  Several authors have noticed the signature of log-periodic oscillations prior
to large stock market crashes [cond-mat/9509033, cond-mat/9510036, Vandewalle
et al 1998]. Unfortunately good fits of the corresponding equation to stock
market prices are also observed in quiet times. To refine the method several
approaches have been suggested:
  1) Logarithmic Divergence: Regard the limit where the critical exponent \beta
converges to 0.
  2) Universality: Define typical ranges for the free parameters, by observing
the best fit for historic crashes.
  We suggest a new approach. From the observation that the hazard-rate in
cond-mat/9510036 has to be a positive number, we get an inequality among the
free variables of the equation for stock-market prices.
  Checking 88 years of Dow-Jones-Data for best fits, we find that 25% of those
that satisfy our inequality, occur less than one year before a crash. We
compare this with other methods of crash prediction, i.p. the universality
method of Johansen et al., which are followed by a crash in only 9% of the
cases.
  Combining the two approaches we obtain a method whose predictions are
followed by crashes in 54% of the cases.
