🚀
Finter
PlaygroundData Catalogue
Quick Start
Quick Start
  • Getting Started with Finter: A Quick Guide
  • Explore Finter
    • Finter Labs (Recommended)
    • Other Ways
      • Google Colab
      • Conda, venv, or Docker
      • Setting Up a .env File (Optional)
  • Framework
    • CM (Content Model)
    • AM (Alpha Model)
    • PM (Portfolio Model)
    • Simulatior
      • Target Volume Limit
    • Finter Cli Submission
      • Validation
      • GitHub Sync
      • [Legacy] JupyterLab Submission
      • [Legacy] Submission
  • MODELING
    • MetaPortfolio
      • Equal weight meta portfolio
      • Fixed weight meta portfolio
      • Risk parity meta portfolio
    • StrategicAssetAllocation
    • DateConverter
    • BuyHoldConverter
  • Supporting Tools
    • FileManager
    • Finter AI (alpha ver.)
    • Data
      • FinHelper
        • filter_unchanged
        • unify_idx
        • shift_fundamental
        • rolling
        • expand_to_gvkeyiid
      • ModelData
      • ID Table
      • ID Converter
      • Quanda Data
    • Evaluator
      • top_n_assets
      • bottom_n_assets
      • compare_with_bm
    • PortfolioAnalyzer
    • Email
Powered by GitBook
On this page
  • Description
  • Parameters
  • Returns
  • Example

Was this helpful?

Edit on GitHub
  1. Supporting Tools
  2. Evaluator

bottom_n_assets

Description

This function identifies the n assets with the lowest returns over a specified period. It is designed to provide insights into the underperforming assets within a particular model identified by position.

Parameters

  • position (str): The name of the model to analyze.

  • n (int): The number of assets to return, based on their low returns.

  • start (int, optional): The start date of the analysis period, formatted as YYYYMMDD.

  • end (int, optional): The end date of the analysis period, formatted as YYYYMMDD.

Returns

  • pd.DataFrame: A DataFrame containing the bottom n assets, sorted by their returns in ascending order. It includes their returns and entity names.

Example

bottom_assets_df = Evaluator.bottom_n_assets('ModelName', 5, 20210101, 20211231)

Last updated 1 year ago

Was this helpful?