Created ML Model which predicts profit/loss based on the details given.
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Updated
Nov 19, 2023 - Jupyter Notebook
Created ML Model which predicts profit/loss based on the details given.
Forecasting Nifty-50 stock prices and computing gains or losses for individual stocks, seamlessly integrated with Google Sheets.
Created LSTM model predicts the stock price of NIFTY 50 with help of various indicators.
NSE historical data analysis (2022 - 2023)
NIFTY 50 index price predictions using deep learning models like 1-d cnn and lstm. Designing a trading strategy to outperform benchmark investments
Stock data analysis
The Nifty 50 Stock Price Prediction project aims to forecast the stock prices of companies listed on India's Nifty 50 index. The Nifty 50 represents the top 50 companies across diverse sectors on the National Stock Exchange (NSE), reflecting the overall performance of the Indian stock market.
Predicting the value of an obfuscated metric relevant for making trading decisions.
Predicting Nifty-50 Stock Price and calculating profit or loss for each stock with google sheet integration
Analyzing the stocks from data given by NIFTY50 on Kaggle
FinSearch Research Competition
StockFolio is a (mock) stock market picker where one can build their portfolio from the Nifty50 stocks. This is a React, Redux, Typescript project with Scss, Framer motion and Firebase.
This Node.js script automates the process of downloading PDF files from the BSE India API based on specific search criteria, such as category, date range, and type. It uses Axios for HTTP requests and file handling, allowing users to fetch and store PDFs locally for further analysis or archiving purposes.
A Demo Financial Application leveraging the power of Go, ClickHouse and Apache Echart
Golden Cross strategy implementation in S&P500 and NIFTY50 historical data.
Scrapping Sensex & Nifty data using Node.js(puppeteer) | Data from Moneycontrol
Finance concepts in python.
This is a backtesting framwork(again, kinda) to understand if doing SIP with any kind of strategy that people talk about are worth looking into or not.
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