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201 Results

The Framework for Risk Identification and Assessment

Technical Report No. 113 Cameron MacDonald, Virginie Traclet
Risk assessment models are an important component of the Bank’s analytical tool kit for assessing the resilience of the financial system. We describe the Framework for Risk Identification and Assessment (FRIDA), a suite of models developed at the Bank of Canada to quantify the impact of financial stability risks to the broader economy and a range of financial system participants (households, businesses and banks).
Content Type(s): Staff research, Technical reports Research Topic(s): Economic models, Financial institutions, Financial stability, Housing JEL Code(s): C, C3, C5, C6, C7, D, D1, E, E0, E00, E2, E27, E3, E37, E4, E47, G, G0, G2, G21

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.

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 Research Topic(s): Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58

Nowcasting Canadian Economic Activity in an Uncertain Environment

Staff Discussion Paper 2018-9 Tony Chernis, Rodrigo Sekkel
This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components.
Content Type(s): Staff research, Staff discussion papers Research Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C53, E, E3, E37, E5, E52

Analysis of Asymmetric GARCH Volatility Models with Applications to Margin Measurement

Staff Working Paper 2018-21 Elena Goldman, Xiangjin Shen
We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH (GTARCH) family and propose a more general Spline-GTARCH model, which captures high-frequency return volatility, low-frequency macroeconomic volatility as well as an asymmetric response to past negative news in both autoregressive conditional heteroscedasticity (ARCH) and GARCH terms.

State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models

Staff Working Paper 2018-14 Luis Uzeda
Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood.

Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?

The official Chinese labour market indicators have been seen as problematic, given their small cyclical movement and their only-partial capture of the labour force. In our paper, we build a monthly Chinese labour market conditions index (LMCI) using text analytics applied to mainland Chinese-language newspapers over the period from 2003 to 2017.

Dismiss the Gap? A Real-Time Assessment of the Usefulness of Canadian Output Gaps in Forecasting Inflation

We use a new real-time database for Canada to study various output gap measures. This includes recently developed measures based on models incorporating many variables as inputs (and therefore requiring real-time data for many variables).

What Drives Interbank Loans? Evidence from Canada

Staff Working Paper 2018-5 Narayan Bulusu, Pierre Guérin
We identify the drivers of unsecured and collateralized loan volumes, rates and haircuts in Canada using the Bayesian model averaging approach to deal with model uncertainty. Our results suggest that the key friction driving behaviour in this market is the collateral reallocation cost faced by borrowers.
Content Type(s): Staff research, Staff working papers Research Topic(s): Financial markets, Wholesale funding JEL Code(s): C, C5, C55, E, E4, E43, G, G2, G23

A Calibrated Model of Intraday Settlement

Staff Discussion Paper 2018-3 Héctor Pérez Saiz, Siddharth Untawala, Gabriel Xerri
This paper estimates potential exposures, netting benefits and settlement gains by merging retail and wholesale payments into batches and conducting multiple intraday settlements in this hypothetical model of a single "calibrated payments system." The results demonstrate that credit risk exposures faced by participants in the system are largely dependent on their relative activity in the retail and wholesale payments systems.
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