March 20, 2024

Forecasting Volatility Using Machine Learning

Comparing traditional models to the LSTM model, for predicting the volatility of equities

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.

Read the full article on AlphaLayer's Substack

Follow us on: