other publication formats
9. Audrino F, Huang C, Okhrin O (2016) Flexible HAR Model for Realized Volatility (R&R Journal of Financial Econometrics).
10. Belomestny D, Klochkov Y, Spokoiny V (2016) Sieve maximum likelihood estimation in a semi-parametric regression with errors in variables (submitted to Theory of Probability & Its Applications).
11. Benschop T, Lopez-Cabrera B (2014) Volatility Modelling of CO2 Emission Allowance Spot Prices with RegimeSwitching GARCH Models. SFB 649 Discussion Paper 2014-050. (resubmitted Journal of Energy Markets)
12. Chao S-K, Huang C (2016) Multivariate Factorisable Sparse Asymmetric Least Squares Regression (submitted to Journal of Computational and Graphical Statistics).
13. Chen S, Härdle WK, Wang W (2015) Estimating inflation expectation co-movement across countries (submitted to Journal of Empirical Finance).
14. Ebert J, Spokoiny V, Suvorikova A (2016) Construction of Non-asymptotic Confidence Sets in 2-Wasserstein Space arXiv preprint arXiv:1703.03658
15. Efimov K, Adamyan L, Spokoiny V (2016) Adaptive Weights Clustering AWC (submitted to AISTATS 2017).
16. Härdle W K, Kok Fai P, Lee Kuo Chuen D, Nasekin S (2014) TEDAS – Tail Event Driven Asset Allocation. SFB 649 Discussion Paper 2014-032.
17. Fang L, Härdle WK (2015) Stochastic Population Analysis: A Functional Data Approach, SFB Discussion Paper 2015007 (submitted to Population Review).
18. Fang L, Härdle WK and Park JY (2016) A Mortality Model for Multi-populations: A Semi-Parametric Approach, SFB Discussion Paper 2016-023 (submitted to International Journal of Forecasting).
19. Härdle W K, Chen C Y, Qian Y (2016) Industry interdependency in a network context (work in progress).
20. Härdle W K, Hong Z, Nasekin S (2016) Leveraged ETF options volatility paradox: a statistical study. SFB 649 discussion paper 2016-004 (Financial Econometrics revise and resubmit).
21. Holtz S (2016) Parametric covariation from noisy observation: equivalence, efficiency and estimation (to be submitted).
22. Papagiannouli K (2016) Rates of convergence of Co-integrated volatility in presence of jumps (Submitted).
23. Trimborn S, Härdle W K (2016) CRIX or evaluating blockchain based currencies. SFB 649 Discussion Paper 2016-021.
24. Trimborn S, Härdle W K (2016) CRIX an Index for blockchain based currencies (submitted to Journal of Empirical Finance).
25. Trimborn S, Okhrin O (2015) R-package gofCopula: Goodness of Fit tests for Copulae.
26. Yu L, Borke L, Benschop T (2016) FRM: A Financial Risk Meter based on penalizing tail events occurrence. SFB 649 discussion paper 2017-003. (submitted to Statistics & Risk Modeling)
27. Zboňáková L, Härdle W and Wang W (2016) Time Varying Quantile Lasso. SFB 649 Discussion Paper 2016-047.
Publications from (Post)doctoral researchers from Germany, funded by other sources BEFORE 2017
a) Publications in Journals
28. Härdle W K, Hautsch N and Mihoci A (2015) Local Adaptive Multiplicative Error Models for High-Frequency Forecasts. Journal of Applied Econometrics 30 (4), 529 – 550, DOI: 10.1002/jae2376.
29. Härdle W K, Hautsch N and Mihoci A (2012) Modelling and Forecasting Liquidity Supply Using Semiparametric Factor Dynamics. Journal of Empirical Finance 19(4), 610 – 625, DOI: 10.1016/j.jempfin.2012.04.002.
30. López Cabrera B, Schulz F (2016) Volatility Linkages between energy and agricultural commodity prices, Energy Economics, 54, 190 – 203, DOI: 10.1016/j.eneco.2015.11.018.
31. López Cabrera B, Schulz F (2016) Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach. Journal of the American Statistical Asociation, DOI: 10.1080/01621459.2016.1219259.
32. Mihoci A (2016) Modelling Limit Order Book Volume Covariance Structures, accepted for publication in: Hokimoto, T (2016) Advances in Statistical Methodologies and Their Applications to Real Problems, InTech, Rijeka, ISBN 978-953-51-4962-0.
b) SFB discussion papers and other publication formats
33. Fan M, Lu M-J, Härdle W (2016) Hedge Strategy Based on Spectral Risk Measurement (Submitted to Journal of Portfolio Management).
