  Researchers have studied the first passage time of financial time series and
observed that the smallest time interval needed for a stock index to move a
given distance is typically shorter for negative than for positive price
movements. The same is not observed for the index constituents, the individual
stocks. We use the discrete wavelet transform to illustrate that this is a long
rather than short time scale phenomenon -- if enough low frequency content of
the price process is removed, the asymmetry disappears. We also propose a new
model, which explain the asymmetry by prolonged, correlated down movements of
individual stocks.
