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Table 13 Competing models vs. random walk for positive and negative forecast errors

From: Great expectations? evidence from Colombia’s exchange rate survey

  Positive forecast errors Negative forecast errors
1-Month 1-Year 1-Month 1-Year
Extrapolative 0.0003 (0.001) 0.19*** (0.035) −0.0003 (0.001) 0.21*** (0.046)
Adaptive 0.0002 (0.001) 0.17*** (0.033) −0.0002 (0.001) 0.31*** (0.051)
Regressive 0.0001 (0.001) 0.11*** (0.032) 0.0009 (0.001) 0.06*** (0.022)
Forward discount 0.008*** (0.002) 0.01 (0.015) −0.001 (0.001) −0.005 (0.012)
Surveyed expectations     
All Participants 0.001*** (0.000) −0.06 (0.087) 0.006*** (0.002) −0.015 (0.017)
Commercial banks 0.009*** (0.002) −0.03 (0.094) 0.007*** (0.002) 0.019 (0.021)
Stockbrokers 0.010*** (0.002) −0.054 (0.082) 0.006*** (0.002) 0.013 (0.015)
Pension funds 0.011*** (0.003) 0.068 (0.139) 0.005*** (0.002) 0.011 (0.025)
  1. Source: authors’ calculations. All estimations correspond to rolling regressions. Values correspond to \(\left( MSPE_{r}-MSPE_{u}\right)\), where \(MSPE_{r}\) and \(MESPE_{u}\) correspond to “restricted” (Random Walk) and “unrestricted” (competing strategies) models. Methodology follows that of Clark and West (2006). Standard errors are in parenthesis
  2. ***, **, * correspond to significance levels of 1, 5 and 10 %, respectively