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Project Title: Stock Market Analysis (2014-2018)

Author: VARUNSHIYAM S

Description :

This project analyzes a real-world dataset of stock prices for leading multinational corporations (Amazon, Apple, Microsoft, Google) from 2014 to 2018.

Key Objectives :

  • Data Cleaning and Preparation:

    • Ensure data quality by identifying and handling missing, incorrect, or invalid data points.

  • Exploratory Analysis and Visualization:

    • Calculate intraday profits.
    • Analyze distributions of opening vs. closing prices using histograms.
    • Explore relationships between 'open', 'high', 'low', 'close', and 'volume' with bar charts and pie charts.
    • Answer questions about the dataset using Pandas and Matplotlib.

  • Insights:

    • Identify trends for each market.
    • Analyze intraday profits for each market.
    • Visualize the performance of each market over time.
    • Utilize histograms for opening and closing values.
    • Utilize pie charts for stock distribution.
    • Utilize line graphs for stock price timelines.

Potential Benefits for Traders

  • Gain valuable insights into historical data of leading tech companies.
  • Visualize trends and market behavior over time.
  • Leverage visualizations for informed trading decisions.

Key Findings :

  • Stocks of Amazon, Apple, Microsoft, and Google experienced significant growth between 2014 and 2018, solidifying their positions as leading tech players.
  • Amazon's stock price increased the most, reflecting its dominance in e-commerce, cloud computing (AWS), and innovative technologies.
  • Apple's success stemmed from its flagship products (iPhone, iPad) and new categories like the Apple Watch.
  • Microsoft's transformation under CEO Satya Nadella, focusing on cloud computing (Azure) and software services (Office 365), led to impressive growth.
  • Google (Alphabet Inc.) capitalized on its search engine dominance, mobile technology (Android), and digital advertising to achieve substantial growth.

Conclusion :

This analysis highlights the remarkable growth of Amazon, Apple, Microsoft, and Google from 2014 to 2018. Strategic decisions, technological advancements, and innovative product launches have fueled their success. Their ability to adapt to market trends and generate value for investors makes them prominent players in the tech sector.

Further Exploration :

This project lays the groundwork for exploring additional questions about the stock market:

  • Average daily return for Amazon stock.
  • Optimal days for profit booking in Microsoft stock.
  • Vulnerability of Google's stock to financial crises.
  • Volatility of daily returns for Apple stock.

Getting Started :

To get started with this project, follow these steps

Prerequisites :

  • Python 3.x
  • Pandas
  • Matplotlib
  • Jupyter Notebook (optional but recommended)

Installation

  • Clone the repository git clone https://github.com/yourusername/stock-prices-analysis.git

  • Navigate to the project directory cd stock-prices-analysis

  • Install the required packages pip install -r requirements.txt

Usage

  • Open the Jupyter Notebook jupyter notebook

  • Run the notebook Stock_Prices_Analysis.ipynb to see the analysis and visualizations.

Contribution Guidelines :

Contributions to this project are welcome! To contribute:

Fork the repository, make changes, and submit pull requests. Adhere to the project's coding style and formatting guidelines. This README provides an overview of the project's objectives, methodology, and guidelines for contributions. For more details, refer to the project repository.