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In finance, the Heston model, named after Steven L. Heston, is a mathematical model that describes the evolution of the volatility of an underlying asset. [1] It is a stochastic volatility model: such a model assumes that the volatility of the asset is not constant, nor even deterministic, but follows a random process.
Volatility as described here refers to the actual volatility, more specifically: . actual current volatility of a financial instrument for a specified period (for example 30 days or 90 days), based on historical prices over the specified period with the last observation the most recent price.
The volatility of volatility controls its curvature. The above dynamics is a stochastic version of the CEV model with the skewness parameter β {\displaystyle \beta } : in fact, it reduces to the CEV model if α = 0 {\displaystyle \alpha =0} The parameter α {\displaystyle \alpha } is often referred to as the volvol , and its meaning is that of ...
A local volatility model, in mathematical finance and financial engineering, is an option pricing model that treats volatility as a function of both the current asset level and of time . As such, it is a generalisation of the Black–Scholes model , where the volatility is a constant (i.e. a trivial function of S t {\displaystyle S_{t}} and t ...
Volatility risk is the risk of an adverse change of price, due to changes in the volatility of a factor affecting that price. It usually applies to derivative instruments , and their portfolios, where the volatility of the underlying asset is a major influencer of option prices .
The main idea behind these two models is that volatility is dependent upon past realizations of the asset process and related volatility process. This is a more precise formulation of the intuition that asset volatility tends to revert to some mean rather than remaining constant or moving in monotonic fashion over time.
The parameter controls the relationship between volatility and price, and is the central feature of the model. When γ < 1 {\displaystyle \gamma <1} we see an effect, commonly observed in equity markets, where the volatility of a stock increases as its price falls and the leverage ratio increases. [ 3 ]
The volatilities in the market for 90 days are 18% and for 180 days 16.6%. In our notation we have , = 18% and , = 16.6% (treating a year as 360 days). We want to find the forward volatility for the period starting with day 91 and ending with day 180.