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DESTR was introduced to address the need for a reliable, transparent, and robust benchmark rate for short-term unsecured lending in Denmark. Similar to international benchmarks like SOFR (US) and €STR (Eurozone), DESTR ensures consistency and stability in the overnight money market.
Prior to DESTR, Denmark lacked a benchmark that fully aligned with international best practices. By implementing DESTR, financial institutions and central banks could:
DESTR is calculated based on actual transactions in Denmark’s overnight unsecured money market. The data is collected daily from banks, ensuring transparency and reliability.
The formula considers:
Using a volume-weighted average:
DESTR= (1,000,000×0.55)+(2,000,000×0.60)+(3,000,000×0.58) 1,000,000+2,000,000+3,000,000
DESTR = 0.58%
DESTR plays a vital role as a key benchmark for overnight lending rates in Denmark, helping financial markets function smoothly. Its core uses include:
Risk management: Institutions use DESTR to manage liquidity risk.
Valuation of financial products: Financial contracts like derivatives reference DESTR.
Monetary policy: The rate helps Denmark’s central bank monitor market liquidity and implement monetary policies effectively.
For example, banks managing overnight funding now rely on DESTR to assess short-term borrowing costs and optimise their liquidity strategies.
Unlike SOFR, which reflects secured transactions, DESTR focuses on unsecured overnight borrowing.
Similar to €STR and SONIA, DESTR provides a reliable unsecured rate but specifically applies to the Danish money market.
DESTR directly impacts a wide range of market participants:
DESTR is more than just a benchmark; it is critical for promoting financial stability and transparency in Denmark’s short-term money market. By providing a consistent and accurate reference rate, DESTR enhances confidence among market participants and aligns Denmark with international standards.
TraditionData offers reliable access to DESTR and other global benchmark rates, empowering institutions to make informed decisions with high-quality market data.