Before revision:  The results show conclusively that the thresholds control the level of risk-return trade-off, which can be usefully implemented in allocating assets across asset classes based on individual risk capacity and risk tolerance levels. Next, we obtain frontier lines representing the risk-reward relationship for portfolios built using three strategies (e. g., long, short, and long-short), and then determine the efficient frontier that maximizes returns at specific risk levels. We thus find optimal investment strategies using portfolios tailored to an investor's riskpreference .
After revision:  The results show conclusively that the thresholds control the level of risk-return levels, and an EWP based on all the assets plays a role in the reference portfolio of TBPs. In the process, thresholds play dominant roles in characterizing risk, return, and the prediction accuracy of the subset. The TBP is more data-driven in designing portfolio target risk and return than existing ones, in the sense that it requires no prior knowledge of finance such as financial assumptions, financial mathematics, or expert insights. In a practical application, we present the TBP management procedure for a time horizon extending over multiple time periods; we also discuss their application to mean-variance portfolios to reduce estimation risk .