34. Gschöpf P, Mihoci A and Härdle W K (2016) TERES - Tail Event Risk Expectile based Shortfall. SFB 649 Discussion Paper 2015-047, manuscript ID ISR-OA-084-16DP (submitted to International Statistical Review).
35. Härdle W K, Mihoci A and Ting C H A (2016) Adaptive Order Flow Forecasting with Multiplicative Error Models. SFB 649 Discussion Paper 2014-035, manuscript ID FOR-16-0139 (Submitted to Journal of Forecasting).
36. Härdle W, Nasekin S, Lee DKC, Petukhina A (2015) Tail Event Driven ASset allocation: evidence from equity and mutual funds markets, SFB 649 Discussion Paper 2015-045 (R&R to Journal of asset management).
37. Klinke S, Mihoci A and Härdle W K (2010) Exploratory factor analysis in Mplus, R and SPSS. ICOTS-8. Session 4F: Sensible use of multivariate software. ISBN 978-90-77713-54-9.
38. Linlin N, Xu X, Ying C (2015) An Adaptive Approach to Forecasting Three Key Macroeconomic Variables. SFB 649 Discussion Paper 2015-023.
39. López Cabrera B and Schulz F (2016) Time-Adaptive Probabilistic Forecasts of Electricity Spot Prices with Application to Risk Management. SFB 649 Discussion Paper 2016-035.
40. Lu M-J, Yi-Hsuan Chen C, Härdle W (2014) Copula-Based Factor Model for Credit Risk Analysis. SFB 649 Discussion Paper 2015-042.
41. Wesselhöfft N (2016) Constrained Kelly Portfolios under alpha-stable laws.
42. Xu X, Mihoci A and Härdle W K (2016) lCARE - localizing Conditional AutoRegressive Expectiles. SFB Discussion Paper 2015-052, manuscript ID 16-131 (submitted to Journal of Empirical Finance).
43. Zharova A, Mihoci A and Härdle W K (2016) Academic Ranking Scales in Economics: Prediction and Imputation. SFB 649 Discussion Paper 2016-020, manuscript ID ISR-OA-083-16 (submitted to International Statistical Review).
Publications from doctoral researchers at Xiamen University BEFORE 2017
a) Publications in Journals
44. Cai N, Cai Z, Fang Y, Xu Q (2015) Forecasting major Asian exchange rates using a new semiparametric STAR model. Empirical Economics 48 (1), 407 – 426, DOI: 10.1007/s00181-014-0888-5.
45. Chen G, Hong Z, Ren Y (2016) Durable consumption and asset returns: Cointegration analysis. Economic Modelling, 53, 231 – 244, DOI: 10.1016/j.econmod.2015.12.008.
46. 10.1007/s00181-014-0888-5.
47. Dingshi T, Junchao X (2012) Research on Idiosyncratic Risk, Market Efficiency and CAPM anomalies. Nankai Economic Studies, 10, 136 – 153.
48. Haiqiang C, Chuanhai Z (2015) Does index futures trading reduce stock market jump risk? Economic Research Journal 42 (1), 153 – 167.
49. Xu Q, Cai Z, Fang Y (2016) Panel data models with cross-sectional dependence: a selective review. Applied Mathematics-A Journal of Chinese Universities, Series B 31 (2), 127 – 147, DOI: 10.1007/s11766-016-3441-9.
50. Xu W, Hong Z, Qin C (2013) A new sampling strategy willow tree method with application to path-dependent option pricing. Quantitative Finance, 13 (6), 861 – 872, DOI: 10.1080/14697688.2012.762111.
51. Yang Y, Lin M (2016) Bayesian Inference for Nonlinear DSGE Model via Multiple-try Metropolis Algorithm. Statistical Research (Chinese) 33 (2), 91 – 98.
52. Yang Y, Wang L (2016) An auxiliary particle filter for nonlinear dynamic equilibrium models. Economics Letters 144 (7), 112 – 114.
b) SFB discussion papers and other publication formats
53. Cai Z, Fang Y, Xu Q (2016) Inferences for varying-coefficient panel data models with cross-sectional dependence. Working Paper.
54. Härdle W, Nasekin S, Hong Z (2016) Leveraged ETF options implied volatility paradox: a statistical study. SFB 649 Discussion Paper 2016-004.
55. Hong Z, Niu L, Zeng G (2016) Discrete-time arbitrage-free Nelson-Siegel term structure model and application. Available at SSRN 2731041.
List of all publications by IRTG professors
1. Antonczyk D, Fitzenberger B, Sommerfeld K (2010) Rising Wage Inequality, the Decline of Collective Bargaining, and the Gender Wage Gap. Labour Economics, 17(5), 835–847, DOI: 10.1016/j.labeco.2010.04.008.
