Telling from Discrete Data Whether the Underlying Continuous-Time Model is a Diffusion

Yacine Ait-Sahalia

No 8504, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Asset returns have traditionally been modeled in the literature as following continuous-time Markov processes, and in many cases diffusions. Can discretely sampled financial rate data help us decide which continuous-time models are sensible? Diffusion processes are characterized by the continuity of their sample paths. This cannot be verified from the discrete sample path: by nature, even if the underlying sample path were continuous, the discretely sampled data will always appear as a sequence of discrete jumps. Instead, this paper relies on a characterization of the transition density of the discrete data to determine whether the discontinuities observed in the discrete data are the result of the discreteness of sampling, or rather evidence of genuine jump dynamics for the underlying continuous-time process. I then focus on the implications of this approach for option pricing models.

JEL-codes: G12 C22 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2001-10
Note: AP
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Journal Article: Telling from Discrete Data Whether the Underlying Continuous-Time Model Is a Diffusion (2002)
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