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This paper proposes a unique approach to simulate intraday transactions in the Canadian retail payments batch system when such transactions are unobtainable. The simulation procedure has potential for helping with data-deficient problems where only high-level aggregate information is available.

An anonymous credential mechanism is a set of protocols that allows users to obtain credentials from an organization and demonstrate ownership of these credentials without compromising users’ privacy. In this work, we construct the first secret-free and quantum-safe credential mechanism.

The history of Canada's money provides a unique perspective from which to view the growth and development of the Canadian economy and Canada as a nation. Author James Powell traces the evolution of Canadian money form its pre-colonial origins to the present day, highlighting the currency chaos of the colonial period, as well as the effects of two world wars and the Great Depression.

This technical report describes sampling, weighting and variance estimation for the Bank of Canada’s 2017 Methods-of-Payment Survey. Under quota sampling, a raking ratio method is implemented to generate weights with both post-stratification and nonparametric nonresponse weight adjustments.

We develop a model in which a financial intermediary’s investment in risky assets—risk taking—is excessive due to limited liability and deposit insurance and characterize the policy tools that implement efficient risk taking.

Repo market imbalances can be large and persistent, and can lift the cost of short-term funding in Canada, including the CORRA benchmark. Banks’ holdings of settlement balances absorbed most of the repo imbalances during QE, but have become far less central by the end of QT.

Banks’ business interactions create a network of relationships that are hidden in the correlations of bank stock returns. But for policy interventions, we need causality to understand how the network changes. Thus, this paper looks for the causal network anticipated by investors.

We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does.