C53 - Forecasting and Prediction Methods; Simulation Methods - Bank of Canada
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Bank of Canada RSS Feedsen2024-03-29T02:18:16+00:00On the Tail Risk Premium in the Oil Market
https://www.bankofcanada.ca/2017/11/staff-working-paper-2017-46/
This paper shows that changes in market participants’ fear of rare events implied by crude oil options contribute to oil price volatility and oil return predictability. Using 25 years of historical data, we document economically large tail risk premia that vary substantially over time and significantly forecast crude oil futures and spot returns.2017-11-20T07:47:32+00:00enOn the Tail Risk Premium in the Oil Market2017-11-20Asset pricingEconometric and statistical methodsFinancial marketsStaff Working Paper 2017-46https://www.bankofcanada.ca/wp-content/uploads/2017/11/swp2017-46.pdfOn the Tail Risk Premium in the Oil MarketReinhard EllwangerNovember 2017CC5C53C58DD8D84EE4E44GG1G12G13QQ4Q43A Three‐Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth
https://www.bankofcanada.ca/2017/06/staff-discussion-paper-2017-8/
This paper estimates a three‐frequency dynamic factor model for nowcasting Canadian provincial gross domestic product (GDP). Canadian provincial GDP is released by Statistics Canada on an annual basis only, with a significant lag (11 months).2017-06-12T11:50:01+00:00enA Three‐Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth2017-06-12Business fluctuations and cyclesEconometric and statistical methodsRegional economic developmentsStaff Discussion Paper 2017-8https://www.bankofcanada.ca/wp-content/uploads/2017/06/sdp2017-8.pdfA Three‐Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP GrowthTony ChernisGabriella VelascoCalista CheungJune 2017CC5C53EE3E32E37RR1R11Assessing the Predictive Ability of Sovereign Default Risk on Exchange Rate Returns
https://www.bankofcanada.ca/2017/05/staff-working-paper-2017-19/
Increased sovereign credit risk is often associated with sharp currency movements. Therefore, expectations of the probability of a sovereign default event can convey important information regarding future movements of exchange rates.2017-05-17T08:24:48+00:00enAssessing the Predictive Ability of Sovereign Default Risk on Exchange Rate Returns2017-05-17Econometric and statistical methodsExchange ratesInternational financial marketsStaff Working Paper 2017-19https://www.bankofcanada.ca/wp-content/uploads/2017/05/swp2017-19.pdfAssessing the Predictive Ability of Sovereign Default Risk on Exchange Rate ReturnsClaudia ForoniFrancesco RavazzoloBarbara SadabaMay 2017CC2C22C5C52C53FF3F31Markov‐Switching Three‐Pass Regression Filter
https://www.bankofcanada.ca/2017/04/staff-working-paper-2017-13/
We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes.2017-04-20T13:08:27+00:00enMarkov‐Switching Three‐Pass Regression Filter2017-04-20Econometric and statistical methodsStaff Working Paper 2017-13https://www.bankofcanada.ca/wp-content/uploads/2017/04/swp2017-13.pdfMarkov‐Switching Three‐Pass Regression FilterPierre GuérinDanilo Leiva-LeonMassimiliano MarcellinoApril 2017CC2C22C23C5C53Assessing the Business Outlook Survey Indicator Using Real-Time Data
https://www.bankofcanada.ca/2017/04/staff-discussion-paper-2017-5/
Every quarter, the Bank of Canada conducts quarterly consultations with businesses across Canada, referred to as the Business Outlook Survey (BOS). A principal-component analysis conducted by Pichette and Rennison (2011) led to the development of the BOS indicator, which summarizes survey results and is used by the Bank as a gauge of overall business sentiment.2017-04-03T10:30:19+00:00enAssessing the Business Outlook Survey Indicator Using Real-Time Data2017-04-03Business fluctuations and cyclesRegional economic developmentsStaff Discussion Paper 2017‐5https://www.bankofcanada.ca/wp-content/uploads/2017/04/sdp2017-5.pdfAssessing the Business Outlook Survey Indicator Using Real-Time DataLise PichetteMarie-Noëlle RobitailleApril 2017CC5C53C8C82EE3E37A Dynamic Factor Model for Nowcasting Canadian GDP Growth
https://www.bankofcanada.ca/2017/02/staff-working-paper-2017-2/
This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data.2017-02-02T13:04:19+00:00enA Dynamic Factor Model for Nowcasting Canadian GDP Growth2017-02-02Business fluctuations and cyclesEconometric and statistical methodsStaff Working Paper 2017-2https://www.bankofcanada.ca/wp-content/uploads/2017/02/swp2017-2.pdfA Dynamic Factor Model for Nowcasting Canadian GDP GrowthTony ChernisRodrigo SekkelFebruary 2017CC3C32C38C5C53EE3E37