Financial time series data commonly exhibit heteroskedasticity and volatility clustering. What significant advantages do GARCH models offer over traditional ARMA models for analyzing this type of data? Please explain the basic principles of GARCH models, discuss common variants, and elaborate on how you would select and evaluate an appropriate GARCH model in a practical application.

金融时间序列数据普遍存在异方差性（heteroskedasticity）和波动率聚类（volatility clustering）现象。你认为GARCH模型在这类数据分析中相较于传统的ARMA模型有哪些显著优势？请阐述GARCH模型的基本原理、常见变体以及在实际应用中如何选择和评估一个合适的GARCH模型。