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A stochastic process is a collection of random variables usually indexed by a totally ordered set.

1 vote
1 answer
2k views

Mixing the Ornstein-Uhlenbeck Process and Geometric Brownian Motion

The Ornstein-Uhlenbeck process with mean reversion level 0 is defined as follows: $$dX_t=a X_t dt + \sigma_1 d W_{1t}. \tag{1} $$ Geometric Brownian motion is defined as follows: $$dX_t= a X_t dt + …
Julian Karch's user avatar
7 votes
1 answer
810 views

Solve SDE $dX_t=(c+\sigma_\zeta W'_t)X_tdt + \sigma_\epsilon dW_t$

I am trying to solve the following SDE $$dX_t=(c+\sigma_\zeta W'_tX_t)dt + \sigma_\epsilon dW_t$$ $c\in \mathbb{R}$ is a constant, $X_t$ is a stochastic process, $\sigma_\zeta,\sigma_\epsilon \in \ma …
Julian Karch's user avatar
1 vote
2 answers
1k views

Understanding the limits of the Ito Process Defintion

I would like to understand what kind of stochastic process are Ito Processes. According to Kuo[p. 102] an Ito Process is a stochastic process of the form $$dX_t=g(t)dt+f(t)dW(t),$$ where $W(t)$ is a …
Julian Karch's user avatar