Valuing Hard-to-Price Securities in Volatile Markets
Valuing hard-to-price securities has long been a complex endeavour for asset managers and institutional investment firms, particularly for OTC instruments and illiquid assets. This challenge is amplified in volatile markets, where obtaining direct, observable prices becomes even more difficult, making accurate valuations a significant issue with serious consequences. To address this, the use of reliable, transparent and independent third-party pricing and valuations services has become indispensable for firms seeking to maintain financial integrity and client trust against the backdrop of a complex and unstable geopolitical and economic landscape.
This new report, ‘Valuing Hard-to-Price Securities in Volatile Markets,’ based on an A-Team survey of industry practitioners commissioned by LSEG, provides a comprehensive snapshot of current practices in consuming evaluated pricing services. Drawing on insights from pricing professionals across North American and European markets, it explores demand factors, key use-cases, and the critical attributes practitioners seek in their pricing service suppliers.
From this report, readers will gain insights into:
- The essential use-cases for evaluated pricing, including daily portfolio valuation, NAV calculation, performance measurement, and risk management in today’s dynamic markets.
- The key attributes of evaluated pricing services, such as unwavering consistency and reliability, particularly during periods of market turmoil, which are paramount for confident decision-making.
- The importance of transparent and robust methodologies that underpin valuations, ensuring defensible and trustworthy prices for even the most illiquid securities.
- The significance of comprehensive data coverage and geographical reach when selecting providers, especially for firms with diverse, global portfolios.
- Practitioner perspectives on emerging technologies like AI, and the crucial need for transparency regarding their application in valuation models.