Skip to content

Lightweight Data Analytics, Fintech App that finds best investment pair in a given industry among stocks in S&P 500 index based on estimation

Notifications You must be signed in to change notification settings

jytjyt05/Investment-Portfolio-Rec

Folders and files

NameName
Last commit message
Last commit date

Latest commit

15f564c · Dec 11, 2022

History

17 Commits
Dec 11, 2022
Feb 9, 2022
Feb 9, 2022
Nov 30, 2022
Aug 16, 2022
Feb 9, 2022

Repository files navigation

Overview

This lightweight Data Analysis, Fintech App is created to find best investment portoflio in a given industry among stocks in S&P 500 index based on an estimation, such estimation has two parts: the stock's modified z-score and the stock's market to book ratio. The programming language is in Python, it also incorporates a tk interface for convinent usage.

Features

- The user can enter the day range (such as 2020-01-01 to 2021-09-01).
- The user can also choose the industry from the stocks in S&P 500 index.

Summary

  • The code finds a list of stocks satisfying the Benjamen Graham Value Stock Criteria (Modified Altman Z-Score above A- level) and another list of stocks having a Modified Z-Score below BBB- level, both in year 2020.
  • Then the code also finds a list of stocks with market-to-book (M2B) above 20 and another list with M2B below 2.0
  • Long $50,000 in a stock that is both in the high-credit list and in the low-M2B list
  • Short $50,000 in a stock that is both in the low-credit list and in the high-M2B list
  • Return pairs of stocks with the highest investment return in dollars during the chosen day range

Structure

Screenshot1

Demo Screenshot

Entering informations on the boxes at top, after execution, the result is displayed in the box at the middle right. As we can see, the best investing pair in Energy industry is Long a stock in XOM and Short a stock in OXY. Screenshot2

About

Lightweight Data Analytics, Fintech App that finds best investment pair in a given industry among stocks in S&P 500 index based on estimation

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages