# Hunt process

In probability theory, a Hunt process is a strong Markov process which is quasi-left continuous with respect to the minimum completed admissible filtration ${\displaystyle \{F_{t}\}_{t\geq 0}}$.

It is named after Gilbert Hunt.

## References

• Chung, Kai Lai; Walsh, John B. (2006), "Chapter 3. Hunt Process", Markov Processes, Brownian Motion, and Time Symmetry, Grundlehren der mathematischen Wissenschaften, 249 (2nd ed.), Springer, pp. 75ff, ISBN 9780387286969
• Krupka, Demeter (2000), Introduction to Global Variational Geometry, North-Holland Mathematical Library, 23, Elsevier, pp. 87ff, ISBN 9780080954295
• Applebaum, David (2009), Lévy Processes and Stochastic Calculus, Cambridge Studies in Advanced Mathematics, Cambridge University Press, p. 196, ISBN 9780521738651