Renko Brick Size:
Three possibilities -
Log based (x% of the price)
ATR (10 period) based
Time Frame and data:
Flexible (From 1M to 1D). The code should automatically call OHLCV data. The data should be cleaned for any NaN values. Sanity test should be available (can be toggled off while running the code) after each step in the code.
Either should be possible
Cash / Futures
The code should pull lot size based on the symbol automatically. The code should be flexible to create a compounding model for position sizing (starting with 1 lot) based on accumulated profit and total capital, assuming margin at 30%.
Indicator: Custom Indicator to be used for Swing Trade (STI)
Buy/Cover Condition: 1 Brick close above the STI
Sell/Short Condition: 1 Brick close below the STI
GAP UP/ GAP DOWN rules need to be defined in case of positional trades.
Data Visualization in python:
The python code should be capable for creating visualization of the strategy (can use mplfinance for the same). This would help in doing sanity test on the back-end code for different variations and easy understanding of the strategy status.
Backtest: Back testing to be performed on tickers to check signal performance and strategy edge.
VPS: The entire strategy is to be executed in Zerodha over AWS cloud on Windows environment.
Deliverable: The complete python code and algo architecture.