Finance & Fintech

StockMarketPredictions

Stock prediction and analysis toolkit covering EDA, RSI calculation, time-series visualizations, and ML models for classification and regression.

PythonTime SeriesEDAML

Time-series research — conceptual system illustration

Time-series research: OHLCV data → EDA & RSI → Model training → Forecast evaluation

Overview

Python project for stock analysis and prediction. It runs exploratory data analysis, plots price trends, computes averages and RSI signals, and trains a Random Forest classifier for prediction tasks alongside linear regression for closing price forecasts. The workflow includes sample inference using OHLCV inputs and backtesting-style comparisons to validate model behavior.

Highlights

Exploratory data analysis with price trends and RSI calculations.
Random Forest classifier for single- and multi-stock prediction.
Linear regression for closing price forecasts.
Sample inference using open/high/low/volume inputs.
Backtesting-style comparisons of predictions vs actuals.