SYNECTICS AS A METHOD FOR STUDYING STRATEGIC DECISIONS IN EXCHANGE-TRADED ACTIVITIES

The article examines synectics as a method for studying strategic decisions in exchange activities. Such methods are needed because decisions are made under conditions of high volatility, information asymmetry, unstable liquidity, and regulatory constraints. Synectics enables comparisons across heterogeneous markets through functional, structural, operational, and risk analogies. The empirical basis of the study comprises indicators of the Ukrainian capital market, organized commodity trading, and the operations of international exchange operators. The article proposes a system of indicators for assessing the strategic suitability of exchange-related decisions. The mathematical framework incorporates data normalization, entropy-based weighting, a synectic strategic suitability index, and concentration coefficients. An analogical transferability coefficient is additionally introduced to capture the potential for adapting strategic approaches based on functional, structural, operational, and risk similarities between markets. The proposed model links synectic analogies to specific tabulated data rather than declarative judgments. The findings indicate that the recovery in trading volumes in Ukraine is accompanied by persistently high concentration across instruments and trading platforms. The study substantiates the need to consider the role of exchange segments in innovation alongside their scale and growth dynamics. Strategic priorities include instrument diversification, the development of derivatives contracts, improvements to clearing infrastructure, and expanded digital access to trading. The practical value of the article lies in the applicability of the model to selecting exchange strategies, instruments, segments, and technological priorities. The proposed approach also provides an analytical basis for assessing the extent to which international exchange practices can be adapted to the structural characteristics and constraints of the Ukrainian market. Further research should focus on validating the model using daily trading and order book data.