STATIONARY PROCESSES THAT LOOK LIKE RANDOM WALKS— THE BOUNDED RANDOM WALK PROCESS IN DISCRETE AND CONTINUOUS TIME
Several economic and financial time series are bounded by an upper and lower finite limit (e.g., interest rates). It is not possible to say that these time series are random walks because random walks are limitless with probability one (as time goes to infinity). Yet, some of these time series behav...
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Published in: | Econometric theory 2002-02, Vol.18 (1), p.99-118 |
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Main Author: | |
Format: | Article |
Language: | eng |
Subjects: | |
Online Access: | Get full text |
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Summary: | Several economic and financial time series are bounded by an
upper and lower finite limit (e.g., interest rates). It is not
possible to say that these time series are random walks because
random walks are limitless with probability one (as time goes
to infinity). Yet, some of these time series behave just like
random walks. In this paper we propose a new approach that takes
into account these ideas. We propose a discrete-time and a
continuous-time process (diffusion process) that generate bounded
random walks. These paths are almost indistinguishable from
random walks, although they are stochastically bounded by an
upper and lower finite limit. We derive for both cases the ergodic
conditions, and for the diffusion process we present a closed
expression for the stationary distribution. This approach suggests
that many time series with random walk behavior can in fact
be stationarity processes. |
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ISSN: | 0266-4666 1469-4360 |