Python for Finance: Portfolio Statistical Data Analysis

제공자:
Coursera Project Network
학습자는 이 안내 프로젝트에서 다음을 수행하게 됩니다.

Perform exploratory data analysis and visualization of financial data

Portfolio allocation and calculate portfolio statistical metrics

Perform interactive data visualization using Plotly Express

Clock2 hours
Beginner초급
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

In this project, we will use the power of python to perform portfolio allocation and statistically analyze the performance of portfolio using metrics such as cumulative return, average daily returns and Sharpe ratio. We will analyze the performance of following companies: Facebook, Netflix and Twitter over the past 7 years. This project is crucial for investors who want to properly manage their portfolios, visualize datasets, find useful patterns, and gain valuable insights such as stock daily returns and risks. This project could be practically used for analyzing company stocks, indices or currencies and performance of portfolio. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

개발할 기술

  • Data Manipulation
  • Financial Analysis
  • Python Programming
  • Data Visualization (DataViz)
  • Finance

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  1. Understand the problem statement and business case

  2. Import datasets and libraries

  3. Perform random asset allocation and calculate portfolio daily return

  4. Perform random asset allocation and calculate portfolio daily return

  5. Perform portfolio data visulaization

  6. U​nderstand and calculate portfolio statistical metrics

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

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