Risk-Sensitive Specialist Routing for Volatility Forecasting

TL;DR

This paper introduces a risk-sensitive specialist routing framework for ETF volatility forecasting that adapts to changing market states, significantly improving forecast accuracy during volatile periods.

Contribution

The paper develops a novel online risk-sensitive routing framework that dynamically combines specialists based on market regime, enhancing volatility forecast accuracy.

Findings

Routing reduces high-volatility forecast loss by about 24%.

Routing reduces underprediction loss by about 22%.

The strongest forecaster varies with market regime.

Abstract

Volatility forecasting becomes challenging when market conditions shift and model performance varies across market states. Motivated by this instability, we develop a risk-sensitive specialist routing framework for ETF volatility forecasting. The framework uses online risk-sensitive evaluation and state-dependent gating to combine different forecasting specialists across calm and stressed market states. Using a daily panel of six ETFs under a rolling walk-forward design, we find that the strongest forecaster is regime-dependent rather than stable across all states. Relative to the rolling-best baseline, the proposed routing framework reduces high-volatility forecast loss by about 24% and underprediction loss by about 22%. These results suggest that specialist routing provides a practical forecasting architecture that adapts to changing market conditions.