2022级数量经济学硕士研究生培养方案
所属学科门类:经济学
所属一级学科:应用经济学
所属院系:统计与信息学院
一、培养目标
本专业旨在培养德才兼备,具有家国情怀和国际视野,具备良好政治素质与职业道德,具有扎实的现代经济理论和统计理论基础,精通数量分析的基本方法和手段,具有使用量化分析工具独立分析和解决实际经济决策和金融风险管理问题的能力,具有一定创新创业能力,具有较强的数据处理、分析和计算机应用能力的高级经济金融专门人才。
二、学制
本专业学制为2.5年。在规定时期完成课程学习,但未完成学位论文者,可申请延长学习年限,累计最长学习年限不超过4.5年。
三、研究方向
1.计量经济学理论、方法和应用
2.金融统计与风险管理
3.经济决策与数据挖掘
四、课程设置与学分要求
本专业硕士研究生在攻读硕士学位期间应修满38学分,其中包括公共课7学分,学位基础课18学分,专业选修课8学分(其中方向必修课至少4学分),跨专业选修课2学分,名师讲座2学分,社会实践1学分。此外,本专业硕士研究生必须通过国家英语六级考试,或者经相同水平的英语测试,达到合格要求。具体课程安排和学分见附表。
五、社会实践
根据本专业的培养方案,对于数量经济学高级研究人才的培养,要求掌握高级宏微观经济学、高级计量经济学、数理金融等基础课和专业课,掌握这些课程在科学研究中的应用能力。
对于数量经济学应用型人才的培养,要求学生在研究生期间参加一定的社会实践。通过社会实践,培养学生的实践能力、分析问题和解决问题的能力以及综合运用所学基础知识和基本技能的能力,同时也为增强学生适应社会的能力和就业竞争力。社会实践内容的考核办法主要包括以下几个方面:(1)运用课堂学过的数量经济学知识来分析和思考社会实践过程中发生的事情;(2)总结社会实践中的经验与教训,并将这些经验与教训总结成案例;(3)掌握与实习单位有关行业的基本知识与基本技能;(4)总结有关行业的管理知识与基本技能。成果是围绕上述内容写一篇社会实践报告。
具体要求见《必赢626net入口首页硕士研究生社会实践实施细则》。
六、科研能力
为了提高研究生学术科研能力,发挥研究生导师的指导作用,研究生在校期间必须在导师的指导下,从事科学研究,提高学术素养。
七、培养方式
数量经济学专业的课程均采取讲授、讨论和专题研究的方式进行,对硕士研究生的培养实行导师负责制。
七、学位论文
研究生必须按规定时间完成学位论文撰写,经导师同意推荐答辩并通过校、院组织的论文盲审和答辩,论文质量达到所申请学位的合格要求。具体要求见《必赢626net入口首页硕士学位管理办法实施细则》。学位论文的写作要求见《必赢626net入口首页硕士学位论文内容和格式要求(2020年修订)》。
附表:
类别 | 课程名称 | 第1学期 | 第2学期 | 第3学期 | 学时 | 学分 | 开课部门 | |
公共课 | 中国特色社会主义理论与实践研究 | 2 |
|
| 36 | 2 | 马克思主义学院 | |
马克思主义与社会科学方法论研究 | 1 |
|
| 18 | 1 | 马克思主义学院 | ||
高级英语口语与写作 |
| 2 |
| 36 | 2 | 国际商务外语学院 | ||
统计软件(英) | 2 |
|
| 36 | 2 | 统计与信息学院 | ||
学位基础课 | 学术规范与论文写作 |
| 1 |
| 18 | 1 | 统计与信息学院 | |
高级微观经济学(I) | 3 |
|
| 54 | 3 | 国际经贸学院 | ||
高级宏观经济学(I) | 3 |
|
| 54 | 3 | 国际经贸学院 | ||
高级计量经济学 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
高级程序设计 | 2 |
|
| 36 | 2 | 统计与信息学院 | ||
高等统计学 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
高级计量经济学(II) |
| 3 |
| 54 | 3 | 统计与信息学院 | ||
选修课 | 理论型 | 高级微观经济学(II) |
| 2 |
| 36 | 2 | 国际经贸学院 |
高级宏观经济学(II) |
| 2 |
| 36 | 2 | 国际经贸学院 | ||
时间序列分析* |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
数量经济学研究方法* |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
非参数统计* |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
| 2 |
| 36 | 2 | 统计与信息学院 | |||
国民经济核算理论与方法 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
现代经济增长研究 |
| 2 |
| 36 | 2 | 国际经贸学院 | ||
数理金融** |
| 3 |
| 54 | 3 | 统计与信息学院 | ||
金融工程** |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
博弈论*** |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
应用型 | 国际贸易统计 |
| 3 |
| 54 | 3 | 统计与信息学院 | |
全球价值链统计 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
金融计量学** | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
高频数据与量化交易 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
机器学习*** |
| 3 |
| 54 | 3 | 统计与信息学院 | ||
经济数据挖掘与量化研究*** |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
神经网络与深度学习 |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
强化学习基础 |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
互联网前沿技术创新应用案例 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
复杂系统与复杂网络 |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
社会网络分析与计算方法 |
| 2 |
| 36 | 2 | 国际经贸学院 | ||
跨专业 | 金融工程研究 |
| 2 |
| 36 | 2 | 金融管理学院 | |
公司金融研究 |
| 2 |
| 36 | 2 | 金融管理学院 | ||
国际金融研究 |
|
| 2 | 36 | 2 | 金融管理学院 | ||
金融风险管理 |
|
| 2 | 36 | 2 | 金融管理学院 | ||
投资学 |
|
| 2 | 36 | 2 | 金融管理学院 | ||
固定收益证券研究 |
|
| 2 | 36 | 2 | 金融管理学院 | ||
产业组织理论 |
| 2 |
| 36 | 2 | 国际经贸学院 | ||
人口、资源和环境经济学 |
|
| 2 | 36 | 2 | 国际经贸学院 | ||
市场营销专题 |
| 2 |
| 36 | 2 | 工商管理学院 | ||
服务贸易与全球价值链 |
| 2 |
