Abstract
We introduce in this article the EWMA Heston model, a markovian stochastic volatility model able to capture the main empirical features related to volatility dynamics while being more tractable for simulations than rough volatility models based on fractional processes. After having presented the model and its principal characteristics, we focus our analysis on the use of its associated Euler-discretization scheme as a time-series generator for Monte-Carlo simulations. Using this discretization scheme, and on the basis of S&P500 empirical time series, we show that the EWMA Heston model is remarkably consistent with market data, putting it as a potential competitor for rough and super-Heston rough volatility models.
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