1
Allameh Tabataba'i Universty, Department of Mathematics
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Allameh Tabataba'i Universty, Department of Mathematics
10.22124/jmm.2025.29881.2667
Abstract
Implied volatility is a crucial indicator in financial markets, as it reflects market expectations of future volatility and serves as a cornerstone for option pricing, risk management, and asset allocation. Accurate tracking and forecasting of implied volatility are essential for investors and portfolio managers to optimize returns and manage risks effectively. This paper explores several modeling approaches for forecasting the implied volatility of the S\&P 500 index, focusing on exponential autoregressive conditional heteroskedasticity (EGARCH), long short-term memory (LSTM) neural networks, and a non-linear autoregressive model with exogenous inputs (NARX). In addition, a rough fractional stochastic volatility (RFSV) model is also examined. The empirical study demonstrates that the LSTM model offers superior forecasting performance compared to EGARCH, NARX, and RFSV. These findings have important implications for practitioners and researchers aiming to enhance risk management and trading strategies.
Modarresi, N. , Kazemi, R. and Mousavi, A. (2025). Enhancing implied volatility forecasting: multi-model approaches for the S\&P500 index. Journal of Mathematical Modeling, (), -. doi: 10.22124/jmm.2025.29881.2667
MLA
Modarresi, N. , , Kazemi, R. , and Mousavi, A. . "Enhancing implied volatility forecasting: multi-model approaches for the S\&P500 index", Journal of Mathematical Modeling, , , 2025, -. doi: 10.22124/jmm.2025.29881.2667
HARVARD
Modarresi, N., Kazemi, R., Mousavi, A. (2025). 'Enhancing implied volatility forecasting: multi-model approaches for the S\&P500 index', Journal of Mathematical Modeling, (), pp. -. doi: 10.22124/jmm.2025.29881.2667
CHICAGO
N. Modarresi , R. Kazemi and A. Mousavi, "Enhancing implied volatility forecasting: multi-model approaches for the S\&P500 index," Journal of Mathematical Modeling, (2025): -, doi: 10.22124/jmm.2025.29881.2667
VANCOUVER
Modarresi, N., Kazemi, R., Mousavi, A. Enhancing implied volatility forecasting: multi-model approaches for the S\&P500 index. Journal of Mathematical Modeling, 2025; (): -. doi: 10.22124/jmm.2025.29881.2667
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