| 36 | 2 | 贸易谈判学院 | ||
名师讲座 | 8次 | 2 |
| |||||
社会实践 |
|
|
|
| 1 |
|
注:*,**,***分别为方向1、2、3的方向必修课,亦可作为其他方向专业选修课。
MasterPrograminQuantitativeEconomics for2022
AcademicField: Economics
PrimaryDiscipline: Applied Economics
SchoolOffering the Program: School of Statistics and Information
I.Program Objectives
Thismajor aims to cultivate high-level economic and financialprofessionals with both ability and political integrity, family andcountry feelings and international vision, good political quality andprofessional ethics, solid foundation in modern economic theory andstatistical theory, proficient in the basic methods and means ofquantitative analysis, the ability to independently analyze and solvepractical economic decision-making and financial risk managementproblems using quantitative analysis tools, and the ability toinnovate and start a business, and have strong data processing,analysis and computer application capabilities.
II.Duration of the Program
Theduration of this program is 2.5 years. Students who have successfullycompleted the course of study within the prescribed period, but havenot completed the dissertation, may apply for an extension of theperiod of study for a maximum cumulative period not exceeding 4.5years.
III.Research Areas
1. Theories,Methods and Applications in Quantitative Economics
2. FinancialStatistics and Risk Management
3. EconomicDecisions and Data Mining
IV.Courses and Credits
Allstudents must earn 38 credits, including 7 “common required course”credits, 18 “required course” credits, 8 “optional course”credits (including 4 or more “directional compulsory course”credits), 2“cross-specialty optional course” credits, 2 “lecture course”credits and 1 “social practice” credit. In addition, mastercandidates in this program must pass College English Test (CET) 6 oran equivalent test of English language proficiency to fulfil therequirement for graduation. Specific course structure can be found inthe appendix.
V.Social Practice
Accordingto the program plan, students who are going to get seniorquantitative economics researchers are required to have a goodknowledge of courses, such as Advanced Macro- and Micro-economics,Advanced Econometrics and Mathematical Finance. They are alsorequired to apply the learned knowledge in scientific research.
Forstudents who are going to be quantitative economics practicalpersonnel, they are required to take part in social practice. Throughsocial practice, we can equip students with practical abilities toanalyze and solve problems by using the basic knowledge and skillsthey have learned in this program. Hence, we can enhance their socialadaptability and employment competitiveness. Social practice is to beassessed by completing a report covering the following points: 1)Analyze and consider the events occurring in the course of socialpractice by knowledge of quantitative economics learned inclassrooms. 2) Sum up the experiences and lessons in social practicefor case studies. 3) Command the basic knowledge and skill of theinternship and the relevant industry. 4) Summarize the managementknowledge and skills of the relevant industry.
Forspecific requirements, please refer to the Detailed Rules for “theImplementation of social practice for master's degree students ofShanghai University of International Business and Economics”.
