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When redeeming shares for investors, bond fund managers must choose a mix of cash and bond sales to honour their commitments. This note uses machine learning algorithms to uncover new patterns in decisions fund managers make to meet redemptions.

Recent research suggests that quantitative easing (QE) may affect a broad range of asset prices through a portfolio balance channel. Using novel security-level holding data of individual US mutual funds, we establish evidence that portfolio rebalancing occurred both within and across funds.

Mutual funds employ a host of tools to manage redemption run risk. However, our results suggest that Canadian corporate bond funds may be vulnerable to redemption runs, especially when they are less liquid and when market volatility is high.

This paper discusses how the bankers’ acceptance (BA) market in Canada is organized and its essential link to the Canadian Dollar Offered Rate (CDOR). Globally, BAs are a niche product used only in a limited number of jurisdictions.

When investors redeem their fund shares for cash, fixed-income fund managers can choose whether to draw on their liquid holdings or sell bonds in the secondary market. We analyze the liquidity-management decisions of Canadian corporate bond mutual funds, focusing on the strategies they use to meet investor redemptions.

We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH (GTARCH) family and propose a more general Spline-GTARCH model, which captures high-frequency return volatility, low-frequency macroeconomic volatility as well as an asymmetric response to past negative news in both autoregressive conditional heteroscedasticity (ARCH) and GARCH terms.

Canadian corporate bond mutual funds have rapidly increased in number and size in recent years. Their holdings have also become riskier, increasing their exposures to credit risk, interest rate risk and liquidity risk. We also briefly discuss financial stability implications.

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.

We identify the drivers of unsecured and collateralized loan volumes, rates and haircuts in Canada using the Bayesian model averaging approach to deal with model uncertainty. Our results suggest that the key friction driving behaviour in this market is the collateral reallocation cost faced by borrowers.

This paper estimates potential exposures, netting benefits and settlement gains by merging retail and wholesale payments into batches and conducting multiple intraday settlements in this hypothetical model of a single "calibrated payments system." The results demonstrate that credit risk exposures faced by participants in the system are largely dependent on their relative activity in the retail and wholesale payments systems.