Generalized Wiener process

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In statistics, a generalized Wiener process^[1] (named after Norbert Wiener) is a continuous time random walk with drift and random jumps at every point in time. Formally:

${\displaystyle a(x,t)dt+b(x,t)\eta {\sqrt {dt}}}$

where a and b are deterministic functions, t is a continuous index for time, x is a set of exogenous variables that may change with time, dt is a differential in time, and η is a random draw from a standard normal distribution at each instant.

1. ^ "Stochastic Processes and Monte Carlo Method | Introduction To Options on QuantConnect". quantconnect.com. Retrieved 13 September 2025.

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