Finance
.
MA Feng

Hits: Date:2020-12-10 10:43

Curriculum Vitae(简历)

 

Ma Feng

 

CONTACT (联系方式)

四川省成都市二环路北一段111

西南交通大学经济管理学院

传真: +86   -28-87600543

金融与财务学系

邮箱:mafeng2016@swjtu.edu.cn

邮编:610031

Southwest Jiaotong University

School   of Economics and Management

Fax: +86   -28-87600543

Department   of Finance

E-mail:mafeng2016@swjtu.edu.cn

No.111,   North Erhuan Road, Chengdu, China 610031

EDUCATION (教育背景)

A. 博士管理科学与工程专业,西南交通大学,2012

B. 硕士经济学,西南交通大学,20010

C. 学士国际经济与贸易,西南交通大学,2006

A. Ph.D. School of Economics and Management, Southwest   Jiaotong University, 2012

B. M.S. School of Economics and Management,   Southwest Jiaotong University, 2010

C. B.S. Humanities College of International Economy and Trade,Southwest   Jiaotong University, 2006

EMPLOYMENT (工作经历)

A. 讲师, 西南交通大学经济管理学院, 9/2016–现在

A. Assistant   Professor, Southwest Jiaotong University, 9/2016–Now

RESEARCH INTEREST(研究兴趣)

金融计量,金融市场波动率预测(高频数据),股票收益率预测

Financial econometric, Financial Market Volatility Forecasting(high   frequency data), stock yield forecasting

PUBLCATIONSPAPERS &   CASES)发表,包括文章和案例

a) Basic or   Discovery Scholarship学术类

[1] Yaojie   Zhang Feng Ma Yudong Wang. Forecasting crude oil prices with a large set of   predictors: Can LASSO select powerful predictors? [J]. Journal of Empirical   Finance. 2019.54:97-117.

[2] Yi,   Yongsheng, Feng Ma: Interest Rate Level and Stock Return Predictability   [J].Review of Financial Economics. 2019. 1873-5924 (SSCI).

[3] Yaojie Zhang,   Feng Ma, Tianyi Wang, Li Liu: Out-of-sample Volatility Prediction: A New   Mixed-Frequency Approach [J]. Journal of Forecasting. 2019.38(7):669-680(SCI).

[4] Yongsheng   Yi, Feng Ma, Dengshi Huang, Yaojie Zhang:Interest rate level and stock return   predictability [J]. Review of Financial Economics. 2019.37(4): 506-522. (SCI)

[5] Yu Li,   Feng Ma, Yaojie Zhang, Zuoping Xiao: Economic policy uncertainty and the   Chinese stock market volatility: new evidence [J]. Applied Economics.   2019.51(49): 5398-5410. (SCI).

[6] Feng Ma,   Xinjie Lu, Ke Yang, Yaojie Zhang: Volatility forecasting: long memory, regime   switching and heteroscedasticity [J]. Applied Economics. 2019. 51(38):   4151-4163. (SCI).

[7] Weiju   Xu, Jiqian Wang, Feng Ma, Xinjie Lu:Forecast the realized range-based   volatility: The role of investor sentiment and regime switching [J]. Physica   A-Statistical Mechanics and Its Applications. 2019.527. (SCI).

[8] Feng Ma,   Yaojie Zhang, Wahab, M. I. M, Xiaodong Lai: The role of jumps in the   agricultural futures market on forecasting stock market volatility: New   evidence [J]. Journal of Forecasting. 2019. 38(5): 400-414. (SCI).

[9] Yongsheng   Yi, Feng Ma, Yaojie Zhang, Dengshi Huang: Forecasting stock returns with   cycle-decomposed predictors [J]. International Review of Financial Analysis.   2019. 64: 250-261. (SCI).

[10] Jing Liu, Feng Ma, Yaojie Zhang: Forecasting   the Chinese stock volatility across global stock markets [J]. Physica   A-Statistical Mechanics and Its Applications. 2019. 525: 466-477. (SCI).

[11] Yanyan   Xu, Dengshi Huang, Feng Ma, Gaoxiu Qiao: Liquidity and realized range-based   volatility forecasting: Evidence from China [J]. Physica A-Statistical   Mechanics and Its Applications. 2019. 525: 1102-1113. (SCI).

