Threshold Random Walks in the U.S. Stock Market
AbstractThis paper extends the work in Serletis and Shintani (2003) and Elder and Serletis ( 2006) by re-examining the empirical evidence for random walk type behavior in the U.S. stock market. In doing so, it tests the random walk hypothesis by employing unit-root tests that are designed to have more statistical power against nonlinear al- ternatives. The nonlinear feature of our model is re ected by three regimes, one of which is characterized by a unit root process and the random walk hypothesis while the lower and upper regimes are well captured by a stationary autoregressive process with mean reversion and predictability.
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Bibliographic InfoPaper provided by Brock University, Department of Economics in its series Working Papers with number 0602.
Length: 12 pages
Date of creation: May 2006
Date of revision: May 2006
Publication status: Published in Chaos, Solitons & Fractals, 2008, vol. 37, pages 43-48
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More information through EDIRC
Asymmetric time series; Threshold adjustment; Nonlinear autoregression Autoregression;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
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