The Moving Average Convergence/Divergence (MACD) trading indicator is simple and has been widely used in financial markets to provide trading signals. The MACD-Histogram (MACDH) can be derived from MACD as a second-order trading signal of price actions. To reduce the lagging effects in MACD/MACDH, forecasted values are introduced in a hybrid trading signal, termed as the forecasted-MACDH (fMACDH). The forecasted values are predicted using an online neuro-fuzzy network called the Self-reorganizing Fuzzy Associative Machine (SeroFAM). SeroFAM was designed with both learning and unlearning capabilities in order to handle “shifts” and “drifts” occurring as stock market price fluctuations. A detailed trading simulation is performed for a single stock under a single long-short-MACD (LSM) parameter to explain the experimental design, and 5180 trading simulations were run for the top 10 largest stocks under 518 combinations of the LSM parameters to assess the robustness of the test cases. Comparative results are also provided.