No. 90 - Hedging at speed in sovereign bond markets
This paper examines the adoption of an emerging class of algorithmic trading strategies, known as Auto-Hedging (AH), among market makers in the secondary market for Italian government bonds. AH strategies enable market makers to rapidly offset exposures following quote executions, mitigating inventory risk and adverse selection. Using trade-level data from the MTS market, we document a sharp increase in AH usage since 2020, with widespread adoption across dealers and instruments. Our empirical analysis shows that variations in AH adoption are primarily driven by time-invariant, entity-specific characteristics, while market liquidity conditions exert a more modest yet statistically significant influence. Moreover, we find that AH can also be influenced by external factors beyond the immediate trading environment. Overall, the study highlights the growing role of algorithmic trading in market-making risk management and the challenges faced by dealers in increasingly fast-paced and competitive electronic markets.
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14 September 2026
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