This study introduces a novel portfolio construction algorithm, named the Interest rate-based portfolio combination (IPc), uniquely incorporating dynamic interest rate as an indicator to guide asset allocation decisions. Extensive literature substantiates the existence of an inverse relationship between the interest rate and the profitability of the stock market, although this relationship has not been widely exploited in the realm of portfolio optimization research. Leveraging this relationship, we utilize the interest rate as a predictive indicator for stock market trends. IPc algorithm is designed to dynamically adjust the allocation weights between two portfolio strategies: the Minimum variance portfolio (MV) and the Ridge-Regularized portfolio (RR). The RR functions as the cornerstone strategy within the IPc framework, establishing a robust foundation that guides portfolio decision-making processes. In scenarios where the interest rate is elevated, IPc increases the relative weight of MV, adhering to a more conservative investment strategy. This adjustment is predicated on the understanding that elevated interest rate signals reduced stock market profitability, thus necessitating a shift towards more conservative investment strategies.
To evaluate the performance of IPc, we conduct a comprehensive comparison against seven distinct portfolio strategies and three stock market indices, across a variety of investment performance metrics. Our empirical experiment demonstrates that IPc outperforms the benchmarks, underscoring the utility of employing the interest rate into portfolio strategies. Results of this study augment the existing body of knowledge on portfolio management, offering valuable insights for both academics and practitioners in the field of portfolio optimization.