Crypto Volatility Forecasting
Short-term volatility forecast using LSTM for crypto portfolio allocation
Situation
Client needed accurate short-term volatility forecasts for cryptocurrency portfolio allocation and risk management decisions.
Task
Develop ML model to predict daily volatility with high accuracy for real-time allocation decisions.
Action
Business & Strategy
Built interactive dashboard for real-time risk metrics and volatility forecasts. Created alert system for extreme volatility events.
Technical Implementation
Implemented LSTM model with windowed time-series inputs (14-day windows). Trained on 3+ years of crypto market data. Automated prediction pipeline via Google Colab scheduled jobs. Integrated with portfolio rebalancing system.
Results
Business Impact
Portfolio stability increased by 15%. Reduced drawdowns during high-volatility periods by 22%.
Technical Achievement
Achieved MSE < 0.05 on test set. Successfully automated end-to-end pipeline with 99% job success rate.