NOTE: Fork of Skyte's (modified by maximbelyayev) Relative Strength repository.

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RS Rating

IBD Style Relative Strength Percentile Ranking of Stocks (i.e. 0-99 Score). (Approx 3.9 average deviation score)
I also made a TradingView indicator, updated to use data generated here: https://www.tradingview.com/script/pziQwiT2/

Daily Generated Outputs

Stocks: https://github.com/Fred6725/rs-log/blob/main/output/rs_stocks.csv
Industries: https://github.com/Fred6725/rs-log/blob/main/output/rs_industries.csv

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Known Issues

Unfortunately the close prices loaded from the price history API are not always split adjusted. So if a stock had a split recently there is a chance the relative strength value will be wrong...

Calculation

Yearly performance of stock divided by SPY performance during the same period (SPY by default).

RS Score for Stocks = 40% * P3 + 20% * P6 + 20% * P9 + 20% * P12

RS Score for SPY = 40% * P3 + 20% * P6 + 20% * P9 + 20% * P12

With P3 the performance of the 3 last month. (P3 = Close/Close[63], for 63 days back)

Formula: RS Score = (1 + RS Score for Stocks) / (1 + RS Score for SPY)

Then all stocks are ranked from largest to smallest and a percentile is assigned from 99 to 0.

Considered Stocks

Tickers from ftp://ftp.nasdaqtrader.com/symboldirectory/nasdaqtraded.txt disregarding ETFs and all stocks where the industry and sector information couldn't be retrieved from yahoo finance.

How To Run

Run EXE

1. Open the latest successful run here: https://github.com/maximbelyayev/relative-strength/actions/workflows/exe.yml
2. Download exe-package at the bottom (need to be logged in into github)
3. Exctract the relative-strength folder and enter it
   • If needed open config.yaml and put in your preferences
4. Run relative-strength.exe

Run Python Script

1. Open config.yaml and put in your preferences
2. Install requirements: python -m pip install -r requirements.txt
3. Run relative-strength.py

Separate Steps

Instead of running relative-strength.py you can also:

1. Run rs_data.py to aggregate the price data
2. Run rs_ranking.py to calculate the relative strength rankings

*** Output ***

• in the output folder you will find:
  • the list of ranked stocks: rs_stocks.csv
  • the list of ranked industries: rs_industries.csv

Config

Private File

You can create a config_private.yaml next to config.yaml and overwrite some parameters like API_KEY. That way you don't get conflicts when pulling a new version.

Data Sources

Can be switched with the field DATA_SOURCE

Yahoo Finance

(Benchmark: Loads 1500 Stocks in 20m)

• Is default, no config necessary.

TD Ameritrade

(Benchmark: Loads 1500 Stocks in 18m)

1. Create TDAmeritrade Developer Account and App
2. Put in your API_KEY in config.yaml and change DATA_SOURCE.