[12] Yixiang   Chen, Feng Ma, Yaojie Zhang:Good, bad cojumps and volatility forecasting: New   evidence from crude oil and the US stock markets [J]. Energy Economics. 2019.   81:52-62. (SCI).

[13] Yaojie   Zhang, Feng Ma, Yu Wei: Out-of-sample prediction of the oil futures market   volatility: A comparison of new and traditional combination approaches [J].   Energy Economics. 2019. 81: 1109-1120. (SCI).

[14] Feng Ma, Yin Liao, Yaojie Zhang, Yang Cao:   Harnessing jump component for crude oil volatility forecasting in the   presence of extreme shocks [J]. Journal of Empirical Finance. 2019. 52:   40-55. (SCI).

[15] Weiju   Xu, Feng Ma, Wang Chen, Bing Zhang: Asymmetric volatility spillovers between   oil and stock markets: Evidence from China and the United States [J]. Energy   Economics.2019.80: 310-320. (SCI).

[16] Yaoji Zhang,Yu Wei, Feng Ma, Yongsheng Yi:   Economic constraints and stock return predictability: A new approach [J].   International Review of Financial Analysis. 2019.63:1-9. (SCI).

[17] Yaojie   Zhang, Qing Zeng, Feng Ma,Benshan Shi: Forecasting stock returns: Do less   powerful predictors help? [J]. Energy Economics.2019.78: 32-39. (SCI).

[18] Feng Ma,Wahab, M. I. M, Yaoji   Zhang:Forecasting the US stock volatility: An aligned jump index from G7   stock markets [J]. Pacific-Basin Finance Journal. 2019. 54: 132-146. (SCI).

[19] Yanyan   Xu,Dengshi Huang, Feng Ma, Gaoxiu Qiao: The heterogeneous impact of liquidity   on volatility in Chinese stock index futures market [J]. Physica   A-Statistical Mechanics and Its Applications. 2019. 517: 73-85. (SCI).

[20] Yaojie Zhang, Feng Ma,Bo Zhu: Intraday   momentum and stock return predictability: Evidence from China [J]. 2019.76:   319-329. (SCI).

[21]马锋,张耀杰,黄登仕,赖晓冬. 石油期货价格波动的预测:基于范围波动的新证据[J]. 能源经济.2018.09

[21]Feng   Ma, Yaojie Zhang, Dengshi Huang, Xiaodong Lai: Forecasting oil futures price   volatility: New evidence from realized range-based volatility. Energy   Economics[J]. 2018.09

[22]张耀杰,马锋等. 日内动量和股票收益可预测性:证据来自中国[J]. 经济模型.   2018.08

[22]Yaojie   Zhang, Feng Ma, Bo Zhu: Intraday momentum and stock return predictability:   Evidence from China[J]. Economic Modelling. 2018.08

[23]刘静,马锋,杨科,张耀杰. 基于大跳跃和小跳跃预测石油期货价格波动[J]. 能源经济,2018.04

[23]Jing   Liu, Feng Ma, Ke Yang, Yaojie Zhang: Forecasting the oil futures price   volatility: Large jumps and small jumps[J]. Energy Economics 2018.04

[24]马锋,刘静,张耀杰等. 低频数据真的没有信息吗?基于组合预测的角度[J]. 北美经济与金融杂志.   2018.04

[24]Feng   Ma, Yu Li, Li Liu, Yaojie Zhang: Are low-frequency data really uninformative?   A forecasting combination perspective[J]. The North American Journal of   Economics and Finance 2018.04

[25]马锋,刘静等. 经济政策不确定性对原油期货实现波动性的预测[J]. 应用经济学.2017.10

[25]Feng   Ma, M. I. M. Wahab, Jing Liu, Li Liu: Is economic policy uncertainty   important to forecast the realized volatility of crude oil futures?[J].   Applied Economics 2017.10

[26]马锋,魏宇等. 利用高频数据预测原油的波动性:进一步的证据[J]. 经验经济学.   2017.07

[26]Feng   Ma, Yu Wei, Wang Chen, Feng He: Forecasting the volatility of crude oil fures   using high-frequency data: further evidence[J]. Empirical Economics 2017.07

[27]马锋等. 基于进一步证据预测中国股市实现波动率[J]. 应用经济学.   2016.01

[27]Wang   Pu, Yixiang Chen, Feng Ma: Forecasting the realized volatility in the Chinese   stock market: further evidence. Applied Economics. 2016.01

