C12 - Hypothesis Testing: General

• Bitcoin Awareness and Usage in Canada: An Update

  Staff Analytical Note 2018-23 Christopher Henry, Kim Huynh, Gradon Nicholls

  The results of our 2017 Bitcoin Omnibus Survey (December 12 to 15, 2017) when compared with those from 2016 show that Bitcoin “awareness” increased from 64 to 85 per cent, while ownership increased from 2.9 to 5.0 per cent. Most Bitcoin purchasers are using the cryptocurrency as an investment and not as a means of payment for goods or services.

  Content Type(s): Staff Research, Staff Analytical Notes Topic(s): Bank notes, Digital Currencies and Fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, E, E4

• Bitcoin Awareness and Usage in Canada

  Staff Working Paper 2017-56 Christopher Henry, Kim Huynh, Gradon Nicholls

  There has been tremendous discussion of Bitcoin, digital currencies and FinTech. However, there is limited empirical evidence of Bitcoin’s adoption and usage. We propose a methodology to collect a nationally representative sample using the Bitcoin Omnibus Survey (BTCOS) to track the ubiquity and usage of Bitcoin in Canada.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Bank notes, Digital Currencies and Fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, E, E4

• The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Estimation of the Total Private Cost for Large Businesses

  Technical Report No. 110 Valéry Dongmo Jiongo

  The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods faced low response rates and outliers in sample data for two of its retailer strata: chains and large independent businesses. This technical report investigates whether it is appropriate to combine these two strata to produce more accurate estimates of the total private cost to large businesses of the main payment methods.

  Content Type(s): Technical Reports Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C12, C8, C83

• Small‐Sample Tests for Stock Return Predictability with Possibly Non‐Stationary Regressors and GARCH‐Type Effects

  Staff Working Paper 2017-10 Sermin Gungor, Richard Luger

  We develop a simulation-based procedure to test for stock return predictability with multiple regressors. The process governing the regressors is left completely free and the test procedure remains valid in small samples even in the presence of non-normalities and GARCH-type effects in the stock returns.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Asset Pricing, Econometric and statistical methods, Financial markets JEL Code(s): C, C1, C12, C3, C32, G, G1, G14

• Early Warning of Financial Stress Events: A Credit-Regime-Switching Approach

  Staff Working Paper 2016-21 Fuchun Li, Hongyu Xiao

  We propose an early warning model for predicting the likelihood of a financial stress event for a given future time, and examine whether credit plays an important role in the model as a non-linear propagator of shocks.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Econometric and statistical methods, Financial stability JEL Code(s): C, C1, C12, C14, G, G0, G01, G1, G17

• Testing for the Diffusion Matrix in a Continuous-Time Markov Process Model with Applications to the Term Structure of Interest Rates

  Staff Working Paper 2015-17 Fuchun Li

  The author proposes a test for the parametric specification of each component in the diffusion matrix of a d-dimensional diffusion process. Overall, d (d-1)/2 test statistics are constructed for the off-diagonal components, while d test statistics are constructed for the main diagonal components.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Asset Pricing, Econometric and statistical methods, Interest rates JEL Code(s): C, C1, C12, C14, E, E1, E17, E4, E43, G, G1, G12, G2, G20

• Bootstrap Tests of Mean-Variance Efficiency with Multiple Portfolio Groupings

  Staff Working Paper 2014-51 Sermin Gungor, Richard Luger

  We propose double bootstrap methods to test the mean-variance efficiency hypothesis when multiple portfolio groupings of the test assets are considered jointly rather than individually.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Asset Pricing, Econometric and statistical methods, Financial markets JEL Code(s): C, C1, C12, C14, C15, G, G1, G12

• Multivariate Tests of Mean-Variance Efficiency and Spanning with a Large Number of Assets and Time-Varying Covariances

  Staff Working Paper 2013-16 Sermin Gungor, Richard Luger

  We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Asset Pricing, Econometric and statistical methods, Financial markets JEL Code(s): C, C1, C12, C15, C3, C33, G, G1, G11, G12

• A Semiparametric Early Warning Model of Financial Stress Events

  Staff Working Paper 2013-13 Ian Christensen, Fuchun Li

  The authors use the Financial Stress Index created by the International Monetary Fund to predict the likelihood of financial stress events for five developed countries: Canada, France, Germany, the United Kingdom and the United States.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Econometric and statistical methods, Financial stability JEL Code(s): C, C1, C12, C14, G, G0, G01, G1, G17

• Testing Linear Factor Pricing Models with Large Cross-Sections: A Distribution-Free Approach

  Staff Working Paper 2010-36 Sermin Gungor, Richard Luger

  We develop a finite-sample procedure to test the beta-pricing representation of linear factor pricing models that is applicable even if the number of test assets is greater than the length of the time series. Our distribution-free framework leaves open the possibility of unknown forms of non-normalities, heteroskedasticity, time-varying correlations, and even outliers in the asset returns.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Econometric and statistical methods, Financial markets JEL Code(s): C, C1, C12, C14, C3, C33, G, G1, G11, G12