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王汉超教授

山东大学金融研究院教授，博士生导师

代表性论文:

1. Wang,H. Peng, B. Li,D. and Leng, C. Nonparametric estimation of large covariance matrices with conditional sparsity. Journal of Econometrics (2021), 223: 53-72.

2. Su, Z. and Wang, H. A Donsker-type theorem for log-likelihood processes. Journal of Theoretical Probability (2020), 33: 1401-1425.

3. Wang, H. Lin, Z. and Su, Z. On Bernstein type inequalities for stochastic integrals of multivariate point processes. Stochastic Processes and their Applications (2019), 129: 1605-1621.

4. Song, Y. and Wang, H. Central limit theorems of local polynomial threshold estimators for diffusion processes with jumps. Scandinavian Journal of Statistics (2018) 45: 644-681.

5. Lin, Z. and Wang, H. On convergence to stochastic integrals. Journal of Theoretical Probability (2016) 29: 717–736.

6. Liang, H. Phillips, P. Wang, H. and Wang, Q. Weak convergence to stochastic integrals for econometric applications. Econometric Theory (2016) 32: 1349–1375.

7. Huang, C. Wang, H. and Lin, Z. Nonparametric estimation of quantiles for a class of stationary processes. Science China Mathematics (2015) 58: 2621–2632.

8. Wang, H. The Euler scheme for a stochastic differential equation driven by pure jump semimartingales. Journal of Applied Probability (2015) 52: 149-166.

9. Lin, Z. Wang, H. Strong approximation of locally square-integrable martingales. Acta Mathematica Sinica (English Series) (2012) 28: 1221–1232.

10. Hanif, M. Wang, H. Lin, Z. Reweighted Nadaraya-Watson estimation of jump-diffusion models. Science China Mathematics (2012) 55: 1005–1016.

11. Lin, Z. Wang, H. Empirical likelihood inference for diffusion processes with jumps. Science China Mathematics (2010) 53: 1805-1816.

专著:

Lin, Z. Wang, H. (2014), Weak convergence and its applications, World Scientific Publishing Co. Pte. Ltd., Hackensack, NJ. ISBN 978-981-4447-69-0

教材:

王汉超，于志勇. (2022) 应用随机分析. 高等教育出版社. ISBN:978-7-04-057895-9

王汉超教授

山东大学金融研究院教授，博士生导师

代表性论文:

1. Wang,H. Peng, B. Li,D. and Leng, C. Nonparametric estimation of large covariance matrices with conditional sparsity. Journal of Econometrics (2021), 223: 53-72.

2. Su, Z. and Wang, H. A Donsker-type theorem for log-likelihood processes. Journal of Theoretical Probability (2020), 33: 1401-1425.

3. Wang, H. Lin, Z. and Su, Z. On Bernstein type inequalities for stochastic integrals of multivariate point processes. Stochastic Processes and their Applications (2019), 129: 1605-1621.

4. Song, Y. and Wang, H. Central limit theorems of local polynomial threshold estimators for diffusion processes with jumps. Scandinavian Journal of Statistics (2018) 45: 644-681.

5. Lin, Z. and Wang, H. On convergence to stochastic integrals. Journal of Theoretical Probability (2016) 29: 717–736.

6. Liang, H. Phillips, P. Wang, H. and Wang, Q. Weak convergence to stochastic integrals for econometric applications. Econometric Theory (2016) 32: 1349–1375.

7. Huang, C. Wang, H. and Lin, Z. Nonparametric estimation of quantiles for a class of stationary processes. Science China Mathematics (2015) 58: 2621–2632.

8. Wang, H. The Euler scheme for a stochastic differential equation driven by pure jump semimartingales. Journal of Applied Probability (2015) 52: 149-166.

9. Lin, Z. Wang, H. Strong approximation of locally square-integrable martingales. Acta Mathematica Sinica (English Series) (2012) 28: 1221–1232.

10. Hanif, M. Wang, H. Lin, Z. Reweighted Nadaraya-Watson estimation of jump-diffusion models. Science China Mathematics (2012) 55: 1005–1016.

11. Lin, Z. Wang, H. Empirical likelihood inference for diffusion processes with jumps. Science China Mathematics (2010) 53: 1805-1816.

专著:

Lin, Z. Wang, H. (2014), Weak convergence and its applications, World Scientific Publishing Co. Pte. Ltd., Hackensack, NJ. ISBN 978-981-4447-69-0

教材:

王汉超，于志勇. (2022) 应用随机分析. 高等教育出版社. ISBN:978-7-04-057895-9

王汉超教授

山东大学金融研究院教授，博士生导师

代表性论文:

1. Wang,H. Peng, B. Li,D. and Leng, C. Nonparametric estimation of large covariance matrices with conditional sparsity. Journal of Econometrics (2021), 223: 53-72.

