Stochastic discount factor

The concept of the stochastic discount factor (SDF) is used in financial economics and mathematical finance. The name derives from the price of an asset being computable by "discounting" the future cash flow ${\displaystyle {\tilde {x}}_{i}}$ by the stochastic factor ${\displaystyle {\tilde {m}}}$, and then taking the expectation.^[1] This definition is of fundamental importance in asset pricing.

If there are n assets with initial prices ${\displaystyle p_{1},\ldots ,p_{n}}$ at the beginning of a period and payoffs ${\displaystyle {\tilde {x}}_{1},\ldots ,{\tilde {x}}_{n}}$ at the end of the period (all xs are random (stochastic) variables), then SDF is any random variable ${\displaystyle {\tilde {m}}}$ satisfying

${\displaystyle E({\tilde {m}}{\tilde {x}}_{i})=p_{i},{\text{for }}i=1,\ldots ,n.}$

The stochastic discount factor is sometimes referred to as the pricing kernel as, if the expectation ${\displaystyle E({\tilde {m}}\,{\tilde {x}}_{i})}$ is written as an integral, then ${\displaystyle {\tilde {m}}}$ can be interpreted as the kernel function in an integral transform.^[2] Other names sometimes used for the SDF are the "marginal rate of substitution" (the ratio of utility of states, when utility is separable and additive, though discounted by the risk-neutral rate), a "change of measure", "state-price deflator" or a "state-price density".^[2]