So far, we have worked with option pricing models under the constant volatility assumption (Black–Scholes). However, in real markets, volatility is neither constant nor predictable—it is itself random and time-varying. To capture this, we turn to stochastic volatility models, which allow volatility to evolve dynamically as a stochastic process. These models provide more realistic pricing and risk management by explaining phenomena such as volatility clustering, skew, and smiles.