Measuring Systemic Risk Across Financial Market Infrastructures Staff working paper 2016-10 Fuchun Li, Héctor Pérez Saiz We measure systemic risk in the network of financial market infrastructures (FMIs) as the probability that two or more FMIs have a large credit risk exposure to the same FMI participant. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C58, G, G2, G21, G23 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Money and payments, Payment and financial market infrastructures
Predictive Ability of Commodity Prices for the Canadian Dollar Staff analytical note 2016-2 Kimberly Berg, Pierre Guérin, Yuko Imura Recent sharp declines in commodity prices and the simultaneous depreciation of the Canadian dollar (CAD) relative to the U.S. dollar (USD) have rekindled an interest in the relationship between commodity prices and the CAD-USD exchange rate. Content Type(s): Staff research, Staff analytical notes Research Theme(s): Financial markets and funds management, International markets and currencies, Models and tools, Econometric, statistical and computational methods
The Dynamics of Capital Flow Episodes Staff working paper 2016-9 Christian Friedrich, Pierre Guérin This paper proposes a novel methodology for identifying episodes of strong capital flows based on a regime-switching model. In comparison with the existing literature, a key advantage of our methodology is to estimate capital flow regimes without the need for context- and sample-specific assumptions. Content Type(s): Staff research, Staff working papers JEL Code(s): F, F2, F21, F3, F32, G, G1, G11 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Structural challenges, International trade, finance and competitiveness
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. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C3, C38, E, E1, E17, E3, E32 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Computing the Accuracy of Complex Non-Random Sampling Methods: The Case of the Bank of Canada's Business Outlook Survey Staff working paper 2009-10 Daniel de Munnik, David Dupuis, Mark Illing A number of central banks publish their own business conditions surveys based on complex non random sampling methods. The results of these surveys influence monetary policy decisions and thus affect expectations in financial markets. To date, however, no one has computed the accuracy of these surveys because their respective non-random sampling method renders this assessment non-trivial. This paper describes a methodology for modeling complex non-random sampling behaviour, and computing relevant measures of statistical confidence, based on a given survey’s historical selection practice. We apply this framework to the Bank of Canada’s Business Outlook Survey by describing the sampling method in terms of rules-based criteria, historical practices, and Bayesian probabilities. This allows us to replicate the firm selection process using Monte Carlo simulations on a comprehensive micro-dataset of Canadian firms. We find, under certain assumptions, no evidence that the Bank’s firm selection process results in biased estimates and/or wider confidence intervals. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C4, C8, C81, C9, C90 Research Theme(s): Models and tools, Econometric, statistical and computational methods