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mathematical finance Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling in the financial field. In general, there exist two separate branches of finance that req ...
, the CEV or constant elasticity of
variance In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation (SD) is obtained as the square root of the variance. Variance is a measure of dispersion ...
model is a
stochastic volatility In statistics, stochastic volatility models are those in which the variance of a stochastic process is itself randomly distributed. They are used in the field of mathematical finance to evaluate derivative securities, such as options. The name ...
model, although technically it would be classed more precisely as a
local volatility A local volatility model, in mathematical finance and financial engineering, is an option pricing model that treats Volatility (finance), volatility as a function of both the current asset level S_t and of time t . As such, it is a generalisati ...
model, that attempts to capture stochastic volatility and the leverage effect. The model is widely used by practitioners in the financial industry, especially for modelling
equities Stocks (also capital stock, or sometimes interchangeably, shares) consist of all the shares by which ownership of a corporation or company is divided. A single share of the stock means fractional ownership of the corporation in proportion t ...
and
commodities In economics, a commodity is an economic good, usually a resource, that specifically has full or substantial fungibility: that is, the market treats instances of the good as equivalent or nearly so with no regard to who produced them. Th ...
. It was developed by John Cox in 1975.


Dynamic

The CEV model is a stochastic process which evolves according to the following
stochastic differential equation A stochastic differential equation (SDE) is a differential equation in which one or more of the terms is a stochastic process, resulting in a solution which is also a stochastic process. SDEs have many applications throughout pure mathematics an ...
: :\mathrmS_t = \mu S_t \mathrmt + \sigma S_t ^ \mathrmW_t in which ''S'' is the spot price, ''t'' is time, and ''μ'' is a parameter characterising the drift, ''σ'' and ''γ'' are volatility parameters, and ''W'' is a Brownian motion. It is a special case of a general
local volatility A local volatility model, in mathematical finance and financial engineering, is an option pricing model that treats Volatility (finance), volatility as a function of both the current asset level S_t and of time t . As such, it is a generalisati ...
model, written as :\mathrmS_t = \mu S_t \mathrmt + v(t,S_t) S_t \mathrmW_t where the price return volatility is :v(t, S_t)=\sigma S_t^ The constant parameters \sigma,\;\gamma satisfy the conditions \sigma\geq 0,\;\gamma\geq 0. The parameter \gamma controls the relationship between volatility and price, and is the central feature of the model. When \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. Conversely, in commodity markets, we often observe \gamma > 1,Geman, H, and Shih, YF. 2009. "Modeling Commodity Prices under the CEV Model." The Journal of Alternative Investments 11 (3): 65–84. whereby the volatility of the price of a commodity tends to increase as its price increases and leverage ratio decreases. If we observe \gamma = 1 this model becomes a
geometric Brownian motion A geometric Brownian motion (GBM) (also known as exponential Brownian motion) is a continuous-time stochastic process in which the logarithm of the randomly varying quantity follows a Brownian motion (also called a Wiener process) with drift. It ...
as in the Black-Scholes model, whereas if \gamma = 0 and either \mu = 0 or the drift \mu S is replaced by \mu, this model becomes an arithmetic Brownian motion, the model which was proposed by
Louis Bachelier Louis Jean-Baptiste Alphonse Bachelier (; 11 March 1870 – 28 April 1946) was a French mathematician at the turn of the 20th century. He is credited with being the first person to model the stochastic process now called Brownian motion, as part ...
in his PhD Thesis "The Theory of Speculation", known as
Bachelier model The Bachelier model is a model of an asset price under Brownian motion presented by Louis Bachelier on his PhD thesis ''The Theory of Speculation'' (''Théorie de la spéculation'', published 1900). It is also called "Normal Model" equivalently ( ...
.


See also

*
Volatility (finance) In finance, volatility (usually denoted by "sigma, σ") is the Variability (statistics), degree of variation of a trading price series over time, usually measured by the standard deviation of logarithmic returns. Historic volatility measures a t ...
*
Stochastic volatility In statistics, stochastic volatility models are those in which the variance of a stochastic process is itself randomly distributed. They are used in the field of mathematical finance to evaluate derivative securities, such as options. The name ...
*
Local volatility A local volatility model, in mathematical finance and financial engineering, is an option pricing model that treats Volatility (finance), volatility as a function of both the current asset level S_t and of time t . As such, it is a generalisati ...
*
SABR volatility model In mathematical finance, the SABR model is a stochastic volatility model, which attempts to capture the volatility smile in derivatives markets. The name stands for "stochastic alpha, beta, rho", referring to the parameters of the model. The SABR ...
* CKLS process


References


External links


Asymptotic Approximations to CEV and SABR ModelsPrice and implied volatility under CEV model with closed formulas, Monte-Carlo and Finite Difference MethodPrice and implied volatility of European options in CEV Model
delamotte-b.fr {{Stochastic processes Options (finance) Derivatives (finance) Financial models