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Local volatility : ウィキペディア英語版
Local volatility
A local volatility model, in mathematical finance and financial engineering, is one that treats volatility as a function of both the current asset level S_t and of time t . As such, a local volatility model is a generalisation of the Black-Scholes model, where the volatility is a constant (i.e. a trivial function of S_t and t ).
==Formulation==
In mathematical finance, the asset ''S''''t'' that underlies a financial derivative, is typically assumed to follow a stochastic differential equation of the form
: dS_t = (r_t-d_t) S_t\,dt + \sigma_t S_t\,dW_t ,
where r_t is the instantaneous risk free rate, giving an average local direction to the dynamics, and W_t is a Wiener process, representing the inflow of randomness into the dynamics. The amplitude of this randomness is measured by the instant volatility \sigma_t. In the simplest model i.e. the Black-Scholes model, \sigma_t is assumed to be constant; in reality, the realized volatility of an underlying actually varies with time.
When such volatility has a randomness of its own—often described by a different equation driven by a different ''W''—the model above is called a stochastic volatility model. And when such volatility is merely a function of the current asset level ''S''''t'' and of time ''t'', we have a local volatility model. The local volatility model is a useful simplification of the stochastic volatility model.
"Local volatility" is thus a term used in quantitative finance to denote the set of diffusion coefficients, \sigma_t = \sigma(S_t,t), that are consistent with market prices for all options on a given underlying. This model is used to calculate exotic option valuations which are consistent with observed prices of vanilla options.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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