Abstract
Market efficiency hypothesis suggests a zero level for the intra-day interest rate. However, a
liquidity crises introduces frictions related to news, which can cause an upward jump of the intra-
day rate. This paper documents that these dynamics can be partially predicted during turbulent
times. A long memory approach outperforms in term of point and density forecasting random
walk and autoregressive benchmarks. The gains are particular high when the full distribution is
predicted and probabilistic assessments of future movements of interest rate derived by the model
can be used as a policy tools for central bank to plan supplementary market operations during
turbulent times. Adding exogenous variables to proxy funding liquidity and counterpart risks
does not improve forecast accuracy and the predictability seems to derive from the econometric
properties of the series more than from economic news available in real-time to the market.
Lingua originale | English |
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Numero di pagine | 25 |
Stato di pubblicazione | Pubblicato - 2011 |
Keywords
- forecasting