C5 - Econometric Modeling
-
-
Improving Overnight Loan Identification in Payments Systems
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. -
May 13, 2014
The Art and Science of Forecasting the Real Price of Oil
Forecasts of the price of crude oil play a significant role in the conduct of monetary policy, especially for commodity producers such as Canada. This article presents a range of recently developed forecasting models that, when pooled together, can generate, on average, more accurate forecasts of the price of oil than the oil futures curve. It also illustrates how policy-makers can evaluate the risks associated with the baseline oil price forecast and how they can determine the causes of past oil price fluctuations. -
Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work
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 helps forecast the real price of oil in physical markets. -
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. -
Which Parametric Model for Conditional Skewness?
This paper addresses an existing gap in the developing literature on conditional skewness. We develop a simple procedure to evaluate parametric conditional skewness models. This procedure is based on regressing the realized skewness measures on model-implied conditional skewness values. -
Volatility and Liquidity Costs
Observed high-frequency prices are contaminated with liquidity costs or market microstructure noise. Using such data, we derive a new asset return variance estimator inspired by the market microstructure literature to explicitly model the noise and remove it from observed returns before estimating their variance. -
Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach
The U.S. Energy Information Administration regularly publishes short-term forecasts of the price of crude oil. -
Are Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis
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.