arish14 / stockanalysis

Stock Analysis and Portfolio

Stock Price Portfolio

Introduction

This document provides an overview of the stock price portfolio analysis conducted using Python. The analysis includes the following components:

• Data Retrieval
• Data Visualization
• Portfolio Generation

Data Retrieval

Stock Data Collection

We gathered historical stock price data for the following companies:

• Apple Inc. (AAPL)
• Alphabet Inc. (GOOGL)
• Microsoft Corporation (MSFT)

Data Sources

We used the Yahoo Finance API via the yfinance library to obtain historical stock data. You can find the code for data retrieval in the Python script.

Data Visualization

We used data visualization libraries such as Matplotlib and Seaborn to create visual representations of the stock data. This includes time series plots, moving averages, and distribution plots of daily returns.

Multiple Linear Regression

Analysis

We conducted a multiple linear regression analysis to explore the relationship between stock prices and various financial indicators. The regression analysis included independent variables such as Open, High, Low, Volume, and moving averages.

Results

[Approximately 15.17% of the portfolio is allocated to AAPL (Apple Inc.). About 22.83% of the portfolio is allocated to GOOGL (Alphabet Inc.). The majority, around 62.01%, of the portfolio is allocated to MSFT (Microsoft Corporation).]

Conclusion

This document provides a comprehensive analysis of the stock price portfolio, from data retrieval to prediction. It highlights key findings and insights obtained from the analysis.

Future Work

Future work may include:

• Further analysis and feature engineering
• Refinement of prediction models
• Portfolio optimization strategies