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arXiv 2206.13751q-fin.STecon.EM
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外汇储备的货币构成估算

Estimating the Currency Composition of Foreign Exchange Reserves

Matthew Ferranti

AI总结:

针对部分大储备国披露货币构成信息不足的问题,本文提出用隐马尔可夫模型估算储备构成,应用于中、新后发现中国储备构成接近全球平均、新加坡美元持有量偏少。

摘要:

各国央行管理着约12万亿美元的外汇储备,影响着全球汇率和资产价格。然而,部分最大的储备持有国仅披露极少的货币构成信息,阻碍了实证分析。本文提出一种隐马尔可夫模型(Hidden Markov Model),通过将投资组合估值波动与主要储备货币的汇率相关联,来估算央行储备的构成。笔者将该模型应用于中国和新加坡——这两个国家合计持有约3.4万亿美元储备且未披露其构成。研究发现,中国的储备构成可能与全球平均水平相似,而新加坡持有的美元可能更少。

英文摘要:

Central banks manage about \$12 trillion in foreign exchange reserves, influencing global exchange rates and asset prices. However, some of the largest holders of reserves report minimal information about their currency composition, hindering empirical analysis. I describe a Hidden Markov Model to estimate the composition of a central bank's reserves by relating the fluctuation in the portfolio's valuation to the exchange rates of major reserve currencies. I apply the model to China and Singapore, two countries that collectively hold about \$3.4 trillion in reserves and conceal their composition. I find that both China's reserve composition likely resembles the global average, while Singapore probably holds fewer US dollars.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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