Due to the file size the notebook it may not show on github, so here is the direct link of the notebook hosted on kaggle:
https://www.kaggle.com/code/ilariaenache/eth-prediction-dv-project#Forecasting-with-Prophet
Ethereum, a decentralized blockchain platform, has gained significant traction since its proposal by programmer Vitalik Buterin in 2013. With its native cryptocurrency, Ether (ETH), Ethereum stands as one of the leading cryptocurrencies by market capitalization, second only to Bitcoin. Analyzing Ethereum's market behavior is crucial for investors, traders, and stakeholders to understand its trends and potential investment opportunities.
The provided script entails a comprehensive analysis of Ethereum market data, starting with data normalization using the min-max function. This normalization technique scales each feature's values to a range between 0 and 1, aiding in the comparison and interpretation of different variables.
The analysis delves into the multivariate distribution of Ethereum market features through the covariance matrix and descriptive statistics. Shapiro-Wilk tests affirm the normality of the data, ensuring its suitability for further statistical analysis.
Data cleaning procedures involve filtering out empty rows/columns and removing duplicates, ensuring the integrity and accuracy of the dataset. Additionally, date conversion and handling missing values are performed to prepare the data for analysis.
Various visualizations are employed to depict Ethereum's market behavior over time. Price charts, volume trends, and correlations between market features are visually represented, providing insights into Ethereum's price movements and trading activities.
The analysis explores different model selection techniques, including stepwise regression using backward, forward, and sequential selection methods. Through these techniques, the most influential predictors for forecasting Ethereum prices are identified, enhancing the accuracy of predictive models.
Utilizing time series analysis, the script forecasts Ethereum high prices, incorporating advanced techniques such as differencing and Box-Cox transformations to ensure stationarity and model stability. These forecasts offer valuable insights for investors and stakeholders to make informed decisions.
By providing a comprehensive analysis of Ethereum's market behavior and forecasting future price trends, this analysis equips investors, traders, and stakeholders with valuable insights to navigate the volatile cryptocurrency market effectively. Understanding Ethereum's past trends and predicting future price movements are critical for optimizing investment strategies and mitigating risks.
The analysis utilizes Ethereum market data, including high, low, open, close prices, trading volume, and market capitalization. The dataset spans a significant timeframe, capturing Ethereum's market evolution over several years and enabling robust statistical analysis and forecasting.