- #1

vale

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I've very little time to figure out the following problem ... and I am wandering if some of you can give me any help or just suggest me any good reading material...

The question is how you can prove a process [tex] P_t[/tex], given the dynamics, is Markov.

In short my process is on alternate intervals, a

**mean reverting brownian bridge**[tex]dP_t = \frac{\alpha}{G-t}(Q-P_t)dt + \sigma dW_t [/tex], and a

**mean reverting proportional volatility**process : [tex]dP_t = K(\theta -P_t)dt + \nu dW_t [/tex]. The length of the intervals and their occurence is determined by an exogenous bootstrap procedure, which I believe, doesn't give any problems, being a resampling procedure with replacement, it doesn't generate any dependence with the past history...

How should I procede on your opinion? Any hints ?

Thank you very much in advance,

Vale