This repository contains a time series forecasting project where I applied ARIMA and SARIMA models to predict Novo Nordisk stock prices. The dataset was sourced from Yahoo Finance.
Problem Statement
The goal of this project is to perform a daily forecast for one month on Novo Nordisk stock data.
NOTE: Novo Nordisk is a global healthcare company specializing in diabetes care medications and devices.
Data Details
- Company: Novo Nordisk
- Data Range: 10 years
- Source: Yahoo Finance Novo Nordisk Historical Data
Approach
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Data Collection: Acquired stock price data for Novo Nordisk from Yahoo Finance.
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Data Transformation: Performed a log transformation to address skewness in the data. The reasons for this transformation are briefly discussed in the notebook.
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Model Implementation: Implemented ARIMA and SARIMA models on both the original and transformed data.
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Results: Compared the performance of models using both the actual and transformed data.
Key Findings
Based on the analysis and results presented in the notebook:
- Log Transformed Data: The models performed better with the log-transformed data. This transformation helped to stabilize variance and improve model accuracy.
- Original Data: The models showed less reliable results when applied to the untransformed data.
For detailed reasons behind the preference for transformed data and an in-depth analysis of the models' performance, please refer to the notebook included in this repository.
Thank you!