Project Overview
This project automates the analysis of accumulation and distribution of filtered securities(symbol) by filtered brokers and percentage of accumulation and distribution and analysis of floorsheet data traded through Nepal stock Exchange (NEPSE) to track accumulation and distribution patterns.
A large dataset (~60,000-90,000 rows per day based on turnover) containing stock symbol, quantity traded, rate, amount, buyer broker, and seller broker details was extracted from merolagani.com. Multiple days' floorsheet data were combined into a consolidated dataset.
The processed data enables flexible filtering by buyer and/or seller broker numbers, providing:
- Total traded amount for each stock symbol
- Amount traded through the selected broker(s)
- Net buy/sell position (accumulation or distribution) for each symbol via the filtered broker(s)
Tools & Technologies Used:
- Python libraries: Selenium (for web automation), Pandas (for data processing), BeautifulSoup
- ChromeDriver in headless mode for reliable scraping
- Excel: FILTER, SUMIFS, and other formulas for final analysis and reporting
Note: This is a personal practice project designed to demonstrate skills in web data extraction, automation, and financial data analysis. All data is publicly available and used solely for educational purposes.
Project Screenshots
