We present a new matrix-logarithm model of the realized covariance matrix of stock returns. The model uses latent factors which are functions of both lagged volatility and returns. The model has several advantages: it is parsimonious; it does not require imposing parameter restrictions; and, it...

The authors describe the key features of a new large-scale Canadian macroeconomic forecasting model developed over the past two years at the Bank of Canada. The new model, called LENS for Large Empirical and Semi-structural model, uses a methodology similar to the Federal Reserve Board’s...

Inflation targeting (IT) had originally been introduced as a device to bring inflation down and stabilize it at low levels. Given the current environment of persistently weak inflation in many advanced economies, IT central banks must now bring inflation up to target. In this paper, the author...

The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market...

Information on the allocation and pricing of over-the-counter (OTC) markets is scarce. Furfine (1999) pioneered an algorithm that provides transaction-level data on the OTC interbank lending market. The veracity of the data identified, however, is not well established. Using permutation methods,...

This paper studies the formation of consumers’ inflation expectations using micro-level data from the Michigan Survey. It shows that beyond the well-established socio-economic determinants of inflation expectations such as gender, income or education, other characteristics such as the...

In this paper, the authors develop a new tool to improve the short-term forecasting of real GDP growth in the euro area and Japan. This new tool, which uses unrestricted mixed-data sampling (U-MIDAS) regressions, allows an evaluation of the usefulness of a wide range of indicators in predicting...

Notwithstanding a resurgence in research on out-of-sample forecasts of the price of oil in recent years, there is one important approach to forecasting the real price of oil which has not been studied systematically to date. This approach is based on the premise that demand for crude oil derives...

The answer as to whether there are gains from pooling real-time oil price forecasts depends on the objective. The approach of combining five of the leading forecasting models with equal weights dominates the strategy of selecting one model and using it for all horizons up to two years. Even more...

Using the prices of crude oil futures contracts, we construct the term structure of crude oil convenience yields out to one-year maturity. The crude oil convenience yield can be interpreted as the interest rate, denominated in barrels of oil, for borrowing a single barrel of oil, and it measures...