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We suggest a procedure for model update, based on detection of structural breaks at unknown change-points. The procedure makes use of the SupF test introduced by Andrews (1993). We apply this procedure for modelling the common stock index returns in the İstanbul Stock Exchange for the 10 year period of 1989 - 1998. The underlying model consists simply of a mean plus noise, with occasional jumps in the level of mean at unknown time instances. The problem is the detection of this jump and the corresponding model update. We find critical values for the SupF test statistic by using the Bootstrap method. A trading rule that uses the forecasts from the suggested procedure is observed to outperform the buy-and-hold strategy.