Covariates Hiding in the Tails Staff Working Paper 2021-45 Milian Bachem, Lerby Ergun, Casper G. de Vries We characterize the bias in cross-sectional Hill estimates caused by common underlying factors and propose two simple-to-implement remedies. To test for the presence, direction and size of the bias, we use monthly US stock returns and annual US Census county population data. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C0, C01, C1, C14, C5, C58
Classical Decomposition of Markowitz Portfolio Selection Staff Working Paper 2020-21 Christopher Demone, Olivia Di Matteo, Barbara Collignon In this study, we enhance Markowitz portfolio selection with graph theory for the analysis of two portfolios composed of either EU or US assets. Using a threshold-based decomposition of their respective covariance matrices, we perturb the level of risk in each portfolio and build the corresponding sets of graphs. Content Type(s): Staff research, Staff working papers Topic(s): Central bank research JEL Code(s): C, C0, C02
Tail Index Estimation: Quantile-Driven Threshold Selection Staff Working Paper 2019-28 Jon Danielsson, Lerby Ergun, Casper G. de Vries, Laurens de Haan The most extreme events, such as economic crises, are rare but often have a great impact. It is difficult to precisely determine the likelihood of such events because the sample is small. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58
Characterizing the Canadian Financial Cycle with Frequency Filtering Approaches Staff Analytical Note 2018-34 Andrew Lee-Poy In this note, I use two multivariate frequency filtering approaches to characterize the Canadian financial cycle by capturing fluctuations in the underlying variables with respect to a long-term trend. The first approach is a dynamically weighted composite, and the second is a stochastic cycle model. Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Financial stability, Monetary and financial indicators, Recent economic and financial developments JEL Code(s): C, C0, C01, C1, C13, C14, C18, C3, C32, C5, C51, C52, E, E3, E32, E6, E66, G, G0, G01, G1, G18
Challenges in Implementing Worst-Case Analysis Staff Working Paper 2018-47 Jon Danielsson, Lerby Ergun, Casper G. de Vries Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach. Content Type(s): Staff research, Staff working papers Topic(s): Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58
Asymmetric Risks to the Economic Outlook Arising from Financial System Vulnerabilities Staff Analytical Note 2018-6 Thibaut Duprey When financial system vulnerabilities are elevated, they can give rise to asymmetric risks to the economic outlook. To illustrate this, I consider the economic outlook presented in the Bank of Canada’s October 2017 Monetary Policy Report in the context of two key financial system vulnerabilities: high levels of household indebtedness and housing market imbalances. Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Financial stability, Financial system regulation and policies, Monetary and financial indicators, Monetary policy and uncertainty, Recent economic and financial developments JEL Code(s): C, C0, C01, C1, C11, C15, E, E1, E17, E3, E32, E37, E4, E44, E47, E5, E58, E6, E66, G, G0, G01, G1, G18
Household Risk Assessment Model Technical Report No. 106 Brian Peterson, Tom Roberts Household debt can be an important source of vulnerability to the financial system. This technical report describes the Household Risk Assessment Model (HRAM) that has been developed at the Bank of Canada to stress test household balance sheets at the individual level. Content Type(s): Staff research, Technical reports Topic(s): Financial stability, Housing, Sectoral balance sheet JEL Code(s): C, C0, C6, C63, C65, D, D0, D1, D14
The Canadian Debt-Strategy Model: An Overview of the Principal Elements Staff Discussion Paper 2011-3 David Bolder, Simon Deeley The Canadian Debt Strategy Model helps debt managers determine their optimal financing strategy. The model’s code and documentation are available to the public. Content Type(s): Staff research, Staff discussion papers Topic(s): Debt management, Econometric and statistical methods, Financial markets, Fiscal policy JEL Code(s): C, C0, G, G1, G11, G17, H, H6, H63
Financial Stress, Monetary Policy, and Economic Activity Staff Working Paper 2010-12 Fuchun Li, Pierre St-Amant This paper examines empirically the impact of financial stress on the transmission of monetary policy shocks in Canada. The model used is a threshold vector autoregression in which a regime change occurs if financial stress conditions cross a critical threshold. Content Type(s): Staff research, Staff working papers Topic(s): Financial stability, Monetary policy and uncertainty JEL Code(s): C, C0, C01, E, E5, E50, G, G0, G01
Market Expectations and Option Prices: Evidence for the Can$/US$ Exchange Rate Staff Discussion Paper 2010-2 Alejandro García, Andrei Prokopiw Security prices contain valuable information that can be used to make a wide variety of economic decisions. To extract this information, a model is required that relates market prices to the desired information, and that ideally can be implemented using timely and low-cost methods. Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods, Exchange rates, Financial markets JEL Code(s): C, C0, C00, C02, G, G1, G13