C5 - Econometric Modeling - Bank of Canada
https://www.bankofcanada.ca/rss-feeds/
Bank of Canada RSS Feedsen2024-03-29T09:07:27+00:00A Distributional Approach to Realized Volatility
https://www.bankofcanada.ca/2013/12/working-paper-2013-49/
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.2013-12-20T10:14:03+00:00enA Distributional Approach to Realized Volatility2013-12-20Econometric and statistical methodsFinancial marketsWorking Paper 2013-49https://www.bankofcanada.ca/wp-content/uploads/2013/12/wp2013-49.pdfA Distributional Approach to Realized VolatilitySelma ChakerNour MeddahiDecember 2013CC1C14C5C51C58Volatility Forecasting when the Noise Variance Is Time-Varying
https://www.bankofcanada.ca/2013/12/working-paper-2013-48/
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.2013-12-20T10:13:05+00:00enVolatility Forecasting when the Noise Variance Is Time-Varying2013-12-20Econometric and statistical methodsFinancial marketsWorking Paper 2013-48https://www.bankofcanada.ca/wp-content/uploads/2013/12/wp2013-48.pdfVolatility Forecasting when the Noise Variance Is Time-VaryingSelma ChakerNour MeddahiDecember 2013CC1C14C5C51C58Which Parametric Model for Conditional Skewness?
https://www.bankofcanada.ca/2013/09/working-paper-2013-32/
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.2013-09-06T09:08:40+00:00enWhich Parametric Model for Conditional Skewness?2013-09-06Econometric and statistical methodsWorking Paper 2013-32 https://www.bankofcanada.ca/wp-content/uploads/2013/09/wp2013-32.pdfWhich Parametric Model for Conditional Skewness?Bruno FeunouMohammad R. Jahan-ParvarRoméo TedongapSeptember 2013CC2C22C5C51GG1G12G15Volatility and Liquidity Costs
https://www.bankofcanada.ca/2013/08/working-paper-2013-29/
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.2013-08-20T10:09:42+00:00enVolatility and Liquidity Costs2013-08-20Econometric and statistical methodsFinancial marketsMarket structure and pricingWorking Paper 2013-29https://www.bankofcanada.ca/wp-content/uploads/2013/08/wp2013-29.pdfVolatility and Liquidity CostsSelma ChakerAugust 2013CC1C14C5C51C58GG2G20Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach
https://www.bankofcanada.ca/2013/08/working-paper-2013-28/
The U.S. Energy Information Administration regularly publishes short-term forecasts of the price of crude oil.2013-08-20T09:22:18+00:00enForecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach2013-08-20Econometric and statistical methodsInternational topicsWorking Paper 2013-28https://www.bankofcanada.ca/wp-content/uploads/2013/08/wp2013-28.pdfForecasting the Real Price of Oil in a Changing World: A Forecast Combination ApproachChristiane BaumeisterLutz KilianAugust 2013CC5C53EE3E32QQ4Q43Are Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis
https://www.bankofcanada.ca/2013/08/working-paper-2013-25/
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.2013-08-15T12:06:08+00:00enAre Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger Hypothesis2013-08-15Econometric and statistical methodsInternational topicsWorking Paper 2013-25https://www.bankofcanada.ca/wp-content/uploads/2013/08/wp2013-25.pdfAre Product Spreads Useful for Forecasting? An Empirical Evaluation of the Verleger HypothesisChristiane BaumeisterLutz KilianXiaoqing ZhouAugust 2013CC5C53GG1G15QQ4Q43CSI: A Model for Tracking Short-Term Growth in Canadian Real GDP
https://www.bankofcanada.ca/wp-content/uploads/2013/08/boc-review-summer13-binette.pdf
Canada’s Short-Term Indicator (CSI) is a new model that exploits the information content of 32 indicators to produce daily updates to forecasts of quarterly real GDP growth. The model is a data-intensive, judgment-free approach to short-term forecasting. While CSI’s forecasts at the start of the quarter are not very accurate, the model’s accuracy increases appreciably as more information becomes available. CSI is the latest addition to a wide range of models and information sources that the Bank of Canada uses, combined with expert judgment, to produce its short-term forecasts.2013-08-15T08:57:04+00:00enCSI: A Model for Tracking Short-Term Growth in Canadian Real GDP2013-08-15The Accuracy of Short-Term Forecast Combinations
https://www.bankofcanada.ca/wp-content/uploads/2013/08/boc-review-summer13-granziera.pdf
This article examines whether combining forecasts of real GDP from different models can improve forecast accuracy and considers which model-combination methods provide the best performance. In line with previous literature, the authors find that combining forecasts generally improves forecast accuracy relative to various benchmarks. Unlike several previous studies, however, they find that, rather than assigning equal weights to each model, unequal weighting based on the past forecast performance of models tends to improve accuracy when forecasts across models are substantially different.2013-08-15T08:53:24+00:00enThe Accuracy of Short-Term Forecast Combinations2013-08-15Big Data Analysis: The Next Frontier
https://www.bankofcanada.ca/wp-content/uploads/2013/08/boc-review-summer13-armah.pdf
The formulation of monetary policy at the Bank of Canada relies on the analysis of a broad set of economic information. Greater availability of immediate and detailed information would improve real-time economic decision making. Technological advances have provided an opportunity to exploit “big data” - the vast amount of digital data from business transactions, social media and networked computers. Big data can be a complement to traditional information sources, offering fresh insight for the monitoring of economic activity and inflation.2013-08-15T08:46:14+00:00enBig Data Analysis: The Next Frontier2013-08-15What Central Bankers Need to Know about Forecasting Oil Prices
https://www.bankofcanada.ca/2013/05/working-paper-2013-15/
Forecasts of the quarterly real price of oil are routinely used by international organizations and central banks worldwide in assessing the global and domestic economic outlook, yet little is known about how best to generate such forecasts. Our analysis breaks new ground in several dimensions.2013-05-29T12:50:11+00:00enWhat Central Bankers Need to Know about Forecasting Oil Prices2013-05-29Econometric and statistical methodsInternational topicsWorking Paper 2013-15https://www.bankofcanada.ca/wp-content/uploads/2013/05/wp2013-15.pdfWhat Central Bankers Need to Know about Forecasting Oil PricesChristiane BaumeisterLutz KilianMay 2013CC5C53EE3E32QQ4Q43