Selecting stocks in financial markets requires evaluating a large number of alternatives under multiple conflicting criteria, such as profitability, indebtedness, liquidity, and risk. Without a structured decision support method, this process is prone to cognitive bias and inconsistency. This study addresses this challenge by applying the FITradeoff (Flexible and Interactive Tradeoff) method to the pre-selection stage of a broader investment portfolio construction framework. FITradeoff is a multicriteria decision analysis method grounded in the Multiattribute Value Theory that elicits scale constants (weights) through partial preference information, avoiding the cognitive burden of precise indifference judgments required by classical tradeoff procedures. Instead, the decision maker responds to tradeoff comparisons between consequences, and the method progressively narrows the feasible weight space using linear programming until a consistent ranking of alternatives emerges. The method was applied to 75 stocks from the Brazilian Ibovespa index, organized by market sector, using eight fundamentalist criteria: Price-to-Earnings (P/E), Price-to-Book (P/B), Dividend Yield, Return on Equity (ROE), Net Debt-to-Equity, Trading Liquidity, Price Volatility, and Corporate Governance level. Results show that top-ranked stocks are not necessarily those with the best individual indicators, but those presenting the best compensatory tradeoffs aligned with the decision maker's preference structure. The sector-based rankings produced by FITradeoff constitute a rational, transparent, and reproducible shortlist of assets that feeds directly into the subsequent portfolio optimization stage of the framework, where capital allocation is determined based on risk-return objectives.

Keywords

FITradeoff, Multicriteria Decision Analysis, Stock Pre-Selection, Fundamentalist Analysis, Investment Decision Support.