Forecasting Volatility Using Machine Learning

Understanding the volatility of financial assets is important for several reasons:

• Risk management: Volatility is a key measure of risk. Measures such as VaR (value at risk) depend on accurate future measures of volatility.
• Asset allocation: Volatility is often a key input in portfolio construction and optimization. For example, for risk parity portfolios or mean-variance optimization.
• Derivates pricing: The prices of derivative contracts, for example, options, are directly linked to expectations of future volatility of the underlying.
• Market making: Forecasting bid / ask spreads is crucial to the market maker’s ability to maintain a liquid book. Spreads are influenced by volatility.

Given this importance, historically there has been an interest in forecasting future financial asset price volatility.

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