Quantopian

Website

quantopian.com

$ Details

-

Categories

#Development #Finance #Tool #Investing

Pyfolio

Website

quantopian.github.io

$ Details

Categories

#Development #Finance #Tool #Investing #Cryptocurrency

Quantopian features and specs

• Community Collaboration
  Quantopian provided a platform for users to share and collaborate on trading algorithms, enabling users to learn from each other and improve their strategies.
• Access to Data
  Quantopian offered access to a wide range of financial data sets, which allowed users to develop and back-test their algorithms using historical data.
• Comprehensive Development Environment
  It featured an integrated development environment (IDE) with tools for coding, testing, and back-testing trading strategies in Python, which was user-friendly and powerful.
• Educational Resources
  Quantopian provided various educational resources, including lectures, tutorials, and a supportive community forum, which were beneficial for both beginners and experienced traders.
• Competition and Incentives
  Quantopian organized contests that incentivized users to develop successful trading algorithms, with the potential to receive a live trading allocation from the company.

Possible disadvantages of Quantopian

• Shutting Down Services
  Quantopian shut down its retail offering in 2020, which meant that users could no longer use their platform for developing and testing new algorithms.
• Limited Live Trading Options
  Users found limited options for deploying their strategies into live trading. Quantopian allowed this only for algorithms selected for allocation, which reduced accessibility for many users.
• Dependence on Platform
  Users who developed algorithms on Quantopian's platform were heavily dependent on it, and when it shut down, they had to transition to other platforms, which could be challenging.
• Resource Limitations
  There were computational and resource limitations for users, which could restrict the complexity of the algorithms and back-testing users could perform without additional infrastructure.
• Portfolio Selection Process
  The selection process for having algorithms licenced for live trading allocation was competitive and not transparent to many users, which could lead to frustration.

Pyfolio features and specs

• Comprehensive Analysis
  Pyfolio provides a detailed analysis of portfolio performance including metrics like returns, risk, and exposure which helps in understanding the strengths and weaknesses of your investment strategy.
• Integration with Zipline
  Pyfolio integrates seamlessly with Zipline, another Quantopian library, allowing users to analyze the backtest performance results effortlessly.
• Visualization Tools
  The library comes with powerful visualization tools that make it easy to plot and interpret various performance metrics and diagnostics related to the portfolio.
• Open Source
  Being open-source, Pyfolio is accessible to a large community of users who contribute to its development and help fix bugs and improve functionality.
• Customizable
  Offers flexibility to customize reports and analyze specific parameters relevant to a user's strategy, which can be crucial for advanced strategies.

Possible disadvantages of Pyfolio

• Maintenance Issues
  Since Quantopian shut down, Pyfolio has not been actively maintained, potentially leading to compatibility issues with new Python versions or other libraries.
• Limited Support for Asset Classes
  Pyfolio was initially designed with a focus on equities, so it may not be as effective for other asset classes such as futures or options without substantial modification.
• Steep Learning Curve
  New users, especially those without a strong statistical or quantitative background, may experience a steep learning curve due to the complexity of financial metrics used.
• Lack of Real-time Analysis
  Pyfolio is primarily designed for backtesting and may not support real-time portfolio performance analysis and reporting out of the box.
• Dependence on Other Libraries
  Though it integrates well with certain libraries, it still relies on several other libraries for data processing and analysis, which may complicate its standalone use and lead to dependency hell.

Algorithmic Trading with Python and Quantopian p. 1

More videos:

Using Pyfolio to Analyze your Trading Strategies

More videos: