Recent Papers

The dynamic nature of global financial markets has amplified the importance of understanding the intricate relationship between risk and return, especially in market-linked securities (MLSs). These structured financial products provide exposure to diverse asset classes, including international currencies and commodities, offering investors opportunities for enhanced returns. However, such securities also come with unique risks stemming from their inherent complexity and the volatility of the underlying markets. This research paper undertakes a comprehensive analysis of the risk-return profile of MLSs with a focus on forex and commodities markets.The study begins with a thorough exploration of the structural framework of MLSs, highlighting their characteristics, types, and key features. It then delves into the international currencies market, the largest financial market globally, and the commodities market, which encompasses raw materials and agricultural products. These markets are evaluated in terms of their liquidity, participants, and sensitivity to economic, geopolitical, and market forces.Quantitative methods such as historical performance analysis, volatility measurement, correlation studies, and scenario-based stress testing are employed to assess the performance and risk factors of MLSs. Particular attention is paid to the influences of exchange rate fluctuations, geopolitical events, and supply-demand imbalances in international currencies and commodities. The findings reveal critical insights into the risk mitigation and return optimization strategies that investors and financial advisors can adopt when incorporating MLSs into their portfolios.The paper also examines the role of MLSs in portfolio diversification, showing how their inclusion can potentially enhance returns and reduce risks under certain market conditions. This research contributes to the broader understanding of structured financial products and their utility in a rapidly evolving global financial landscape, equipping investors with datadriven insights for informed decision-making.

Copyright © 2025 Prashant Kumar . This is an open access article distributed under the Creative Commons Attribution License.