Fuzzy MCDM Approach for NASDAQ Portfolio Selection: Balancing Risk and Return

Abstract

This study examines stock selection in a complex nonlinear dynamic environment by integrating two primary categories of financial indicators:
Accounting Financial Measures (AFM) and Economic Value Financial Measures (EFM). It argues that a comparative evaluation of AFM and
EFM offers a more comprehensive and reliable framework for investment decision-making. The analysis incorporates six key financial criteria:
Return on Invested Capital (ROIC) (C1), Economic Value Added (EVA) (C2), Price/Earnings-to-Growth (PEG) Ratio (C3), Free Cash Flow
(FCF) Yield (C4), .To manage uncertainty and subjectivity in financial assessments, the study applies the Fuzzy Analytic Hierarchy Process
(FAHP), a structured multi-criteria decision-making approach. Financial data were collected from the top ten companies listed on the NASDAQ
Exchange, ensuring a representative sample of leading firms. The FAHP model facilitates the prioritization and ranking of financial indicators
based on their relative importance in investment decisions. The results indicate that Return on Invested Capital (ROIC) (C1), is the most
influential criterion, highlighting the critical role of profitability and effective utilization of shareholders’ equity in stock selection. Other
profitability and value-based measures, such as ROIC and EVA, also demonstrate strong influence, reinforcing the importance of long-term
value creation. In contrast, liquidity-related measures have comparatively lower significance. Overall, the study provides meaningful insights
for investors by emphasizing the prioritization of profitability and growth-oriented metrics over short-term solvency considerations, thereby
supporting more strategic and effective portfolio construction.