Trend-following (TF) strategies use fixed trading mechanism in order to take advantages from the long-term market moves without regards to the past price performance. In contrast with most prediction tools that stemmed from soft-computing such as neural networks to predict a future trend, TF just rides on the current trend pattern to decide on buying or selling. While TF is widely applied in currency markets with a good track record for major currency pairs [1], it is doubtful that if TF can be applied in stock market. In this paper a new TF model that features both strategies of evaluating the trend by static and adaptive rules, is created from simulations and later verified on Hong Kong Hang Seng future indices. The model assesses trend profitability from the statistical features of the return distribution of the asset under consideration. The results and examples facilitate some insights on the merits of using the trend following model.