Central banks use open market operations (OMOs) to adjust the liquidity available to the financial system to maintain the short-term borrowing rate within the desired target range. Using the conditional event study methodology to decompose the impact of OMOs into supply and announcement effects, this paper finds that when OMO announcements are unexpected, the decrease in the lending rate as a result of the higher supply is significantly moderated by the announcement effect. The results highlight that central banks communicate not just through signals of their desired policy stance, but also through their announcements of operations that implement the stance.

This paper documents stylized facts about the life cycle of trading activity and trading cost (i.e., market liquidity) of Government of Canada (GoC) bonds. Using a unique data set from the cash, repo and securities lending markets, we document three stylized facts. First, the trading activity of all GoC bonds follows an inverse U-shape across all three markets, with activity peaking during the benchmark (on-the-run) phase. Second, the level of activity exhibits considerable heterogeneity across bonds with different maturities: shorter-term bonds are more actively traded in the cash and repo markets, while longer-term bonds are more active in the securities lending market. Finally, in contrast to the conventional notion that a bond becomes less liquid as it ages, our trade-based measures indicate that the transaction cost of a GoC bond remains low in the later stages of its life cycle.

Central banks make public the results of open market operations (OMOs), which they use to adjust the liquidity available to the financial system to maintain the short-term borrowing rate in the range compatible with achieving their monetary policy objectives. This paper shows that such announcements are costly because they moderate the impact of changes in supply achieved through OMOs. Nevertheless, communication of OMOs is desirable because it improves the transparency of the funding market, which makes the price of liquidity—a key input into economic decision making—more reflective of underlying demand and supply of liquidity.

We find that collateral reallocation costs are a significant driver of the dynamics of overnight interbank loans. The cost of negotiating and settling collateralized over-the-counter trades incentivizes the temporary use of unsecured loans to meet changes in short-term liquidity needs, as well as greater uptake of central bank overnight lending facilities. This friction also leads to repos adjusting gradually in response to persistent changes in liquidity demand.

This paper documents the properties of Government of Canada securities in cash, repo and securities lending transactions over their life cycle. By tracking every security from issuance to maturity, we are able to highlight inter-linkages between the markets for cash and for specific securities. Our results indicate that the interaction of search frictions with clientele effects may be key to producing the patterns of trade exhibited by bonds of different maturities.

Data on the use of government securities in the repo, securities lending and cash markets suggest there are bond market clienteles in Canada. Shorter-term bonds are more prevalent in the repo market, while longer-maturity securities are more active in the securities lending market-consistent with the preferred habitat hypothesis. These results could help design better debt-management strategies and more-effective policies to maintain well-functioning financial markets.

Data on the use of government securities in the repo, securities lending and cash markets suggest there are bond market clienteles in Canada. Shorter-term bonds are more prevalent in the repo market, while longer-maturity securities are more active in the securities lending market-consistent with the preferred habitat hypothesis. These results could help design better debt-management strategies and more-effective policies to maintain well-functioning financial markets.

The common-factor hypothesis is one possible explanation for the housing wealth effect. Under this hypothesis, house price appreciation is related to changes in consumption as long as the available proxies for the common driver of housing and non-housing demand are noisy and housing supply is not perfectly elastic.

Bank of Canada working papers are theoretical or empirical works-in-progress on subjects in economics and finance. The views expressed in this paper are those of the author. No responsibility for them should be attributed to the Bank of Canada. and seminar participants at the Bank of Canada, CEMFI, and European Central Bank for their suggestions. Any remaining errors are my own. Abstract This paper proposes a novel regression-based approach to the estimation of Gaussian dynamic term structure models that avoids numerical optimization. This new estimator is an asymptotic least squares estimator defined by the no-arbitrage conditions upon which these models are built. We discuss some efficiency considerations of this estimator, and show that it is asymptotically equivalent to maximum likelihood estimation. Further, we note that our estimator remains easy-to-compute and asymptotically efficient in a variety of situations in which other recently proposed approaches lose their tractability. We provide an empirical application in the context of the Canadian bond market. Résumé Un cadre de régression novateur permettant d'éviter l'optimisation numérique est proposé pour l'estimation de modèles dynamiques gaussiens de la structure par terme des taux d'intérêt. Ce nouvel estimateur est un estimateur des moindres carrés asymptotiques et est défini par les conditions d'absence d'arbitrage à la base de ces modèles. L'auteur analyse les caractéristiques d'efficience de son estimateur et montre que celui-ci est asymptotiquement équivalent à un estimateur du maximum de vraisemblance. De plus, il reste simple à calculer et asymptotiquement efficient dans un éventail de situations où d'autres approches récentes deviennent très difficiles à utiliser. L'auteur présente une application empirique de son cadre au cas du marché obligataire canadien.

The Bank of Canada recently developed an asset-liability-matching model to aid in the management of Canada’s foreign exchange reserves. The model allows policy-makers at the Bank and the Department of Finance to analyze asset-allocation and funding-mix decisions by quantifying both the risk-return and liquidity trade-offs for the assets, as well as the risk-cost trade-offs of the funding liabilities.

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Latent state variable estimates extracted using the entire yield curve predict the one day-ahead equity premium significantly better than do commonly-used proxies derived using only limited information contained in the yield curve such as the historical mean, the term spread and the credit spread. I estimate the state variables using a simple two-stage procedure. I first estimate the parameters of the equation of motion governing the evolution of the state variable for a chosen term structure model. The yield for a given maturity is then a known function of the state variable and the estimated parameters from the first stage. Inverting this function using the observed yield curve gives the state variable estimate.

I propose a novel method to estimate a state variable that summarises the information content of the yield curve, and find that unexpected changes in the state variable significantly predict the expected equity premium on the next trading day. This predictor outperforms changes in the short rate, and the term and credit spreads, especially during recessions. The state variable changes also have much more predictive ability than do changes in the level, slope and curvature factors commonly used to summarise the information content of the yield curve. The two step state variable estimation procedure is intuitive: first I estimate the parameters of the equation of motion governing the evolution of the state variable for a chosen term structure model. The yield for a given maturity is then a known function of the state variable and the parameters estimated in the first stage; inverting this function using the observed yield curve gives the estimate.

We propose a novel two-stage procedure to obtain point estimates of the state variables that drive the term structure of interest rates. In the rst stage, we rst estimate the parameters of the pricing kernel by matching the unconditional moments of the data at each time to maturity with their model counterparts. Then, at each date, we estimate the value of the state variable that imposes the lowest cost in matching the modelled yield curve to the observed yields; bending energy is our choice of measure of the cost required for this curve matching exercise. The resulting estimates have three principal advantages over commonly-used proxies for the economic state of nature. This procedure provides high-frequency estimates of the state of nature, which could be extremely useful for explaining changes in other high-frequency economic variables. These estimates are also a more comprehensive summary of expected future investment opportunities since they take into account investor expectations over various maturities that are embedded in the yield curve. The estimates are also less ad-hoc, since they are based on an underlying model of the yield curve. We demonstrate the procedure for a single state variable a ne model of the yield curve. ∗I owe thanks to Gonzalo Rubio for helpful comments, and to IESE Business School, University of Navarra for support. All errors are mine. Address correspondence to nbulusu@iese.edu or to Av. Pearson 21, 08034 Barcelona, Spain.