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on Forecasting |
| By: | Herman O. Stekler (Department of Economics The George Washington University); David Sendor; Richard Verlander |
| Abstract: | A great amount of effort is spent in forecasting the outcome of sporting events, but few papers have focused exclusively on the characteristics of sports forecasts. Rather, many papers have been written about the efficiency of sports betting markets. As it turns out, it is possible to derive considerable information about the forecasts and the forecasting process from the studies that tested the markets for economic efficiency. Moreover, the huge number of observations provided by betting markets makes it possible to obtain robust tests of various forecasting hypotheses. This paper is concerned with a number of forecasting topics in horse racing and several team sports. The first topic involves the type of forecast that is made: picking a winner or predicting whether a particular team beats the point spread. Different evaluation procedures will be examined and alternative forecasting methods (models, experts, and the market) will be compared. The paper also examines the evidence about the existence of biases in the forecasts and concludes with the applicability of these results to forecasting in general. |
| Keywords: | sports forecasting; betting markets; efficiency; bias; sports models |
| Date: | 2009–12 |
| URL: | http://d.repec.org/n?u=RePEc:gwc:wpaper:2009-002&r=for |
| By: | Herman Stekler (Department of Economics The George Washington University); Ullrich Heilemann |
| Abstract: | The major focus of this paper is to determine whether the accuracy of German macroeconomic forecasts has improved over time. We examine one-year-ahead forecasts of real GDP and inflation for the years 1967 to 2008 made by three major German forecasting groups and the OECD. We examine the accuracy of the forecasts over the entire period and in four sub-periods. We conclude that, with some exceptions, the errors of the German forecasters were similar to those of their U.S. and U.K. counterparts. While the absolute size of the forecast errors has declined, this is not the case for relative accuracy. A benchmark comparison of these predictions with the ex post forecasts of a macroeconometric model indicates that the quality of the growth forecasts can be improved but that the expected increase in accuracy may not be substantial. |
| Keywords: | Forecast evaluations; macroeconomic forecasting; accuracy limits |
| JEL: | E37 |
| Date: | 2010–02 |
| URL: | http://d.repec.org/n?u=RePEc:gwc:wpaper:2010-001&r=for |
| By: | Francesco Ravazzolo (Norges Bank (Central Bank of Norway)); Shaun P. Vahey |
| Abstract: | We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents the univariate dynamic process followed by a single disaggregate variable. The ensemble produced from these components approximates the many unknown relationships between the disaggregates and the aggregate by using time-varying weights on the component forecast densities. In our application, we use the disaggregate ensemble approach to forecast US Personal Consumption Expenditure in°ation from 1997Q2 to 2008Q1. Our ensemble combining the evidence from 11 disaggregate series outperforms an aggregate autoregressive benchmark, and an aggregate time-varying parameter specification in density forecasting. |
| Keywords: | Ensemble forecasting, disaggregates |
| JEL: | C11 C32 C53 E37 E52 |
| Date: | 2010–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:bno:worpap:2010_02&r=for |
| By: | Dominique Guegan (Centre d'Economie de la Sorbonne - Paris School of Economics); Patrick Rakotomarolahy (Centre d'Economie de la Sorbonne) |
| Abstract: | The aim of this paper is to introduce a new methodology to forecast the monthly economic indicators used in the Gross Domestic Product (GDP) modelling in order to improve the forecasting accuracy. Our approach is based on multivariate k-nearest neighbors method and radial basis function method for which we provide new theoretical results. We apply these two methods to compute the quarter GDP on the Euro-zone, comparing our approach, with GDP obtained when we estimate the monthly indicators with a linear model, which is often used as a benchmark. |
| Keywords: | k-nearest neighbors method, radial basis function method, non-parametric forecasts, GDP, Euro-area. |
| JEL: | C22 C53 E32 |
| Date: | 2010–01 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:10013&r=for |
| By: | Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Patrick Rakotomarolahy (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I) |
| Abstract: | The aim of this paper is to introduce a new methodology to forecast the monthly economic indicators used in the Gross Domestic Product (GDP) modelling in order to improve the forecasting accuracy. Our approach is based on multivariate k-nearest neighbors method and radial basis function method for which we provide new theoretical results. We apply these two methods to compute the quarter GDP on the Euro-zone, comparing our approach, with GDP obtained when we estimate the monthly indicators with a linear model, which is often used as a benchmark. |
| Keywords: | k-nearest neighbors method, radial basis function method, non-parametric, forecasts, GDP, Euro-area. |
| Date: | 2010–01 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00461711_v1&r=for |
| By: | Korobilis, Dimitris |
| Abstract: | This paper develops methods for automatic selection of variables in forecasting Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic (linear and nonlinear) VARs. The performance of the proposed variable selection method is assessed in a small Monte Carlo experiment, and in forecasting 4 macroeconomic series of the UK using time-varying parameters vector autoregressions (TVP-VARs). Restricted models consistently improve upon their unrestricted counterparts in forecasting, showing the merits of variable selection in selecting parsimonious models. |
| Keywords: | Forecasting; variable selection; time-varying parameters; Bayesian |
| JEL: | C32 C53 C52 E37 C11 E47 |
| Date: | 2009–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:21124&r=for |
| By: | Chang, C.; McAleer, M.J.; Tansuchat, R. (Erasmus Econometric Institute) |
| Abstract: | Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover and asymmetric effects across and within the four markets, using three multivariate GARCH models, namely the constant conditional correlation (CCC), vector ARMA-GARCH (VARMA-GARCH) and vector ARMA-asymmetric GARCH (VARMA-AGARCH) models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecast conditional correlations between pairs of crude oil returns have both positive and negative trends. Moreover, the optimal hedge ratios and optimal portfolio weights of crude oil across different assets and market portfolios are evaluated in order to provide important policy implications for risk management in crude oil markets. |
