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고려대학교 금융빅데이터 학회 [FBA]에서 학회원을 모집합니다. (International Students are also welcomed)
고려대학교 금융빅데이터 학회 [FBA]에서 학회원을 모집합니다. (International Students are also welcomed)
글쓴이 : FBA | 등록일 : 2018-12-07 02:04:07 | 글번호 : 179624
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고려대학교 금융빅데이터 학회 [FBA]에서 학회원을 모집합니다. (International Students are also welcomed)

 

자세한 사항은 Additional Information about FBA 를 참고해 주시길 바랍니다학회 지원 및 학회에 대해 궁금한 사항이 있으시면 메일로 문의 부탁드립니다.
Email: 
fba.trading.group@gmail.com

 

FAQ 


Q1. 지원 과정이 어떻게 되나요?

A1. 지원서를 아래 링크에서 다운받고, 작성 완료 후 메일로 보내주시면 됩니다.
     지원이 완료되시면 메일을 통해 면접 일정을 조율하게 됩니다. 

 


Q2. 
프로그래밍 경험이 없는데 지원 가능한가요?

A2. 네 가능합니다파이썬 기초과정이 포함되어 있기 때문에 프로그래밍 경험 없이도 지원가능 합니다.

 

 

 
지원서는 아래 링크에서 받아보실 수 있습니다.

링크: https://www.dropbox.com/s/6cu5uqmt04ay4i6/FBA%20Application%20Form.docx?dl=0

작성 완료 후 
recruit.fba.trading.group@gmail.com  으로 보내주시길 바랍니다.


 

1.        모집 일정

      모집 마감일: 1 4일 (금), 2019.
       
      면접일: 1월 5일 (토), 2019

      합격 발표: 1월 6일 (), 2019.
   
      오리엔테이션: 1월 7일 (), 2019


2.        
세션 시간

       정기 세션매주 토요일 9:00 am


 


Attention International applicants!

Minimum requirements for application are basic level of quantitative methods (calculus, linear algebra) and basic level of English. Our Club is open to people from various backgrounds, so feel free to contact us anytime.

Important Facts

You may download application form from the link below, and please send it to recruit.fba.trading.group@gmail.com

   Link: 
https://www.dropbox.com/s/6cu5uqmt04ay4i6/FBA%20Application%20Form.docx?dl=0


1.        Recruitment Dates
   
     Deadline: Until January 5th, 2019.

     Announcement: January 6th, 2019.

2.        Session Meeting

      Orientation:January 7th 
      Weekly Session: Saturday 9:00 am, Korea University



Additional Information about FBA

Who we are


i.        Overview

We study the field at the intersection of Data Science and application in Quantitative Finance. We create investment portfolio which is applied when we make investment decisions.
In detail, we bring application of practical cutting-edge Data Science technologies into traditional and alternative investment strategies.
As a group, we believe in the power of collective intelligence. We share ideas and analysis, and we fully committed to sharing our research and insights with the worlds investment community.

ii.        Data Science and Finance

Analyzing diverse financial data using data analysis techniques such as regression, data mining, etc. is not new. It had not been classified as a mainstream in finance yet and there are ample opportunities to explore novel investment strategies.
Along with emerging Data Science, we have strong conviction of developing Alpha generating algorithms.

iii.        Our Vision

There is a limit of making alpha from traditional investment strategies using financial data such as stock, bond, derivatives. That is,there is no reason to obsessed with widely used data.
We search for new data. We explore unreleased data from extracting quantitative data from qualitative data.
It takes intense curiosity, craving innovation in research in the global financial markets, their behaviors, drivers, and signals.

iv.        FBA Club 

FBA Club members are intellectuals who are highly interested in Data Science, and Quantitative Finance and pursuing careers in various industries. 

There are diverse goals of FBA Club 
1.  We educate undergraduates in great details (from basic to advanced level) who are pursuing careers as a Data Scientist and Quantitative Analyst.
2.  Before entering industry, we provide people practical analyzing and investment experiences, and offer direct and indirect interaction with people working in the field.
3.  We explore exotic and creative Data Analysis Techniques and investment strategies.



FBA Club Training Program

Program Schedule
- Preliminary Session
- Intermediate Session
- Advanced Session

Program Details

Preliminary Session
        
- Introduction to Python 
- Introduction to Data Analysis  
- Basics of Algorithmic Trading 

Intermediate Session
 

- Artificial Intelligence for Trading 
- Deep Learning Foundations 
 
Advance Session

- Advanced topics in Deep Learning approaches in Quantitative Finance  




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