Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach. Models include performing sector rotations in GICS classified sectors and releasing single stock (Bank of America) trading signals in the US stock market. The multi-agent models are implemented using the Netlogo framework. Both models utilize historical data and produce returns that exceed benchmark returns, which are Buy and Hold strategies on S&P 500 Index and Bank of America stock respectively.