Greeks (finance)

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In mathematical finance, the Greeks are the quantities representing the market sensitivities of derivatives such as options. Each "Greek" measures a different aspect of the risk in an option position, and corresponds to a parameter on which the value of an instrument or portfolio of financial instruments is dependent. The name is used because the parameters are often denoted by Greek letters.

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[edit] Use of the Greeks

The Greeks are vital tools in risk management. Each Greek (with the exception of theta - see below) represents a specific measure of risk in owning an option, and option portfolios can be adjusted accordingly ("hedged") to achieve a desired exposure; see for example Delta hedging.

As a result, a desirable property of a model of a financial market is that it allows for easy computation of the Greeks. The Greeks in the Black-Scholes model are very easy to calculate and this is one reason for the model's continued popularity in the market.

[edit] The Greeks

  • The delta measures the sensitivity to changes in the price of the underlying asset. The Δ of an instrument is the mathematical derivative of the option value V with respect to the underlyer's price, \Delta = \frac{\partial V}{\partial S}.
  • The gamma measures the rate of change in the delta. The Γ is the second derivative of the value function with respect to the underlying price, \Gamma = \frac{\partial^2 V}{\partial S^2}. Gamma is important because it indicates how a portfolio will react to relatively large shifts in price.
  • The vega, which is not a Greek letter (ν, nu is used instead), measures sensitivity to volatility. The vega is the derivative of the option value with respect to the volatility of the underlying, \nu=\frac{\partial V}{\partial \sigma}. The term kappa, κ, is sometimes used instead of vega, as is tau, τ, though this is rare.
  • The speed measures third order sensitivity to price. The speed is the third derivative of the value function with respect to the underlying price, \frac{\partial^3 V}{\partial S^3}.


  • The theta measures sensitivity to the passage of time (see Option time value). Θ is the negative of the derivative of the option value with respect to the amount of time to expiry of the option, \Theta = -\frac{\partial V}{\partial T}.
  • The rho measures sensitivity to the applicable interest rate. The ρ is the derivative of the option value with respect to the risk free rate, \rho = \frac{\partial V}{\partial r}.
  • Less commonly used:
    • The lambda λ is the percentage change in option value per change in the underlying price, or \lambda = \frac{\partial V}{\partial S}\times\frac{1}{V}. It is the logarithmic derivative.
    • The vega gamma or volga measures second order sensitivity to implied volatility. This is the second derivative of the option value with respect to the volatility of the underlying, \frac{\partial^2 V}{\partial \sigma^2}.
    • The vanna measures cross-sensitivity of the option value with respect to change in the underlying price and the volatility, \frac{\partial^2 V}{\partial S \partial \sigma}, which can also be interpreted as the sensitivity of delta to a unit change in volatility.
    • The delta decay, or charm, measures the time decay of delta, \frac{\partial \Delta}{\partial T} = \frac{\partial^2 V}{\partial S \partial T}. This can be important when hedging a position over a weekend.
    • The color measures the sensitivity of the charm, or delta decay to the underlying asset price, \frac{\partial^3 V}{\partial S^2 \partial T}. It is the third derivative of the option value, twice to underlying asset price and once to time.

[edit] Black-Scholes

The Greeks under the Black-Scholes model are calculated as follows, where φ (phi) is the standard normal probability density function and Φ is the standard normal cumulative distribution function. Note that the gamma and vega formulas are the same for calls and puts.

For a given: Stock Price  S \, , Strike Price  K \, , Risk-Free Rate  r \, , Annual Dividend Yield  q \, , Time to Maturity,  \tau = T-t \, , and Volatility  \sigma \, ...

Calls Puts
value  e^{-q \tau} S\Phi(d_1) - e^{-r \tau} K\Phi(d_2) \,  e^{-r \tau} K\Phi(-d_2) - e^{-q \tau} S\Phi(-d_1)  \,
delta  e^{-q \tau} \Phi(d_1) \,  -e^{-q \tau} \Phi(-d_1) \,
gamma  e^{-q \tau} \frac{\phi(d_1)}{S\sigma\sqrt{\tau}} \,
vega  S e^{-q \tau} \phi(d_1) \sqrt{\tau} \,
theta  -e^{-q \tau} \frac{S \phi(d_1) \sigma}{2 \sqrt{\tau}} - rKe^{-r \tau}\Phi(d_2) + qSe^{-q \tau}\Phi(d_1) \,  -e^{-q \tau} \frac{S \phi(d_1) \sigma}{2 \sqrt{\tau}} + rKe^{-r \tau}\Phi(-d_2) - qSe^{-q \tau}\Phi(-d_1) \,
rho  K \tau e^{-r \tau}\Phi(d_2)\,  -K \tau e^{-r \tau}\Phi(-d_2) \,
volga  Se^{-q \tau} \phi(d_1) \sqrt{\tau} \frac{d_1 d_2}{\sigma} = \nu  \frac{d_1 d_2}{\sigma} \,
vanna  -e^{-q \tau} \phi(d_1) \frac{d_2}{\sigma} \, = \frac{\nu}{S}\left[1 - \frac{d_1}{\sigma\sqrt{\tau}} \right]\,
charm  -qe^{-q \tau} \Phi(d_1) + e^{-q \tau} \phi(d_1) \frac{2(r-q) \tau - d_2 \sigma \sqrt{\tau}}{2\tau \sigma \sqrt{\tau}} \,  qe^{-q \tau} \Phi(-d_1) + e^{-q \tau} \phi(d_1) \frac{2(r-q) \tau - d_2 \sigma \sqrt{\tau}}{2\tau \sigma \sqrt{\tau}} \,
color  -e^{-q \tau} \frac{\phi(d_1)}{2S\tau \sigma \sqrt{\tau}} \left[2q\tau + 1 + \frac{2(r-q) \tau - d_2 \sigma \sqrt{\tau}}{\sigma \sqrt{\tau}}d_1 \right] \,
dual delta  -e^{-r \tau} \Phi(d_2) \,  e^{-r \tau} \Phi(-d_2) \,
dual gamma  e^{-r \tau} \frac{\phi(d_2)}{K\sigma\sqrt{\tau}} \,

where

 d_1 = \frac{\ln(S/K) + (r - q + \sigma^2/2)\tau}{\sigma\sqrt{\tau}}
 d_2 = \frac{\ln(S/K) + (r - q - \sigma^2/2)\tau}{\sigma\sqrt{\tau}} = d_1 - \sigma\sqrt{\tau}
 \phi(x) = \frac{e^{- \frac{x^2}{2}}}{\sqrt{2 \pi}}
 \Phi(x) = \int_{-\infty}^x \frac{e^{- \frac{y^2}{2}}}{\sqrt{2 \pi}} \,dy = \int_{-x}^{\infty} \frac{e^{- \frac{y^2}{2}}}{\sqrt{2 \pi}} \,dy

[edit] See also

[edit] External links