mean and variance of the SDE $dy_{t}=\nu(\mu-y_{t})dt+J_{t}dN_{t}\sigma dW_{t}$

104 Views Asked by At

Say I have an SDE as follows:

$$dy_{t}=\theta(\mu-y_{t})dt+J_{t}dN_{t}\sigma dW_{t} \tag{1}$$

where dW is a standard Wiener process and dN is a Poisson process with arrival rate $\lambda$.

How do I then find the mean and the variance? If possible at all?

As the Wiener process is multiplied with the jump I am not sure how to start using stochastic calculus. One idea is to log everything so I can treat each component individually, but am not sure that would work.

Any help is highly appreciated :)

1

There are 1 best solutions below

6
On

I would like to comment, but I am not among the privileged, so I answer:

Do you think that summing a product involving one (stochastic) differential with another product involving two (stochastic) differentials yields a well-defined expression?