Gelir Çeşitliliği ve Kredi Kullanımının Performansa Etkisi: Türk Aracı Kurumları Üzerine Kantitatif Bir Yaklaşım
The Impact of Revenue Diversification and Credit Utilization on Performance: A Quantitative Approach on Turkish Brokerage Firms

Summary/Abstract: This study evaluates the financial performance of brokerage houses operating in Türkiye’s capital markets during the period 2005-2024 using multi-criteria decision-making (MCDM) techniques, namely IDOCRIW for criteria weighting and COBRA for alternative ranking. The motivation stems from the structural fragility in the sector, where brokerage houses remain highly dependent on trading commissions - comprising 60–75% of their service revenues - while generating only 25-40% from non-commission income streams. This concentration indicates a lack of revenue diversification and undermines long-term financial sustainability. Accordingly, the study provides a comprehensive framework for analyzing performance through the lenses of investor behavior, leverage usage, and income structure. The dataset was compiled from the Turkish Capital Markets Association (TSPB) and consists of six key financial indicators: the ratio of investors with margin agreements, ratio of margin users, margin utilization rate, ratio of margin trading volume to equity volume, commission income to sales ratio, and interest income to sales ratio. These indicators offer insights into both institutional performance and investor risk appetite. IDOCRIW, which integrates Entropy and CILOS methods to determine objective weights, was used to compute the relative importance of the criteria. The COBRA method was then applied to rank the performance of each year within the dataset. According to the IDOCRIW results, the most significant factor was “interest income from clients as a share of sales revenue” which received the highest weight of 65.22%. In contrast, the “ratio of margin users to equity investors” had the lowest weight at 2.76%. These findings underscore the decisive role of credit-based income in brokerage performance. COBRA rankings indicated that 2009 was the best-performing year, primarily due to a 37% increase in commission income and a 34% decrease in interest income compared to the previous year. Meanwhile, 2024 showed the lowest performance despite record trading volumes and rising investor numbers, revealing deeper structural vulnerabilities. To test the robustness of the results, alternative rankings using other distance-based MCDM methods-VIKOR, TOPSIS, ARAS, EDAS, and MABAC-were compared. Spearman rank correlation analysis revealed strong correlations (ρ > 0.80) between COBRA and these methods, supporting the validity of the results. The TODIM method, which incorporates gain/loss sensitivity, produced significantly different rankings and did not correlate meaningfully with the others. Sensitivity analysis was also conducted to test the model’s stability: reducing the weight of the dominant K6 criterion by up to 90% caused only minor shifts in rankings, indicating that the overall evaluation framework remains consistent under changing assumptions. Further comparisons with other weighting methods such as MEREC, CRITIC, and NMD confirmed the consistency and reliability of the IDOCRIW-based model. The findings suggest that brokerage houses must reduce their dependency on commission income by expanding into high value-added services such as investment advisory, portfolio management, and IPO consultancy. Additionally, close monitoring of investor behavior and prudent leverage management are essential for mitigating operational risks. Regulatory bodies should promote income diversification through incentives and develop stricter oversight mechanisms to ensure sustainability. The study also recommends caution regarding zero-commission marketing strategies, which may distort competition and conceal hidden costs. Unlike previous research focused on firm-level analysis, this study adopts a macro-level approach by providing a year-based sectoral evaluation. The proposed IDOCRIW-COBRA framework offers practical implications for decision-makers, investors, and policymakers by presenting an empirically grounded model for sector-wide performance measurement.

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