This paper introduces the Adjusted Return Structure (ARS), a reference-based framework that recasts performance evaluation as a structural normalization problem. Traditional performance comparisons often rely on raw terminal returns, which can obscure the fact that identical returns are frequently produced under materially different structural movement burdens. To address this, the proposed framework decomposes cumulative logarithmic returns into positive (P), negative (N), and total (V) structural components, normalizing the analyzed asset against a selected reference structure.Rather than collapsing performance into a single composite score, the model generates a multi-dimensional diagnostic profile. It evaluates returns under equalized long-side adverse movement (ARn), equalized short-side adverse movement (ARp), and equalized direction-neutral total movement (ARv). By formally separating the structural reference (which normalizes exposure) from the return reference (which interprets relative performance), the ARS framework allows analysts to compare financial assets under precisely equalized structural risk conditions. While the mathematical framework is retrospective in its decomposition, the resulting ARS profiles serve as robust, persistent structural features for quantitative backtesting, strategy evaluation, and financial simulation.
Motty Shai (Wed,) studied this question.