A sampling-window approach to transactions-based Libor fixing
FRB of New York Staff Report, 2013•papers.ssrn.com
We examine the properties of a method for fixing Libor rates that is based on transactions
data and multi-day sampling windows. The use of a sampling window may mitigate
problems caused by thin transaction volumes in unsecured wholesale term funding markets.
Using two partial data sets of loan transactions, we estimate how the use of different
sampling windows could affect the statistical properties of Libor fixings at various maturities.
Our methodology, which is based on a multiplicative estimate of sampling noise that avoids …
data and multi-day sampling windows. The use of a sampling window may mitigate
problems caused by thin transaction volumes in unsecured wholesale term funding markets.
Using two partial data sets of loan transactions, we estimate how the use of different
sampling windows could affect the statistical properties of Libor fixings at various maturities.
Our methodology, which is based on a multiplicative estimate of sampling noise that avoids …
Abstract
We examine the properties of a method for fixing Libor rates that is based on transactions data and multi-day sampling windows. The use of a sampling window may mitigate problems caused by thin transaction volumes in unsecured wholesale term funding markets. Using two partial data sets of loan transactions, we estimate how the use of different sampling windows could affect the statistical properties of Libor fixings at various maturities. Our methodology, which is based on a multiplicative estimate of sampling noise that avoids the need for interest rate data, uses only the timing and sizes of transactions. Limitations of this sampling-window approach are also discussed.
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