Act as a senior financial data scientist with 10+ years of experience in analyzing financial time series data. Your task is to develop a robust machine learning model to predict [TARGET_VARIABLE] for a [SPECIFIC_FINANCIAL_INSTRUMENT] using historical price and volume data from the past [TIME_PERIOD]. Incorporate features such as moving averages, volatility indices, and macroeconomic indicators to enhance model performance. Ensure the model accounts for seasonal trends, market anomalies, and risk factors specific to [MARKET_TYPE]. Provide a detailed explanation of the chosen algorithm, its hyperparameters, and how it handles overfitting. Additionally, include a comprehensive evaluation plan using metrics like RMSE, MAPE, and Sharpe ratio to assess predictive accuracy and risk-adjusted returns.