Devlog 07

Hello :D.

I’m at 10 hours so I have to make a devlog. I will be dropping the tkinter gui completely.

Tkinter is genuinely terrible for this project, I’ve spent too long making the dark theme frames and canvas charts, and the UI still looks very old and bad.

I will be switching the whole frontend to Streamlit. Streamlit is alot easier to use and is way more convenient. Streamlit also converts Cortex into a web app instead of having to download and run it locally. Alot better for users who just want to test it.

The Streamlit building experience also seems better, as they have prebuilt UI components, proper charting libraries, and easier deployment.

Whats next?

I am scrapping the tkinter app. I will start building the backend wrappers and logic to connect with the Streamlit frontend.

Devlog 06

Hello :D.

Since the last devlog, I’ve gotten started on creating the complete pipeline. I started on a script for a complete backtest run.

Majority of the time in this devlog was taken up by my frontend work that I just started. This has been the hardest part so far (for me), I don’t remember the last time I’ve had to use tkinter.

Current features in the UI:

• Ticker selection and date range picker (to retrieve stock data)
• Strategy parameters (fast/slow SMA periods)
• Risk controls (initial capital, commision %, slippage %) to improve backtesting accuracy
• List of all trade executions

I haven’t implemented matplotlib to show the equity curve and drawdown, that will most likely be up next. The current UI also just feels very blocky and sharp, I will be smoothening everything out.

Whats next?

I’ll be implementing the chart using Matplotlib for equity curves and drawdowns, and fixing up the styling/layout.

Devlog 05

hey guys :D.

I’ve finally completed the PerformanceMetrics module. This allows the program to now display trade stats, WLR, return metrics, and alot more.

I also added 4 new strategies for the EMA, Stochastic, ADX, and ATR indicators that I added in the prev devlog.
Main.py was also of course updated to handle the metrics. I’ve also just began work on the full pipeline and data wrappers. After that will come the frontend development.

Devlog 04

Hello :D.

Last devlog I finished up the backtesting engine, strategy module, and added 2 new indicators.

3 new indicators were added to the TechnicalIndicators module:

• Stochastic Oscillator
• ADX (Average directional index - trend strength)
• ATR (Average true range - volatility)

My strategy module was also updated to generate signals for the MACD and Bollinger Bands indicators.

Majority of my time has been taken up by the new PerformanceMetrics module I’ve been working on. This module evaluates the backtesting results with return, risk, drawdown, and trade statistics. It still isn’t finished, but will definitely be done before the next devlog.

Whats next?

Next up will just be more addition of indicators and strategy refinement. After I’ll be setting up the backend wrapper and data handlers to work with the frontend (which I will develop later).

Devlog 03

Hello :D.

Last devlog I migrated everythng to SQLite and built out a few technical indicators.

Devlog took this long as I was working on the backtesting engine for a while. Took a while to understand what was going on when I first tried to work on trade execution, create the cash vs holdings trackng, and the entry exit logic.

I did get a full simulation working that has slippage, comissions, and risk management like stop loss and take profit.

I’ve also added the strategy module to turn indicator outputs into buy and sell signals. 2 new indicators were also added:

• MACD (Moving Average Convergence Divergence)
• Bollinger Bands

main.py was also of course updated to handle the new modules.

Devlog 02

Hello :D.
Last time, I had a script that pulled stock data from yfinance, flattened the dataframes, and saved the data to JSON and CSV files.

For this update, I migrated to an actual local database, created separate modules, and built out the first bit of the indicators.

I switched over to an SQLite database, and as everything was getting too crammed in the main.py, created separate modules for handling the database and fetching yfinance data, which include the DatabaseManager and DataFetcher classes.

I’ve started out on building indicators.py to compute technical indicators. So far I’ve implemented:

• SMA (Simple Moving Average)
• EMA (Exponential Moving Average)
• RSI (Relative Strength Index)

I also updated main.py to handle all the new modules and work with the SQLite database.

Whats next?

I will most likely start building out the strategy part to generate signals based on the indicator outputs.

Devlog 01

Hey guys :D. First devlog of Cortex, heres a quick overview:

Cortex is a backtesting and market analysis platform that I’m building to test algotrading strategies.

For this first update, I got the main data pipeline working. All my data is coming from yfinance. I setup yfinance to pull 2 years of daily OHLCV data for 6 tickers (AAPL, MSFT, GOOGL, NVDA, SPY, and AMZN). pandas returns MultiIndex columns, so I had to format everything into a flat table. The formatted JSON and CSV files are also exported.