Are stocks a good investment? How long should you hold them? How much would you earn and with what variability? Read the notebook to find out.

In today's world, people trade stocks through online with own decisions, based on the financial data and market information. This notebook presents several aspects of analyzing financial data using data science, combined both python and statistics to provide and extract insights from the stock data.

In this Notebook, I analyze the following five semiconductor stocks: HD, INTC, AMD, MU, NVDA, and TSM. Then, I choose the stock with the least correlation to JNJ in order to diversify a portfolio. The data was generated using the GOOGLEFINANCE historical market data script.

Algo Trading - Notebooks: Start to End of Algo Trading Development. Data:Stocks up till 2019 with all daily close data.

A 3 part series of Jupyter notebooks to help one find alpha in the stock market with AI

This notebook provides some skills to perform financial analysis on economical data.

A collection of notebooks and different prediction models that can predict the stock prices. Also a comparison of how all these models performed.

Neuro evolution agent to buy and sell stocks atumatically

Predicting opening price, closing price - all in Jupyter Notebooks