  The online search problem is a fundamental problem in finance. The numerous
direct applications include searching for optimal prices for commodity trading
and trading foreign currencies. In this paper, we analyze the advice complexity
of this problem. In particular, we are interested in identifying the minimum
amount of information needed in order to achieve a certain competitive ratio.
We design an algorithm that reads b bits of advice and achieves a competitive
ratio of (M/m)^(1/(2^b+1)) where M and m are the maximum and minimum price in
the input. We also give a matching lower bound. Furthermore, we compare the
power of advice and randomization for this problem.
