This chapter derives the optimal trend-following rule in a two-state regime-switching model, where bull and bear markets represent distinct regimes. It examines how the optimal trading rule’s parameters depend on the statistical properties of returns in each state, the probability distribution of regime transitions, and the impact of trading costs. The chapter models regime shifts using both Markov and semi-Markov models and investigates how transaction costs influence the shape of return weights in the optimal trading indicator. For each model, we determine the optimal return weights in the absence of transaction costs, showing how they align with the underlying return dynamics. When transaction costs are introduced, the optimal rule adapts by incorporating additional smoothing to mitigate excessive trading. These findings highlight the complexity of designing effective trend-following strategies and emphasize that optimal parameter selection is market dependent and influenced by both return dynamics and cost constraints.