  We present a method for constructing the log-optimal portfolio using the
well-calibrated forecasts of market values. Dawid's notion of calibration and
the Blackwell approachability theorem are used for computing well-calibrated
forecasts. We select a portfolio using this "artificial" probability
distribution of market values. Our portfolio performs asymptotically at least
as well as any stationary portfolio that redistributes the investment at each
round using a continuous function of side information. Unlike in classical
mathematical finance theory, no stochastic assumptions are made about market
values.
