陈增敬
山东大学数学学院教授，第十四届全国政协委员
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陈增敬
山东大学数学学院教授，第十四届全国政协委员
个人履历：
陈增敬：男，1961年9月出生，中国工业与应用数学学会会士，山东大学齐鲁证劵金融研究院院长、山东大学数学学院院长，教授，博士生导师，教育部“长江学者”特聘教授，国家杰出青年科学基金获得者，国家“百千万人才工程”国家级人选，第十四届孙冶方经济科学奖获得者（《连续时间下的模糊性、风险性和资产收益》），加拿大University of Western Ontario 统计与精算科学系兼职教授。兼任：教育部教学指导委员会统计学分委会委员，全国概率统计学会理事、全国应用统计学会常务理事，第十四届全国政协委员， 民建山东省委会副主任委员，全国应用统计专业学位研究生教育指导委员会委员。1983年获山东师范大学数学系理学学士学位。1998年获山东大学博士学位。陈增敬主要从事金融数学、非线性期望和资产定价的理论与应用研究。提出并证明了倒向随机微分方程的共单调定理、g‐期望唯一性定理、g‐期望表示定理、概率集合下的非线性大数定律和非线性中心极限定理等；他与国际经济学家 Epstein 合作建立的资产定价公式被国外同行称为 Chen‐Epstein 公式，在国际金融学界产生了重要影响。先后在《Annals of Probability》《JRSSB》《Econometrica》《Journal of Economic Theory》 《Economic Theory》《Automatica》《Advances in Applied Mathematics》等顶级期刊上发表了一系列论文。荣获全国五一劳动奖章、泰山学者攀登计划专家。
科研项目：
主持科技部、国家重点研发计划重点专项：金融风险的计量理论与方法，2019-09至2024-08；
主持山东省自然科学基金、重大基础研究项目：金融风险计量理论和控制技术，2019-12至2024-12；
主持国家自然科学基金委员会重点项目：金融数学中的若干随机分析问题的研究，2013-01至2017-12；
参与国家自然科学基金委员会创新群体项目：金融数学-金融风险控制中的G风险度量、倒向随机分析和计算，2010-01至2012-12；
主持国家自然科学基金委员会,杰出青年基金项目，10325106，经济数学，2004-01至2007-12。
论文代表：
A central limit theorem, loss aversion and multi-armed bandits, J. Econ.Theory, 209(2023), 105645, 35 pp.
Strategic two-sample test via the two-armed bandit process, J. R. Stat. Soc. B, 00(2023), 1-28.
Bang-bang control for a class of optimal stochastic control problems with symmetric cost functional, Automatica，149(2023), 110849, 9 pp.
Efficient dynamic channel assignment through laser chaos: a multiuser parallel processing learning algorithm, Sci. Rep-UK, 13(1)(2023), 1353, 12 pp.
A transitivity property of Ocone martingales, Stat. Probabil. Lett., 193 (2023) 109703, 7 pp.
Optimal distributions of rewards for a two-armed slot machine, Neurocomputing, 518 (2023), 401–407.
Laws of Large Numbers for Dynamic Coherent Risk Measures，Journal of Mathematical Finance, 12(2022), 301-323.
Explicit solutions for a class of nonlinear BSDEs and their nodal sets，Probab. Uncertain. Qua., 7(4)(2022), 283–300.
A central limit theorem for sets of probability measures, Stoch. Proc. Appl., 152 (2022) 424–451.
Non-uniform Berry-Esseen bound by unbounded exchangeable pairs approach, Appl. Math. J. Chinese Univ., 36(2)(2021), 256-268.
An invariance principle of strong law of large numbers under nonadditive probabilities, Commun. Stat.-Theor. M., 50(10)(2021), 2398–2418.
A new proof for the generalized law of large numbers under Choquet expectation，J. Inequal. Appl. 2020(158) (2020), 17 pp.
An elementary proof of Peng's central limit theorem under sub-linear expectations, Int. J. Financ. Eng., 7(2)(2020), 2050020, 15 pp.
Extension of the strong law or large numbers for capacities, Math. Control Relat. Fields, 9(1)(2019), 175–190.
Weak laws of large numbers for sublinear expectation, Math. Control Relat. Fields, 8(3-4)(2018), 637–651.
Strong laws of large numbers for sub-linear expectation without independence, Comm. Statist. Theory Methods, 46(15)(2017), 7529–7545.
A general strong law of large numbers for non-additive probabilities and its applications, Statistics, 50(4)(2016), 733–749.
General laws of large numbers under sublinear expectations, Comm. Statist. Theory Methods, 45(14)(2016), 4215–4229.
Strong laws of large numbers for sub-linear expectations, Sci. China Math., 59(5)(2016), 945–954.
Lp solutions of anticipated backward stochastic differential equations under monotonicity and general increasing conditions, Stochastics, 88(2)(2016), 267–284.
Large deviation for negatively dependent random variables under sublinear expectation, Comm. Statist. Theory Methods, 45(2)(2016), 400–412.
Strong law of large numbers for upper set-valued and fuzzy-set valued probability, Math. Control Relat. Fields, 5(3)(2015), 435–452.
A new comparison theorem of multidimensional BSDEs, Acta Math. Appl. Sin. Engl. Ser., 31(1)(2015), 131–138.
Invariance principles for the law of the iterated logarithm under G-framework, Sci. China Math., 58(6)(2015), 1251–1264.
A law of large numbers under the nonlinear expectation, Acta Math. Appl. Sin. Engl. Ser., 31(4)(2015), 953–962.
A strong law of large numbers for non-additive probabilities, Internat. J. Approx. Reason., 54(3)(2013), 365–377.
Harnack inequality for mean-field stochastic differential equations, Statist. Probab. Lett., 83(5)(2013), 1424–1432.
Risk measures and nonlinear expectations, Journal of Mathematical Finance, 3(2013), 383–391.
Optimal Stopping Rule meets Ambiguity, In: Real Options, Ambiguity, Risk and Insurance-World Class University Program in Financial Engineering, Ajou University, Volume Two, 5(2013), 97–125.
Large deviation principle for diffusion processes under a sublinear expectation, Sci. China Math., 55(11)(2012), 2205–2216.
Exponential stability for stochastic differential equation driven by G-Brownian motion, Appl. Math. Lett., 25(11)(2012), 1906–1910.
Representation theorems for generators of BSDEs in Lp spaces, Acta Math. Appl. Sin. Engl. Ser., 28(2)(2012), 255–264.
Laws of large numbers of negatively correlated random variables for capacities, Acta Math. Appl. Sin. Engl. Ser., 27(4)(2011), 749–760.
An integral representation theorem of g-expectations, Risk and Decision Analysis, 2 (2010/2011), 245–255.
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