| Keywords: | volatility spillovers;multivariate GARCH;conditional correlation;crude oil prices;spot returns;forward returns;futures returns |
| Date: | 2010–03–02 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:eureir:1765018329&r=for |
| By: | Michael Artis; Marianne Sensier |
| Abstract: | This paper applies a business cycle dating algorithm to monthly North West county and local authority district claimant count data to assess turning points in the economic cycle of sub-regions. We date the transition of all districts of the North West into recession beginning in June 2007. By utilising manufacturing and service sector survey information in a logistic regression model we forecast the continuation of the recession for North West region’s employment cycle in the first quarter of 2010. A longer term forecast with the Land Registry’s house price index predicts a transition to an expansion phase in the fourth quarter of 2010. |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:man:cgbcrp:136&r=for |
| By: | McAleer, Michael; Jimenez-Martin, Juan-Angel; Perez Amaral, Teodosio |
| Abstract: | In this paper we advance the idea that optimal risk management under the Basel II Accord will typically require the use of a combination of different models of risk. This idea is illustrated by analyzing the best empirical models of risk for five stock indexes before, during, and after the 2008-09 financial crisis. The data used are the Dow Jones Industrial Average, Financial Times Stock Exchange 100, Nikkei, Hang Seng and Standard and Poor’s 500 Composite Index. The primary goal of the exercise is to identify the best models for risk management in each period according to the minimization of average daily capital requirements under the Basel II Accord. It is found that the best risk models can and do vary before, during and after the 2008-09 financial crisis. Moreover, it is found that an aggressive risk management strategy, namely the supremum strategy that combines different models of risk, can result in significant gains in average daily capital requirements, relative to the strategy of using single models, while staying within the limits of the Basel II Accord. |
| Keywords: | Optimal risk management; average daily capital requirements; alternative risk strategies; value-at-risk forecasts; combining risk models |
| JEL: | G11 C53 C22 G32 |
| Date: | 2009–09–19 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:20975&r=for |
| By: | Mumtaz, Haroon (Bank of England); Sunder-Plassmann, Laura (University of Minnesota) |
| Abstract: | The aim of this paper is to explore the evolution of real exchange rate dynamics over time. We use a time-varying structural vector autoregression to investigate the role of demand, supply and nominal shocks and consider their impact on, and contribution to fluctuations in, the real exchange rate, output growth and inflation in four major economies over the past four decades. Our analysis therefore extends recent empirical research on evolving macroeconomic dynamics which has primarily focused on inflation and output and the time-varying impact of monetary policy on these variables. In addition we generalise recent VAR studies on exchange rate dynamics where the analysis is limited to a time-invariant setting. Our main results are as follows. The transmission of demand, supply and nominal shocks to the real exchange rate, output and inflation has changed substantially over time. Demand shocks have a larger impact on the real exchange rate after the mid-1980s for the United Kingdom, euro area and Japan and after the mid-1990s for Canada. Nominal shocks had a larger impact on output and inflation during the 1970s relative to the recent past. The forecast error variance of the real exchange rate is explained mainly by demand shocks with a smaller role for nominal shocks. |
| Keywords: | Real exchange rate; time-varying VAR; sign restrictions; Bayesian estimation |
| JEL: | C32 E42 F31 F33 |
| Date: | 2010–03–10 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0382&r=for |
| By: | Torben G. Andersen (Kellogg School of Management, Northwestern University, Evanston, IL; NBER, Cambridge, MA; and CREATES, Aarhus, Denmark); Luca Benzoni (Federal Reserve Bank of Chicago, Chicago, Illinois, USA.) |
| Abstract: | We give an overview of a broad class of models designed to capture stochastic volatility in financial markets, with illustrations of the scope of application of these models to practical finance problems. In a broad sense, this model class includes GARCH, but we focus on a narrower set of specifications in which volatility follows its own random process and is therefore a latent factor. These stochastic volatility specifications fit naturally in the continuous-time finance paradigm, and there- fore serve as a prominent tool for a wide range of pricing and hedging applications. Moreover, the continuous-time paradigm of financial economics is naturally linked with the theory of volatility mod- eling and forecasting, and in particular with the practice of constructing ex-post volatility measures from high-frequency intraday data (realized volatility). One drawback is that in this setting volatility is not measurable with respect to observable information, and this feature complicates estimation and inference. Further, the presence of an additional state variable|volatility|renders the model less tractable from an analytic perspective. New estimation methods, combined with model restrictions that allow for closed-form solutions, make it possible to address these challenges while keeping the model consistent with the main properties of the data. |
| Keywords: | Stochastic Volatility, Realized Volatility, Implied Volatility, Options, Volatility Smirk, Volatility Smile, Dynamic Term Structure Models, Affine Models |
| JEL: | E43 G12 |
| Date: | 2010–02–25 |
| URL: | http://d.repec.org/n?u=RePEc:aah:create:2010-10&r=for |
| By: | Edouard Debonneuil |
| Abstract: | The Lee Carter modelling framework is widely used because of its simplicity and robustness despite its inability to model specific cohort effects. A large number of extensions have been proposed that model cohort effects but there is no consensus. It is difficult to simultaneously account for cohort effects and age-adjusted improvements and we here test a simple model that accounts for both: we simply add a non age-adjusted cohort component to the Lee Carter framework. This is a trade-off between accuracy and robustness but, for various countries present in the Human Mortality Database and compared to various models, the model accurately fits past mortality data and gives good backtesting projections. |
| Date: | 2010–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1003.1802&r=for |