This repository focuses on predicting Apple Inc.'s stock prices using time series analysis from 2013 to 2018. The project involves data exploration, stationarity analysis, time series decomposition, model development, and generating insights to assist investors.

The stock price forecasting results for 5 leading technology companies: Meta (META), Tesla (TSLA), NVIDIA (NVDA), Microsoft (MSFT), and Apple (AAPL). This analysis uses three popular prediction models: LSTM (Long Short-Term Memory), ARIMA (AutoRegressive Integrated Moving Average), and FBProphet.

I am currently analyzing a portfolio of GOOGL, AMZN, AAPL, and MSFT, evaluating daily returns, volatility, and the Sharpe ratio. Additionally, I’m using a Monte Carlo simulation to project the portfolio's performance over the next 30 years, offering insights into its long-term potential.

Repositorio donde se implementa una red neuronal LTSM para predecir el valor de cierre de varios activos financieros

Nasdaq ML & Analysis

Apple stock forecasting