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2151 Results

AI Agents for Cash Management in Payment Systems

Staff working paper 2025-35 Iñaki Aldasoro, Ajit Desai
Can artificial intelligence (AI) think and act like a cash manager? In this paper we explore how generative AI agents can help manage liquidity, prioritize payments and optimize efficiency in real-time gross settlement systems.

Quantitative Easing and Long‐Term Yields in Small Open Economies

Staff working paper 2017-26 Antonio Diez de los Rios, Maral Shamloo
We compare the Federal Reserve’s asset purchase programs with those implemented by the Bank of England and the Swedish Riksbank, and the Swiss National Bank’s reserve expansion program.

How do Canadians perceive access to cash?

Staff analytical note 2024-24 Heng Chen, Daneal O’Habib, Hongyu Xiao
This paper introduces a subjective measure of cash accessibility in Canada, complementing existing distance-based metrics developed by Chen, O’Habib and Xiao (2023). Analyzing data from the 2023 Methods-of-Payment Survey, this study explores how Canadians perceive their ease of accessing cash from automated banking machines (ABMs) and financial institution branches.
Content Type(s): Staff research, Staff analytical notes JEL Code(s): J, J1, J15, O, O1, R, R5, R51 Research Theme(s): Money and payments, Cash and bank notes

Is anyone surprised? The high-frequency impact of US and domestic macroeconomic data announcements on Canadian asset prices

Staff analytical note 2025-10 Blake DeBruin Martos, Rodrigo Sekkel, Henry Stern, Xu Zhang
Using almost two decades of detailed high-frequency data, we show how Canadian interest rates, the CAD/USD spot exchange rate, and stock market returns react to both US and domestic macro announcements. We find that Canadian macroeconomic announcements invoke greater responses in short-term yields, whereas US macroeconomic announcements play an increasingly important role in the yield movements of longer-term assets.

Macroeconomic Uncertainty Through the Lens of Professional Forecasters

Staff working paper 2016-5 Soojin Jo, Rodrigo Sekkel
We analyze the evolution of macroeconomic uncertainty in the United States, based on the forecast errors of consensus survey forecasts of different economic indicators. Comprehensive information contained in the survey forecasts enables us to capture a real-time subjective measure of uncertainty in a simple framework.

Quantile VARs and Macroeconomic Risk Forecasting

Staff working paper 2025-4 Stéphane Surprenant
This paper provides an extensive evaluation of the performance of quantile vector autoregression (QVAR) to forecast macroeconomic risk. Generally, QVAR outperforms standard benchmark models. Moreover, QVAR and QVAR augmented with factors perform equally well. Both are adequate for modeling macroeconomic risks.
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