Sentiment‐driven mean reversion in the 4/2 stochastic volatility model with jumps

Abstract

SummaryWith the availability of social networks, specialized forums, and online news, sentiment analysis has become a common and useful technique for the analysis of economic and financial scenarios. Several data‐providers have also started computing proprietary sentiment indexes on financial assets to be delivered together with market price and trading volume. We develop a modified version of the mean‐reverting 4/2 stochastic volatility model introduced in Escobar‐Anel & Gong (2020) to describe the dynamics of commodities. In our specification, jumps are allowed in the asset price dynamics, and the drift coefficient may also switch between regimes related to a sentiment indicator. In this framework, we discuss the distributional characteristics of asset returns, provide a numerical procedure for model estimation, and give some preliminary results on the pricing of European‐style derivatives. Finally, the model is fitted to the market data for Gold and Crude Oil.

Probabilistic and statistical methods in commodity risk management

“…We notice that the attention paid by Cretarola et al 4 to volatility models lets this paper be close to Gianfreda and Scandolo 5 and Bonnini et al, 6 where the authors deal with risk and price volatility.…”

“…Interestingly, Clemente et al 3 and Cretarola et al 4 provide a network‐based perspective of the dynamics of the commodities and of the energy system.…”

“…Cretarola et al 4 explore sentiment analysis as a valuable technique for analyzing economic and financial scenarios in the context of social networks, specialized forums, and online news. To capture the dynamics of commodities, the authors modify the mean‐reverting 4/2 stochastic volatility model introduced in a prior study.…”