Rasd - EGX Short-Term Trading Toolkit

An Arabic RTL toolkit for Egyptian Exchange beginners: market gate, stock scanner, chart lab, strategy backtester and Telegram alerts. Python backend with a SQLite price cache.

Client

Date

October 2026

Duration

1 week

Technologies

5 tools

Technologies Used

Python

JavaScript

SQLite

OpenRouter

Telegram Bot API

Project Overview

Rasd is a personal tool I built for short-term trading on the Egyptian Exchange (EGX). It is written for beginners and runs entirely in Egyptian Arabic with a right-to-left layout and an English toggle. The app walks a user through four steps in order: a market gate that scores overall conditions, a scanner that ranks every liquid stock, an AI analyst that checks fundamentals, and a backtester for testing rules on old prices. A chart lab teaches candlesticks, support and resistance, SMA/EMA and RSI with a lesson sequence. A small Python server stores daily candles in SQLite, and a Telegram bot sends scheduled alerts. It is an educational and research tool, not investment advice.

Challenge

EGX has little tooling in Arabic, and beginners are told to read candles and indicators they have never seen. Free data is also awkward: the browser cannot fetch quotes or history from other sites directly, history has to be stored once and reused, and daily bars from different sources must line up. On the strategy side, I wanted test results I could trust, so the rules could not peek at future prices, had to include trading costs, and had to be checked on years of data the rules had not been tuned on. Alerts had to be usable on a phone without opening the app.

Solution

The front end is plain HTML, CSS and JavaScript with a shared stylesheet and one page per step. server.py serves those pages and adds small APIs: it pulls candles from TradingView, stores them in a SQLite cache, records a snapshot after each session, and proxies the AI analyst through OpenRouter with a structured score. lab.py computes indicators from candles only, tests breakout, pullback and momentum setups with entries at the next open, ATR stops, several exit rules and a 1% risk portfolio model, then runs walk-forward tests and writes rules.json. telegram_alerts.py reads those rules, sends entry, stop, share count and max loss, and signals.py tracks every alert as a virtual trade. A Windows tray app keeps the server running.

Results & Impact

Delivered a working local toolkit with thirteen pages: a guided start page, dashboard, market gate, opportunity scanner, AI analyst, strategy backtester, chart lab with seven lessons, stock analysis, risk and stress tests, scenarios, idea challenge, decision journal and data update. The backtest engine writes its results to JSON and its chosen rules feed the live alerts, so the app and the bot use the same logic. The Telegram bot supports scan, gate, stats and rules commands on a Sunday to Thursday Cairo schedule, and a PDF and HTML beginner guide in Arabic ships with it. No user or performance numbers are claimed.