[28]马锋,魏宇,黄登仕. 基于符号收益和跳跃变差的高频波动率模型. 管理科学学报, 2017

[28]Feng   Ma, Yu Wei, Dengshi, Huang. High frequency volatility model based on symbolic   return and jump variation[J]. Journal of management science, 2017

[29]马锋,魏宇,黄登仕. 隔夜收益率能提高高频波动率模型的预测能力吗?系统工程学报,2016

[29]Feng Ma, Yu Wei, Dengshi, Huang. Can   the overnight rate increase the forecasting ability of the high-frequency   volatility model[J]. Journal of systems engineering , 2016

FUNDED PROJECTS 受资助项目

a) Basic or Discovery Scholarship学术类

[1] 高频数据视角下的金融市场波动率建模及预测:基于机制转换和动态模型平均组合预测法的研究. 国家自然科学青年基金项目.(主持)项目编号:71701170

[1]Forecasting realized volatility in a changing   world: A dynamic model averaging approach. the Natural Science Foundation of   China [grant: 71671145; 71701170].

[2]教育部人文社会科学研究青年基金项目:基于共同跳跃、机制转化和动态模型组合预测法的国际原油市场已实现极差波动率预测研究. 项目编号:17YJC790105人文社会科学基金教育部 [17YJC790105; 17XJCZH002]

[2]Forecasting the realized volatility of the oil   futures market: A regime switching approach. he Humanities and Social Science   Fund of the Ministry of Education [17YJC790105; 17XJCZH002].

[3]中央高校文科科技创新项目:基于马尔科夫状态和动态时变组合预测法的高频波动率建模、预测及其评价研究.项目编号: 2682017WCX01

[3]Modeling, Forecasting and Evaluation of High   Frequency Volatility Based on Markov State and Dynamic Time-varying   Combination Forecasting Method . Ministry of Education Central University   Research Fund [SWJTU grant:2682017WCX01].

[4]国家自然科学青年基金项目:波动率指数衍生产品定价新方法研究基于离散时间波动率模型新视角. 项目编号:71701171

[4]A new pricing method for Volatility Index   Derivatives: a new perspective based on discrete time volatility model. the   Natural Science Foundation of China [research: 71701171].

[5]国家自然科学青年基金项目:基于网络视角的金融系统系统性风险的研究项目编号:71701172

[5]Research project number of systematic risk in   financial system based on Network Perspective.the Natural Science Foundation   of China [research: 71701172].

[6]国家自然科学基金项目:基于混频技术和组合预测的资产复杂性相关性密度预测研究:短期冲击、长期影响与机制转换. 项目编号:71671145

[6]Research on asset complexity correlation   density forecasting based on mixing technology and portfolio forecasting:   short-term impact, long-term impact and mechanism transformation. the Natural   Science Foundation of China [research:71671145].

[7]国家自然科学基金项目:金融危机下原油价格冲击与金融市场波动及其联动复杂性基于多分形机制转换波动率模型和藤copula方法的研究. 项目编号:71371157

[7]Crude Oil   Price Shocks and Financial Market Fluctuations under Financial Crisis and   Their Linkage Complexity: A Study Based on Multi-fractal Mechanism Conversion   Volatility Model and Fujimoto Copula Method. the Natural Science Foundation   of China [research:71371157].

WORKING PAPER 工作论文

a) Basic or   Discovery Scholarship学术类

[1]石油期货价格波动预测:基于区间波动率的新证据,与张耀杰等合著,能源经济,2018.

[1]Forecasting oil futures price volatility: New   evidence from realized range-based volatility, co-author with Zhang, Yaojie;   Huang, Dengshi; Lai, Xiaodong; Energy Economics, 2018.

[2]股票收益预测:弱预测因子有帮助吗?与张耀杰等合著,经济模型,2018.

[2]Forecasting stock returns: Do less powerful   predictors help? co-author with Zhang, Yaojie; Zeng, Qing; Shi, Benshan,   Economic Modelling,2018.

[3]基于预测、经济和组合约束预测原油价格,与易永胜等合著,经济模型,2018.

[3]Forecasting the prices of crude oil using the   predictor, economic and combined constraints, co-author with Yi, Yongsheng;   Zhang, Yaojie; Huang, Dengshi, Economic Modelling, 2018.

[4]基于一个新的视角预测石油期货市场实现波动性,与魏宇等合著,预测,2018.

