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https://github.com/manikantasanjay/time_series_data_analysis_on_stocks

Time Series Data Analysis project on Daily Stock Prices of the following companies(Apple, Microsoft, Google, Amazon) for a span of 5 years.
https://github.com/manikantasanjay/time_series_data_analysis_on_stocks

data-analysis pandas stock time-series time-series-analysis

Last synced: 12 days ago
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Time Series Data Analysis project on Daily Stock Prices of the following companies(Apple, Microsoft, Google, Amazon) for a span of 5 years.

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README 

        
# Time_Series_Data_Analysis_on_Stocks

## Description:

This repository is dedicated to performing exploratory time series data analysis on daily stock prices of key tech companies: Apple, Microsoft, Google, and Amazon, over a span of 5 years. 



## Update v2:  

The project now includes features for fetching real-time stock data using Yahoo Finance API, storing it in MongoDB, and performing various statistical and financial analyses. Additionally, it now features an interactive web-based dashboard built with Dash that allows for dynamic visualization and deeper analysis of stock data.



## 🛠 Libraries Used

* Pandas - For data manipulation and analysis

* Numpy - Support for large, multi-dimensional arrays and matrices

* Seaborn & Matplotlib - For plotting graphs for data visualization

* MongoDB - Used for storing fetched stock data

* yfinance - Used to fetch live stock data

* Dash: Used for building web-based application dashboards.

* TA-Lib: For calculating technical indicators

* Plotly: For creating interactive plots.



## 🗂 Dataset



Explore the historical and the most recent stock data:



Historical Data: Navigate to the link to view the .csv files for each company https://github.com/ManikantaSanjay/Time_Series_Data_Analysis_on_Stocks/tree/main/individual_stocks_5yr :link:



Real-time Data: Data is fetched daily using the yfinance library and stored in MongoDB



## 📊  Tasks Performed



#### Task 1 : Analysing the Closing Price of all the stocks



#### Task 2 : Analysing the Total Volume of stocks being traded each day



#### Task 3 : Analysing the Daily Price Change in stock.



#### Task 4 : Analysing the Monthly Mean of Close Column.



#### Task 5 : Analysing the Correlation between the Stock Prices of these Tech companies. 



#### Task 6 : Analysing the Daily Return of Each Stock & Their Co-Relation



#### Task 7 : Value at Risk Analysis for Apple Stocks



### Update v2:

#### Task 8 : Fetch and Update Stock Data Daily: Script to fetch daily stock data from Yahoo Finance and update the MongoDB database.



#### Task 9: Advanced Financial Calculations/Technical Indicators:

* Stochastic Oscillator and RSI (Relative Strength Index) calculations to measure stock momentum.

* Historical Volatility analysis of closing prices for each month.

* CAGR (Compound Annual Growth Rate) to measure the mean annual growth rate of investment.

* MACD (Moving Average Convergence Divergence) to reveal changes in the strength, direction, momentum, and duration of a trend in a stock's price.

* Advanced Candlestick pattern detection for strategic trading insights.

* Analysis of Money Flow Index (MFI) to identify overbought or oversold conditions.

* Detection of divergences between price movements and MFI, highlighting potential reversal points.



#### Task 10: Create dynamic dashboards using Plotly Dash to visualize each of the technical indicators

  



## âš™ Setup and Installation

Ensure you have Python and MongoDB installed on your system. Install the necessary Python libraries using:



```bash

pip install pandas numpy seaborn matplotlib pymongo yfinance dash plotly talib

python dashboard.py

```



Feel free to fork this repository or contribute by providing suggestions to improve the analysis or adding new features to enhance the stock data exploration.



## Add a star 🌟 to the repo if u like it. 😃 Thank You !!