Python for Finance: Portfolio Statistical Data Analysis

提供方
Coursera Project Network
在此指導項目中,您將:

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
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

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

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  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

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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