[4]Forecasting realized volatility of oil futures   market: A new insight, co-author with Wei, Yu; Liu, Li; Huang, Dengshi,   Journal of Forecasting, 2018.

[5]基于动态模型平均法的区间波动率预测,与刘静等合著,经济模型,2017.

[5]Forecasting the realized range-based volatility   using dynamic model averaging approach, co-author with Liu, Jing; Wei, Yu;   Wahab, MIM, Economic Modelling, 2017.

[6]预测股市波动:实现偏斜和峰度有帮助吗?与刘静等合著,物理学报:统计力学及其应用,2017.

[6]Forecasting   stock market volatility: Do realized skewness and kurtosis help? co-author   with Mei, Dexiang; Liu, Jing; Chen, Wang Physica A: Statistical Mechanics and its   Applications, 2017.

OTHER RESEARCH AND   SCHOLARLY ACTIVITIES

各类其它学术、教学和应用实践类成果

a) Basic or   Discovery Scholarship学术类

Ÿ Relevant, active editorships with academic   journals or other business publications在学术期刊任编辑

[1]《能源经济》匿名评审人, 2017-至今

[1] Serves as the Peer Reviewer of Energy   Economics

[2]《能源政策》匿名评审人, 2017-至今

[2]Serves as the Peer Reviewer of Energy policy

[3]《经济模型》匿名评审人, 2017-至今

[3]Serves as the Peer Reviewer of Economic   Modelling

[4]《应用经济学》匿名评审人, 2017-至今

[4]Serves as the Peer Reviewer of Applied   Economics

[5]《物理学报》匿名评审人, 2017-至今

[5]Serves as the Peer Reviewer of Physica A

[6]《亚洲经济杂志》匿名评审人, 2017-至今

[6]Serves as the Peer Reviewer of Journal of Asian   Economic

[7]《应用经济学快报》匿名评审人, 2017-至今

[7]Serves as the Peer Reviewer of Applied   Economics Letters

Ÿ Conference (with presentation) 受邀参会并作报告

[1] 第十五届金融系统工程与风险管理国际年会,北京,2017.

报告论文:Good jump, bad jump and volatility forecasting:   Evidence from the crude oil futures market.

[1]The Fifteenth International Conference on   financial systems engineering and risk management, Beijing, 2017

Present paper:Good jump, bad jump and volatility   forecasting: Evidence from the crude oil futures market.

[2] 第十三届中国金融学年会,辽宁大连,东北财经大学,2016.

点评论文:Short-Sale Constraints and Option Trading:   Evidence from Reg SHO

The thirteenth China financial annual conference,   2016 Dongbei University of Finance and Economics, Liaoning, China.

Comment paperShort-Sale Constraints and Option Trading:   Evidence from Reg SHO

[3] 第十四届金融系统工程与风险管理国际年会,黑龙江哈尔滨,2016.

报告论文:已实现和已实现极差波动率预测模型研究:基于马尔科夫转换机制的研究视角

[3]The Fourteenth International Conference on   financial systems engineering and risk management, 2016 , Haerbin, China.

Present paper: Realized and realized extreme   volatility forecasting models: a research perspective based on Markov   transformation mechanism.

[4] 2016大数据驱动的管理与决策研究学术研讨会,中国香港,香港中文大学.

[4] 2016 big data driven Symposium on management   and decision making, Hongkong, China.

[5] 第十三届金融系统工程与风险管理国际年会,安徽芜湖,2015.

报告论文:高频波动率预测模型研究:基于符号收益和符号跳跃变差的视角.

[5] The 13th international conference of financial   systems engineering and risk management, Anhui province, 2015.

Report paper: A Study of the High-frequency   Volatility Models: A Signed Return and Signed Jump Variation Perspective.

[6] 第十二届金融系统工程与风险管理国际年会,山西太原,2014.

报告论文:隔夜收益率能提高高频波动率模型的预测能力吗?(获优秀论文奖)

[6]The 12th international conference of financial   systems engineering and risk management, Shanxi province, 2014.

Report paper: Can   overnight returns improve the forecasting performance of high-frequency   volatility models (Outstanding Paper Award) .

COURSES TAUGHT   AT SWJTU 教授课程

《固定证券收益》、《金融学漫谈》、《投资决策与风险管理研究》

Fixed Securities Income, Rambling about Finance, Research   on Investment Decision and Risk Management