2. Bai J, Chen HQ, Chong TL, Wang X (2008) Generic Consistency of the Break-Point Estimator under Specification Errors in a Multiple-Break Model. Econometrics Journal, 11, 287 – 307, DOI: 10.1111/j.1368-423X.2008.00237.x.
3. Baumann A, Lessmann S, Coussement K, & De Bock K W (2015) Maximize what matters: Predicting customer churn with decision-centric ensemble selection. Proc. of the 23rd European Conf. on Information Systems (ECIS'15), Münster, Germany: AIS (2015).
4. Bergemann A, Fitzenberger B, Speckesser S (2009) Evaluating the Dynamic Employment Effects of Training Programs in East Germany Using Conditional Difference-in-Differences. Journal of Applied Econometrics, 24(5), 797–823, DOI: 10.1002/jae.1054.
5. Bibinger M, Winkelmann L (2015) Econometrics of cojumps in high-frequency data with noise. Journal of Econometrics, 184(2), 361-378.
6. Biewen M, Fitzenberger B, Osikominu A, Paul M (2014) The Effectiveness of Public-Sponsored Training Revisited: The Importance of Data and Methodological Choices. Journal of Labor Economics, 32(4), 837–897.
7. Blanchard G, Kawanabe M, Sugiyama M, Spokoiny V, Müller K - R (2006) In search of non - Gaussian components of a high - dimensional distribution. Journal of Machine Learning Research, 7, 247 - 282
8. Bluhm M (2015) Investigating the Monetary Policy Strategy of Central Banks Using Assessment Indicators. European Journal of Political Economy, 38, pp. 181–196.
9. Bluhm M, Krahnen J P (2014) Systemic Risk in an Interconnected Banking System with Endogenous Asset Markets. Journal of Financial Stability, 13, pp. 75-94.
10. Brandner H, Lessmann S, Voß S (2013) A memetic approach to construct transductive discrete support vector machines. European Journal of Operational Research, 230(3), 581-595.
11. Breunig C (2015) Goodness‐of‐Fit Tests based on Series Estimators in Nonparametric Instrumental Regression. Journal of Econometrics, 184(2), doi.org/10.1016/j.jeconom.2014.09.006
12. Breunig C and Johannes J (2015) Adaptive Estimation of Functionals in Nonparametric Instrumental Regression. Econometric Theory, 1‐43, doi.org/10.1017/S0266466614000966
13. Burda M, Bachmann R (2010). Sectoral Transformation, Turbulence, and Labor Market Dynamics in Germany. German Economic Review, 11, 37-59, DOI: 10.1111/j.1468-0475.2009.00465.x.
14. Burda M, Boeri T (2009) Preferences for Rigid versus Individualized Wage Setting. Economic Journal 119, 1440-1463, DOI: 10.1111/j.1468-0297.2009.02286.x
15. Burda M, Hamermesh D (2011) Unemployment, Market Work and Household Production. Economic Letters 107(2), 131-133, DOI: 10.1016/j.econlet.2010.01.004.
16. Burda M, Severgnini B (2014) Solow Residuals without Capital Stocks. Journal of Development Economics 109, 154–171. DOI. 10.1016/j.jdeveco.2014.03.007
17. Burda M, Weder M (2015) Payroll Taxes, Social Insurance and Business Cycles. Journal of the European Economic Association. DOI: 10.1111/jeea.12145
18. Burda M, Wyplosz C (2017) Macroeconomics A European Text 7th edition. Oxford: Oxford University Press.
19. Cai Z and Wang X (2014) Selection of mixed copula model via penalized likelihood. Journal of The American Statistical Association, 109, 788-801.
20. Cai Z and Wang Y (2014) Testing predictive regression models with nonstationary regressors. Journal of Econometrics, 178, 4-14.
21. Cai Z, Juhl T and Yang B (2015) Functional index coefficient models with variable selection. Journal of Econometrics, 189, 272-284.
22. Cai Z, Ren Y and Sun L (2015) Pricing kernel estimation: Local estimating equation approach. Econometric Theory, 31, 560-580.
23. Cai Z, Ren Y and Yang B (2015) A Semiparametric Conditional Capital Asset Pricing Model. Journal of Banking and Finance, 61, 117–126.
24. Cai Z, Wang Y and Wang Y (2015) Testing instability in predictive regression model with nonstationary regressors. Econometric Theory, 31 (2015), 953-980.
25. Caner M, Fan Q (2015) Hybrid GEL Estimators: Instrument Selection with Adaptive Lasso. Journal of Econometrics 187: 256-274
26. Chen C.W.S., Li M, Nguyen N.T.H. and Sriboonchita S (2015) On asymmetric market model with heteroscedasticity and quantile regression", Computational Economics, doi:10.1007/s10614-015-9550-3.
