Forecasts of the power market prices before the day-ahead market closure time are prone to significant error. I predict whether the day ahead or balancing (standard marginal price price will be higher at a given hour next day. It creates decisive forecasts for reducing the balancing cost.

Easy to follow stock price analysis on Indian stock data

Using Long-Short Term Memory Neural Networks to forecast and trade Ethereum, a cryptocurrency.

This project, I am constructing a predictive model that can prognosticate gold prices using historical price data and pertinent financial indicators.

This repository implements the CatBoostRegressor model for predicting prices of financial instruments like stocks, currencies, and cryptocurrencies. It uses gradient boosting to capture patterns in price movements, improving the accuracy and robustness of price forecasts.

This API service is used to forecast product price given the contributing materials that form the final product.

This repository implements a WaveNet model for predicting financial instrument prices, such as currencies, stocks, and cryptocurrencies, using advanced AI techniques like gradient boosting to capture intricate patterns in price movements.

This repository implements an SARIMAX model for predicting financial instrument prices (stocks, currencies, cryptocurrencies). The model uses gradient boosting to capture complex price patterns and handle diverse dataset characteristics for accurate price forecasting.

This repository implements a Temporal Convolutional Network (TCN) model for predicting financial instrument prices, including currencies, stocks, and cryptocurrencies. It uses advanced techniques like gradient boosting to improve prediction accuracy and handle diverse datasets effectively.

This repository implements a Random Forest Regressor for price prediction in financial markets, including stocks, currencies, and cryptocurrencies. It uses gradient boosting techniques to improve the model's accuracy and robustness for forecasting financial data across different datasets.

This repository contains an implementation of the LightGBM model for predicting financial instrument prices like stocks, currencies, and cryptocurrencies. It uses gradient boosting to analyze patterns in price data, aiming to enhance the accuracy and reliability of financial predictions.