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Measuring Interest Rate Expectations in Canada

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Financial market expectations regarding future changes in the target for the overnight rate of interest are an important source of information for the Bank of Canada. Financial markets are the mechanism through which the policy rate affects other financial variables, such as longer-term interest rates, the exchange rate, and other asset prices. An accurate measure of their expectations can therefore help policy-makers assess the potential impact of contemplated changes. Johnson focuses on the expectations hypothesis, which measures expectations of future levels of the target overnight rate as implied by current money market yields. Although expectations can be derived from the current yield on any short-term fixed-income asset, some assets have proven to be more accurate predictors than others. The implementation of a policy of fixed-announcements dates has coincided with the increased predictive power of these short-term assets. As a result of this improvement, a relatively simple model of the yield curve can now provide an accurate measure of financial market expectations.

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  • Grahame Johnson, 2003. "Measuring Interest Rate Expectations in Canada," Bank of Canada Review, Bank of Canada, vol. 2003(Summer), pages 17-27.
  • Handle: RePEc:bca:bcarev:v:2003:y:2003:i:summer03:p:17-27
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    Cited by:

    1. Tiff Macklem, 2005. "Commentary : central bank communication and policy effectiveness," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, issue Aug, pages 475-494.
    2. Chris D'Souza & Ingrid Lo & Stephen Sapp, 2007. "Price Formation and Liquidity Provision in Short-Term Fixed Income Markets," Staff Working Papers 07-27, Bank of Canada.
    3. Bo Young Chang & Bruno Feunou, 2013. "Measuring Uncertainty in Monetary Policy Using Implied Volatility and Realized Volatility," Staff Working Papers 13-37, Bank of Canada.
    4. Lahmiri, Salim, 2016. "Interest rate next-day variation prediction based on hybrid feedforward neural network, particle swarm optimization, and multiresolution techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 388-396.

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