VI.Academic Training
Inorder to improve the academic research ability of graduate studentsand give full play to the research guidance role of graduate tutors,graduate students must engage in scientific research and improvetheir academic literacy under the guidance of their tutors.
VII.Education Modes
Allthe courses will take the forms of intensive lectures, discussionsand study in special topics. Master supervisors are responsible forthe cultivation of their master students.
VIII.Dissertation
Graduatestudents must complete the dissertation writing in accordance withthe prescribed time, and with the consent of the supervisor,recommend the defense and pass the thesis defense organized by theuniversity and the college, and the quality level of the thesis meetsthe qualified requirements of the applied degree. For specificrequirements, please refer to the “Detailed Rules for theImplementation of the Measures for the Administration of Master'sDegrees of Shanghai University of International Business andEconomics”. For the writing requirements of the dissertation,please refer to the “Content and Format Requirements for theMaster's Thesis of Shanghai University of International Business andEconomics (Revised in 2020)”.
AttachedTable:
Category | Course Name | Semester | Credit Hours | Credit | Department | |||
1 | 2 | 3 | ||||||
Common Required Courses | Socialist Theory and Practice with Chinese Characteristics | 2 |
|
| 36 | 2 | School of Marxism | |
Research on Marxism and Methodology of Social Science | 1 |
|
| 18 | 1 | School of Marxism | ||
Advanced Speaking & Writing |
| 2 |
| 36 | 2 | School of Languages | ||
Statistical Software (English) | 2 |
|
| 36 | 2 | School of Statistics and Information | ||
Required Courses | Academic Standards and Paper Writing |
| 1 |
| 18 | 1 | School of Statistics and Information | |
Advanced Micro Economics(I) | 3 |
|
| 54 | 3 | School of Business | ||
Advanced Macro Economics(I) | 3 |
|
| 54 | 3 | School of Business | ||
Advanced Econometrics | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Advance Programming | 2 |
|
| 54 | 2 | School of Statistics and Information | ||
Advanced Statistics | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Advanced Econometrics(II) |
| 3 |
| 54 | 3 | School of Statistics and Information | ||
Optional Courses | Theoretical | Advanced Micro Economics (II) |
| 2 |
| 36 | 2 | School of Business |
Advanced Macro Economics(II) |
| 2 |
| 36 | 2 | School of Business | ||
Time Series Analysis* |
| 2 |
| 36 | 3 | School of Statistics and Information | ||
Research Methods in Quantitative Economics* |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Nonparametric Statistics * |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Theory and Application of Spatio-Temporal Statistics |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Theories and Methods of National Accounting | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Modern Economic Growth Research |
| 2 |
| 36 | 2 | School of Business | ||
Mathematical Finance** |
| 3 |
| 54 | 3 | School of Statistics and Information | ||
Financial Engineering ** |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Game Theory** |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Applied | International Trade Statistics Research |
| 3 |
| 54 | 3 | School of Statistics and Information | |
Global Value Chain Statistics |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Financial Econometrics** | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
High-Frequency Trading and Quantitative Finance |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Machine Learning*** |
| 3 |
| 54 | 3 | School of Statistics and Information | ||
Data Mining and Quantitative Research in Economics*** |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Neural Network and Deep Learning*** |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Reinforcement Learning |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Internet Leading Technology Innovative Applications |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Complex System and Complex Networks |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Social Network Analysis and Calculation Methods |
| 2 |
| 36 | 2 | School of Business | ||
Cross-Specialty | Research in Financial Engineering |
| 2 |
| 36 | 2 | School of Finance | |
Research in Corporate Finance |
| 2 |
| 36 | 2 | School of Finance | ||
Research in International Finance |
|
| 2 | 36 | 2 | School of Finance | ||
Financial Risk Management |
|
| 2 | 36 | 2 | School of Finance | ||
Investment |
|
| 2 | 36 | 2 | School of Finance | ||
Fixed Income Securities Research |
|
| 2 | 36 | 2 | School of Finance | ||
The Theory of Industrial Organization |
| 2 |
| 36 | 2 | School of Business | ||
Population, Resource and Environmental Economics |
|
| 2 | 36 | 2 | School of Business | ||
Monographic Study on Marketing Management |
| 2 |
| 36 | 2 | School of Management | ||
Trade in Services and Global Value Chain |
| 2 |
| 36 | 2 | School of Trade Negotiation | ||
Lectures | 8 times | 2 |
| |||||
Social Practice |
|
|
|
| 1 |
|