Acceptance sampling-based investment indicators for financial security selection and portfolio optimization

We propose simple and double acceptance sampling investment indicators designed to determine the acceptance or rejection of financial securities for investment based on a tolerable threshold assessed through historical data. These indicators alleviate the burden of including underperforming securities in a portfolio and determine the optimal sample size required for decisions at a given significance level. Both the investment indicators are defined to address the perspectives of buyers and sellers of securities. The proposed double acceptance sampling-based indicator extends the simple sampling-based indicator, offering equivalent information with a smaller sample. Furthermore, we develop a generalized mean-variance portfolio optimization model that includes the buyer's risk and entropy-based uncertainty in decision-making for selected securities. The applicability of these indicators and the model's generalizability are illustrated using DJIA 30 index stocks, showcasing reduced portfolio size while producing equivalent or higher portfolio returns as compared to the Markowitz model.