Shuchen Meng
 ·      
scmeng19@163.com | https://mengmeng12.github.io/ | mengmeng12

    Beijing, China
   Sept. 2014 - June. 2019
• Courses Taken: Calculus, Linear Algebra, Probability and Statistics, Microeconomics, Macroeconomics, Econometric, Game Theory,
Investment and Asset pricing, Derivatives, Futures markets.
       Beijing, China
   Sept. 2019 - June. 2021
• Courses Taken: Advanced Econometric, Behavior Finance, Advanced Investment and Asset pricing, Derivatives, Big data, Financial
Econometric, Computational Finance

     Beijing
   2017.8-2017.10
• Use Mysql to check the logic of data processing.
• Responsible for writing data processing work by using python, like daily increment and filling minute lines for settlement.
     Beijing
   2018.2-2018.5
• Work on investment report about import substitution, fund plate, and high dividend stocks.
• Set up a database for the financial data review, CPI data review. Wrote investment review weekly.
       Beijing
   2018.10-2019.1
• Assist the team leader to conduct market research, participate in the business negotiation and participate in designing the trust prod-
ucts’ structure
• Assist the team leader in project due diligence, preparation of feasibility study report and preparation for the review meeting.
 
         

China Agricultural University
        2017-2018
• In support of ’National Undergraduate Training Programs for Innovation’. Contributed to 2017 CES in English version
• To describe children’s education level with dierent parental o-farm employment strategies
• To examine eect of long-term o-farm employment on children’s education
• To identify whether or not the eect is dierent when parents went out during their children’s primary schooling or junior schooling
 年 月  日   · 
          
 
China Agricultural University
   2019
• The yield curve of Chinese and American Treasury bonds is constructed by N-S-S model and dierent characteristics are compared
by descriptive statistics
• The main influence factors were extracted by PCA method
• The correlation between these factors and macroeconomic variables is tested to explore the meaning of yield curve and how to use
yield curve to make economic decisions
       CAFD, CUFE
   2019
• Combined with the percentage of related news in the total news of the day and news emotion, a news popularity list is formed and
updated daily
• I attempt to develop a competitive machine learning model for forecasting and trading stock, so i compared logistics regression,
randomforest and XG-boosting model. It shows statistically and economically significant improvements with emotionfactor in model.
• Use CCTV news keywords for emotional analysis as the indicator of overall position control
         

CAFD, CUFE
   2019-2020
• A dual focus network (DSANet) is proposed to model the eicient multivariable time series prediction, so as to solve the complex
nonlinear dependence of multiple variables in exchange rate prediction
• The prediction results are compared with the classical time-series model to prove the prediction ability of this model is better

       University
      University
         National
           National
        International

           
    
University

           
       
University

• Python, R, L
A
T
E
X, VB, Stata, SAS
• Familiar with MacOS, Windows, and Microso oice
 年 月  日   · 