Corollary: lognormal property of \(S\) - 2023.2 English

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Release Date
2023-12-20
Version
2023.2 English

Let us define \(G = \ln S\). With \(Ito\) lemma, we have

\[dG = (\mu - \frac{\sigma^2}{2}) dt + \sigma dz,\]

using

\[\frac{\partial G}{\partial S} = \frac{1}{S}, \frac{\partial^2 G}{\partial S^2} = -\frac{1}{S^2}, \frac{\partial G}{\partial t} = 0.\]

Thus

\[\ln S_T - \ln S_0 \sim \phi [(\mu-\frac{\sigma^2}{2})T, \sigma^2 T].\]

where \(S_T\) is the stock price at a future time \(T\), \(S_0\) is the stock price at time 0. In other words, \(S_T\) has a lognormal distribution, which can take any value between 0 and \(+\infty\).