Bitcoin Trading Volume Prediction: Navigating the Cryptocurrency Seas with Time Series Analysis Dive into the turbulent waters of Bitcoin trading with this project, uncovering hidden patterns and predicting future volume trends through the power of time series analysis and machine learning.
The Quest:
Bitcoin, the digital gold, boasts a price that dances to its own tune. But what about its trading volume? Can we chart a course through the waves of buyer and seller activity, forecasting future peaks and troughs? This project is your compass, equipped with time series analysis techniques and machine learning models to decipher the cryptic language of volume fluctuations.
Our Voyage Begins:
Unveiling the Secrets: We'll start by scrubbing the historical data, prepping it for analysis just like a pirate cleans their trusty map. Missing values and anomalies will be cast overboard, leaving only a clean chart to guide our way. Exploring the Uncharted: Visualizations become our telescope, revealing trends, seasonality, and volatility lurking beneath the surface. Statistical tests, our sextant, help us navigate through murky waters of stationarity and autocorrelation. Charting the Course: Feature engineering becomes our cartographer, crafting informative features from the time series data like lags, rolling windows, and technical indicators – our treasure chest of insights. Raising the Jolly Roger: Various forecasting models, our trusty fleet, will be deployed – ARIMA, SARIMA, Holt-Winters, and even machine learning approaches. We'll tune their hyperparameters like adjusting the sails, optimizing their performance for accurate predictions. Treasure Ahoy!: RMSE, our compass needle, will point us towards the most accurate model. But the bounty doesn't stop there! We'll delve into the model's results, understanding the influential factors driving volume dynamics and uncovering valuable insights into Bitcoin market behavior.