GS-Stock-Market-Time-Series-Analysis

This is an Analysis on Goldman Sachs Group Inc Stock Market Time Series featuring Prices starting from 2016 to present date
This Project was created using R Language and run using Google Colab Environment
Various Libraries such as Quantmod, Forecast and Anomaly Detection has been used

Stock Market Analysis_Exploratory Data Analysis

GRAPH FOR High, low, Close, Adjusted, Volume OF EACH DAY OVER 2016 - TODAYS DATE
CHARTS FOR OVERALL STOCK ANALYSIS FOR EACH YEAR (2016-2020) featuring
- Bollinger Band
- Momentum
- Price Rate of Change (ROC)

Stock Return Behaviour using logarithm properties to calculate the log-return of the stock
Forecasting Using
- ARIMA Model
- K Nearest Neighbours
- Feed Foward Neural network

Used Business Science : Tidy anomaly detection
Techniques Used
- Normal Anomaly Detection
- Decomposed Anomaly Detection with Trend and Seasonality Adjusted
- Detection with 5% and 15% Anomalies Allowed
- STL Decomposition Method vs Twitter Decomposition Method

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
README.md		README.md
Stock_Market_Analysis_Exploratory_Data_Analysis.ipynb		Stock_Market_Analysis_Exploratory_Data_Analysis.ipynb
Stock_Market_Analysis_Time_Series_Analysis_and_Forecasting.ipynb		Stock_Market_Analysis_Time_Series_Analysis_and_Forecasting.ipynb
Stock_Prices_Anomaly_Detection.ipynb		Stock_Prices_Anomaly_Detection.ipynb
stock_market_analysis_exploratory_data_analysis.R		stock_market_analysis_exploratory_data_analysis.R
stock_market_analysis_time_series_analysis_and_forecasting.R		stock_market_analysis_time_series_analysis_and_forecasting.R
stock_prices_anomaly_detection.R		stock_prices_anomaly_detection.R