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个人信息
姓名: 牛红丽
牛红丽
系别: 金融工程系
职称: 副教授
联系方式: 地址:东凌经济管理大楼1006室
Email:niuhongli@ustb.edu.cn
简介
牛红丽,理学博士,2016年06月毕业于北京交通大学数学系,主要研究领域为金融物理学、金融市场建模、金融统计等,在国内外期刊发表学术论文20余篇, 主持中国博士后科学基金一项。
教育经历
2011/09-2016/06    北京交通大学  理学院  理学博士
2013/09-2014/08    The University of Kiel (Germany) 访问学者
2007/09-2011/06    北京交通大学  理学院  理学学士 
主要科研项目
主持项目:
2017.08-2018.12 中国博士后面上基金项目(一等)“应用3D渗流系统研究金融市场价格波动”。
2015.01-2016.06 北京交通大学优秀博士生创新项目III类“随机交互金融价格模型及统计分析”。
2014.01-2014.12 北京交通大学优秀博士生创新项目“有限程选举交互系统在金融市场的应用”。
参与项目:
2013.01-2016.12  国家自然科学基金项目“经济物理领域中的金融时间序列回程间隙与波动相关性的预测系统、随机模型和统计分析”。
2012.01-2012.12   中央高校基本科研业务项目“云计算环境下的认证安全研究”
获奖情况
2016.06. 获得“北京市优秀毕业生”称号
代表性著作
第一作者与通讯作者论文:
[1] Hongli Niu,Jun Wang, Return volatility duration analysis of NYMEX energy futures and spot, Energy 140 (2017) 837-849.  (SCI期刊)
[2] Hongli Niu, Jun Wang, Quantifying complexity of financial short-term time series by composite multiscale entropy measure, Commun. Nonlinear Sci. Numer. Simulat. 22 (2015) 375-382. (SCI期刊)
[3] Hongli Niu, Jun Wang, Multifractal and Recurrence Behaviors of Continuum Percolation-Based Financial Price Dynamics, Nonlinear Dynamics 83 (2016) 513-528.  (SCI期刊)
[4] Hongli Niu, Jun Wang, Volatility clustering and long memory of financial time series and financial price model, Digit. Signal Process. 23 (2013) 489–498.  (SCI期刊)
[5] Hongli Niu, Jun Wang, Financial time series prediction by a random data-time effective RBF neural network, Soft Comput. 18 (2014) 497–508. (SCI期刊)
[6] Hongli Niu, Jun Wang, Yunfan Lu,Fluctuation behaviors of financial return volatility duration, Phys. A 448 (2016)30-40.  (SCI期刊)
[7] Hongli Niu, Jun Wang, Complex dynamic behaviors of oriented percolation-based financial time series and Hang Seng index, Chaos, Solitons & Fractals 52 (2013) 36–44.  (SCI期刊)
[8] Hongli Niu, Jun Wang, Entropy and Recurrence Measures of a Financial Dynamic System by an Interacting Voter System, Entropy 27 (2015) 2590-2605. (SCI期刊)
[9] Hongli Niu, Jun Wang, Nonlinear analysis on cross correlation of financial time series by continuum percolation system, Int. J. of Bifurcation and Chaos 26 (2016) 1630004. (SCI期刊)
[10] Hongli Niu, Jun Wang, Phase and multifractality analyses of random price time series by finite-range interacting biased voter system, Comput. Stat. 29 (2014) 1045-1063. (SCI期刊)
[11] Hongli Niu, Jun Wang, Power-law scaling behavior analysis of financial time series model by voter interacting dynamic system, J. Appli. Stat. 40 (2013) 2188–2203. (SCI期刊)
[12] Jun Wang, Huopo Pan, Yiduan Wang, Hongli Niu*, Complex System Analysis on Voter Stochastic System and Jump Time Effective Neural Network of Stock Market, Int. J. Comput. Intel. Syst. 8 (2015) 787-795. (SCI期刊)
[13] 牛红丽, 王军, 基于选举模型理论研究股市特性, 北京交通大学报 36 (2012) 138-144.
非第一作者论文
[1] Haiyan Mo, Jun Wang, Hongli Niu, Exponent Back Propagation Neural Network Forecasting for Financial Cross-Correlation Relationship, Expert Systems With Applications, 2016, 53: 106116
[2] Yunfan Lu, Jun Wang, Hongli Niu, Nonlinear Multi-Analysis of Agent-Based Financial Market Dynamics by Epidemic System, Chaos 25 (2015) 103103.
[3] Yunfan Lu, Jun Wang, Hongli Niu, Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis, Phys. Lett. A 379 (2015) 1023–1031.
[4] Ge Yang, Jun Wang, Hongli Niu,Complexity multiscale asynchrony measure and behavior for interacting financial dynamics,Physics Letters A 380 (2016) 2931-2942.
[5] Di Xiao, Jun Wang, Hongli Niu, Volatility Analysis of Financial Agent-Based Market Dynamics from Stochastic Contact System, Computational Economics 48 (2016) 607-625.
[6] Jie Wang, Jun Wang, Wen Fang, Hongli Niu, Financial Time Series Prediction Using Elman Recurrent Random Neural Networks, Comput. Intel. Neuosc. 2016.
[7] Shaolin Tian, Jun Wang, Hongli Niu, Optimal Impulse Control Stochastic System with Poisson Process, Journal of Convergence Information Technology 8 (2013)
[8] 田绍琳, 王军, 牛红丽, 受控于Poisson过程的脉冲型随机控制问题,哈尔滨工业大学学报 4 (2013).
[10] Yiduan Wang, Yao Qin, Hongli Niu, Jun Wang, Analysis and Modelling of Stock Market Relative Fluctuation by Percolation System, J. Inf. Com. Sci. 9 (2012) 771–779.
研究方向
金融统计、金融物理学、金融时间序列分析、神经网络预测
主讲课程
本科生课程:金融营销学 保险学 信用管理