Stock

A stock is a traded ownership interest in a company. In a mathematical finance model, its price is a stochastic process and a self-financing portfolio may hold positive or negative numbers of its shares.

For $\alpha >0$, $\sigma >0$, this positive stochastic process is the exponential of an Ornstein-Uhlenbeck process. The Itô formula givesThe mean level of the logarithm differs from $\mu$ by the quadratic variation correction. In a stock model, specifying this under a physical probability measure does not by itself specify risk-neutral pricing. A non-dividend-paying traded stock has drift $rS$ under a risk-neutral measure; a different drift under that measure would require a corresponding dividend or carry convention.

For a log-mean-reverting price, set $a=e^{-\alpha (T-t)}$. The Ornstein-Uhlenbeck transition distribution gives conditional log-mean $a\log S_t+(1-a)\tilde{\mu }$ and log-variance ${\sigma }^2(1-a^2)/(2\alpha )$. The moment-generating function of a normal distribution therefore gives the displayed formula for $F(t,T)=\mathbb{E}[S_T\mid {\mathcal{F}}_t]$. It is a martingale in $t$ for fixed $T$, by the tower property of conditional expectation, and the Itô formula yieldsThis uses the same probability measure as the specified conditional expectation. It describes futures pricing only when that measure is an appropriate pricing measure, with the required cash-flow conventions. For a non-dividend-paying traded stock and constant interest rate, the forward contract delivery price follows the usual carry relation instead.

A proportional continuous dividend payment at rate $\delta$ per unit time relative to the ex-dividend stock price. The total gain of one share is $d{S}_t+\delta S_{t}dt$. Under a risk-neutral measure with short rate $r$, a geometric stock diffusion therefore has ex-dividend drift $(r-\delta )S_t$. A fixed cash dividend at a specified date is a different convention and generally requires an ex-dividend price jump.

For positive stocks satisfying $d{S}_t^i/S_t^i={\sum }_j{\sigma }_{ij}d{W}_t^j+{\mu }_{i}dt$, let $q=n^{-1}1$ and $V=\sigma {\sigma }^T$. The Itô formula givesThus its volatility is ${\sigma }^{T}q$. This geometric average is generally not the value of the constant equal-weight self-financing portfolio: its instantaneous drift is $q^T\mu -\mathrm{tr}(V)/(2n)+q^{T}Vq/2$, whereas the fully invested equal-weight portfolio has drift $q^T\mu$.

A stock model whose price can be killed or reduced at a default time. The zero-recovery default model combines continuous price dynamics before default with a jump to zero.

For an independent exponential distribution default time of rate $\lambda$ and a continuous nonnegative martingale $S$, this process is a martingale. The compensating pre-default factor $e^{\lambda t}$ balances the survival probability $e^{-\lambda t}$. The strict survival inequality gives a càdlàg price process.