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This paper documents Canada’s recent review of its sovereign debt distribution framework (DDF). Informed by a context of record-high debt issuance since the previous DDF review, along with comparisons with sovereign peers and insights from market participants, the review identified an important need to broaden Canada’s dealer base internationally to support a larger and more diverse set of investors.

Pressures on the CORRA benchmark can emerge from the interaction of client borrowing behavior, dealer balance sheet constraints, even if the level of settlement balances is in a range deemed sufficient to meet the requirement of the payment system and the prudential demand of its members.

In Canada and abroad, yields on long-term government bonds have stayed high even as policy interest rates have fallen. This is due to rising term premiums―the extra compensation investors demand for holding these bonds. A key factor driving higher term premiums is global concerns about the ability of markets to absorb substantial amounts of government debt.

This analytical paper examines the organization of Government of Canada bond dealing. We focus on dealers’ hedging and funding practices, the market infrastructures that support those practices, and trading costs across the yield curve. This paper builds on earlier work discussing Canada’s fixed-income market: "Government of Canada Fixed-Income Market Ecology."

We develop an approach to quantify transaction costs in the repo market using OTC transaction data, where quoted bid-ask spreads are not observable. By estimating effective spreads at the level of individual trades, we construct a novel metric to evaluate intermediation costs across different segments of the market.

This paper examines the interaction between quantitative easing (QE) and the securities lending facility (SLF) using a detailed dataset on Riksbank QE purchases, Swedish DMO SLF transactions and OTC repo deals. A theoretical model further shows how excess demand for assets and search frictions shift the SLF from a backstop to a first-resort tool.

Statistical inference--both estimation and testing--for stochastic volatility (SV) models is known to be challenging and computationally demanding. We propose simple and efficient estimators for SV models with conditionally heavy-tailed error distributions, particularly the Student’s t and Generalized Exponential Distributions (GED). The estimators rely on a small set of moment conditions derived from ARMA-type representations of SV models, with an option to apply “winsorization” to improve stability and finite-sample performance. Except for the degrees of-freedom parameter, closed-form expressions are available for all other parameters, extending Ahsan and Dufour (2019, 2021), thus eliminating the need for numerical optimization or initial values. We derive the estimators’ asymptotic distribution and show that, due to their analytical tractability, they support reliable, and even exact, simulation-based inference via Monte Carlo or bootstrap methods. We assess their performance through extensive simulations and demonstrate their practical relevance in financial return data, which strongly reject the normality assumption in favor of heavy-tailed models.

Project Samara was a real‑world experiment testing distributed ledger technology and wholesale central bank digital money for bond issuance and settlement in Canada. It demonstrated technical feasibility and potential efficiency and risk‑reduction benefits, while highlighting important trade‑offs related to complexity, governance, and regulatory alignment.

Hedge funds are active in Canadian government bond markets and help improve market efficiency. But their trading strategies are not well understood. We offer insights into the range of strategies hedge funds use beyond the more commonly known cash-futures basis trade. We also explore the concentration of trading activity among a few large funds.

We provide a primer on the role of debt modelling in informing the sovereign debt issuance strategy and discuss how specific challenges faced by debt managers can influence model design decisions. These insights are supported by our experiences using the Canadian Debt Strategy Model to guide policy decisions.