Staff research, Publications
-
-
-
Cash Management and Payment Choices: A Simulation Model with International Comparisons
Despite various payment innovations, today, cash is still heavily used to pay for low-value purchases. This paper develops a simulation model to test whether standard implications of the theory on cash management and payment choices can explain the use of payment instruments by transaction size. -
Do Oil Price Increases Cause Higher Food Prices?
U.S. retail food price increases in recent years may seem large in nominal terms, but after adjusting for inflation have been quite modest even after the change in U.S. biofuel policies in 2006. In contrast, increases in the real prices of corn, soybeans, wheat and rice received by U.S. farmers have been more substantial and can be linked in part to increases in the real price of oil. -
Regime Switches in the Risk-Return Trade-Off
This paper deals with the estimation of the risk-return trade-off. We use a MIDAS model for the conditional variance and allow for possible switches in the risk-return relation through a Markov-switching specification. -
-
Funding Advantage and Market Discipline in the Canadian Banking Sector
We employ a comprehensive data set and a variety of methods to provide evidence on the magnitude of large banks’ funding advantage in Canada, and on the extent to which market discipline exists across different securities issued by the Canadian banks. -
-
A Distributional Approach to Realized Volatility
This paper proposes new measures of the integrated variance, measures which use high-frequency bid-ask spreads and quoted depths. The traditional approach assumes that the mid-quote is a good measure of frictionless price. -
Volatility Forecasting when the Noise Variance Is Time-Varying
This paper explores the volatility forecasting implications of a model in which the friction in high-frequency prices is related to the true underlying volatility. The contribution of this paper is to propose a framework under which the realized variance may improve volatility forecasting if the noise variance is related to the true return volatility.