27. Chen G, Hong Z and Ren Y (2016) Durable Consumption and Asset Returns: Cointegration Analysis. Economic Modelling, 53, 231–244.
28. Chen H, Fang Y, Li Y (2015) Estimation and Inference for Varying-Coefficient Model with Nonstationary Regressors using Penalized Splines. Econometric Theory, 31, 753-777.
29. Chen H, Han Q, Li Y, Wu K (2013) Does Index Futures Trading Reduce Volatility in the Chinese Stock Market? A Panel Data Evaluation Approach. Journal of Futures Markets, 33, 1167-1190.
30. Chen HQ, Choi MS (2012) Does Information Vault Niagara Falls? Cross-listed Trading in New York and Toronto. Journal of Empirical Finance 19 (2), 175 – 199, DOI: 10.1016/j.jempfin.2012.01.001.
31. Chen HQ, Chong TL, Bai J (2012) Theory and Applications of TAR Model with two Threshold Variables. Econometric Reviews, 31 (2), 142 – 170, DOI: 10.1080/07474938.2011.607100.
32. Chen HQ, Chong TL, She YN (2014) A Principal Component Approach to Measuring Investor Sentiment in China. Quantitative Finance, 14, 573-579.
33. Chen R, Guo R and Lin M (2010) Self-selectivity in Firm’s Decision to Withdraw IPO: Bayesian Inference for Hazard Models of Bankruptcy with Feedback. Journal of the American Statistical Association, 105 (492), 1297 – 1309, DOI: 10.1198/jasa.2010.ap08663.
34. Chen Y, Li B, Niu L (2013) A Local Vector Autoregressive Framework and its Applications to Multivariate Time Series Monitoring and Forecasting. Statistics and Its Interface, 6(4), 499-509.
35. Chen Y, Niu L (2014) Adaptive Dynamic Nelson-Siegel Term Structure Model with Applications. Journal of Econometrics, 180(1), 98 – 115.
36. Chen, HQ (2015) Robust Estimation and Inference for Threshold Models with Integrated Regressors. Econometric Theory, 31(4), 778-810.
37. Chen, HQ, Choi MS, Hong Y (2014) How Smooth is Price Discovery, Evidence from Cross-listed Stock Trading. Journal of International Money and Finance, 32, 668-699.
38. Choros B, Härdle W, Okhrin O (2016) A semi parametric factor model for CDO Surfaces Dynamics. J. Multivariate Analysis, 146, 151–163, DOI:10.1016/j.jmva.2015.09.002
39. Chow G, Liu C, Niu L (2011) Co-movements of Shanghai and New York Stock Prices by Time-varying Regressions. Journal of Comparative Economics, 39 (4), 577 – 583, DOI: 10.1016/j.jce.2011.06.001.
40. Chow G, Niu L (2015) Housing Prices in Urban China as Determined by Demand and Supply. Pacific Economic Review, 20(1), 1-16.
41. Diederichs E, Juditsky A, Spokoiny V, Schütte C (2010) Sparse non - Gaussian component analysis. IEEE Transactions on Information Theory, 56, 3033 – 3047, DOI: 10.1109/TIT.2010.2046229.
42. Dümbgen L, Spokoiny V (2001) Multiscale testing of qualitative hypotheses. Annals of Statistics, 29 (1), 124 – 152, DOI: 10.1214/aos/996986504.
43. Dustmann C, Fitzenberger B, Schönberg U, Spitz-Oener A (2014) From Sick Man of Europe to Economic Superstar: Germany's Resurgent Economy. Journal of Economic Perspectives, 28(1), 167–188.
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155. Wu DD, Härdle WK (2020) Service Data Analytics and Business Intelligence. Computational Statistics. DOI: https://doi.org/10.1007/s00180-020-00968-2
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159. Hou AJ, Wang W, Chen CYH, Härdle WK (2020) Pricing Cryptocurrency options. Journal of Financial Econometrics. DOI: https://doi.org/10.1093/jjfinec/nbaa006
160. Chen D, Chen S, Härdle WK (2015) The Influence of Oil Price Shocks on China’s Macro-economy: A Perspective of International Trade. Journal of Governance and Regulation, 4, (4-1), 178-189. DOI: http://doi.org/10.22495/jgr_v4_i4_c1_p5
161. Dautel AJ, Härdle WK, Lessmann St, Seow WV (2020) Forex Exchange Rate Forecasting Using Deep Recurrent Neural Networks. Digital Finance, https://doi.org/10.1007/s42521-020-00019-x
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