2. Su, Z. and Wang, H. A Donsker-type theorem for log-likelihood processes. Journal of Theoretical Probability (2020), 33: 1401-1425.

3. Wang, H. Lin, Z. and Su, Z. On Bernstein type inequalities for stochastic integrals of multivariate point processes. Stochastic Processes and their Applications (2019), 129: 1605-1621.

4. Song, Y. and Wang, H. Central limit theorems of local polynomial threshold estimators for diffusion processes with jumps. Scandinavian Journal of Statistics (2018) 45: 644-681.

5. Lin, Z. and Wang, H. On convergence to stochastic integrals. Journal of Theoretical Probability (2016) 29: 717–736.

6. Liang, H. Phillips, P. Wang, H. and Wang, Q. Weak convergence to stochastic integrals for econometric applications. Econometric Theory (2016) 32: 1349–1375.

7. Huang, C. Wang, H. and Lin, Z. Nonparametric estimation of quantiles for a class of stationary processes. Science China Mathematics (2015) 58: 2621–2632.

8. Wang, H. The Euler scheme for a stochastic differential equation driven by pure jump semimartingales. Journal of Applied Probability (2015) 52: 149-166.

9. Lin, Z. Wang, H. Strong approximation of locally square-integrable martingales. Acta Mathematica Sinica (English Series) (2012) 28: 1221–1232.

10. Hanif, M. Wang, H. Lin, Z. Reweighted Nadaraya-Watson estimation of jump-diffusion models. Science China Mathematics (2012) 55: 1005–1016.

11. Lin, Z. Wang, H. Empirical likelihood inference for diffusion processes with jumps. Science China Mathematics (2010) 53: 1805-1816.

专著:

Lin, Z. Wang, H. (2014), Weak convergence and its applications, World Scientific Publishing Co. Pte. Ltd., Hackensack, NJ. ISBN 978-981-4447-69-0

教材:

王汉超，于志勇. (2022) 应用随机分析. 高等教育出版社. ISBN:978-7-04-057895-9

王汉超教授

山东大学金融研究院教授，博士生导师

代表性论文:

1. Wang,H. Peng, B. Li,D. and Leng, C. Nonparametric estimation of large covariance matrices with conditional sparsity. Journal of Econometrics (2021), 223: 53-72.

2. Su, Z. and Wang, H. A Donsker-type theorem for log-likelihood processes. Journal of Theoretical Probability (2020), 33: 1401-1425.

3. Wang, H. Lin, Z. and Su, Z. On Bernstein type inequalities for stochastic integrals of multivariate point processes. Stochastic Processes and their Applications (2019), 129: 1605-1621.

4. Song, Y. and Wang, H. Central limit theorems of local polynomial threshold estimators for diffusion processes with jumps. Scandinavian Journal of Statistics (2018) 45: 644-681.

5. Lin, Z. and Wang, H. On convergence to stochastic integrals. Journal of Theoretical Probability (2016) 29: 717–736.

6. Liang, H. Phillips, P. Wang, H. and Wang, Q. Weak convergence to stochastic integrals for econometric applications. Econometric Theory (2016) 32: 1349–1375.

7. Huang, C. Wang, H. and Lin, Z. Nonparametric estimation of quantiles for a class of stationary processes. Science China Mathematics (2015) 58: 2621–2632.

8. Wang, H. The Euler scheme for a stochastic differential equation driven by pure jump semimartingales. Journal of Applied Probability (2015) 52: 149-166.

9. Lin, Z. Wang, H. Strong approximation of locally square-integrable martingales. Acta Mathematica Sinica (English Series) (2012) 28: 1221–1232.

10. Hanif, M. Wang, H. Lin, Z. Reweighted Nadaraya-Watson estimation of jump-diffusion models. Science China Mathematics (2012) 55: 1005–1016.

11. Lin, Z. Wang, H. Empirical likelihood inference for diffusion processes with jumps. Science China Mathematics (2010) 53: 1805-1816.

专著:

Lin, Z. Wang, H. (2014), Weak convergence and its applications, World Scientific Publishing Co. Pte. Ltd., Hackensack, NJ. ISBN 978-981-4447-69-0

教材:

王汉超，于志勇. (2022) 应用随机分析. 高等教育出版社. ISBN:978-7-04-057895-9

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