The Emergence of 'Regular and Predictable' as a Treasury Debt Management Strategy

The Emergence of 'Regular and Predictable' as a Treasury Debt Management Strategy
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“定期且可预测”的国库债务管理策略的出现

DOI:
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发表时间:
2007
期刊:
Capital Markets: Asset Pricing & Valuation
影响因子:
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通讯作者:
K. Garbade
K. Garbade
中科院分区:
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文献类型:
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作者:
K. Garbade

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The Federal Reserve Bank of New York released a report -- New Directions for Understanding Systemic Risk -- that presents key findings from a cross-disciplinary conference that it cosponsored in May 2006 with the National Academy of Sciences' Board on Mathematical Sciences and Their Applications. ; The pace of financial innovation over the past decade has increased the complexity and interconnectedness of the financial system. This development is important to central banks, such as the Federal Reserve, because of their traditional role in addressing systemic risks to the financial system. ; To encourage innovative thinking about systemic issues, the New York Fed partnered with the National Academy of Sciences to bring together more than 100 experts on systemic risk from 22 countries to compare cross-disciplinary perspectives on monitoring, addressing and preventing this type of risk. ; This report, released as part of the Bank's Economic Policy Review series, outlines some of the key points concerning systemic risk made by the various disciplines represented - including economic research, ecology, physics and engineering - as well as presentations on market-oriented models of financial crises, and systemic risk in the payments system and the interbank funds market. The report concludes with observations gathered from the sessions and a discussion of potential applications to policy. ; The three papers presented in this conference session highlighted the positive feedback effects that produce herdlike behavior in markets, and the subsequent discussion focused in part on means of encouraging heterogeneous investment strategies to counter such behavior. Participants in the session also discussed the types of models used to study systemic risk and commented on the challenges and trade-offs researchers face in developing their models.