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on Forecasting |
| By: | Xin Jin (Department of Economics, University of Toronto, Canada); John M. Maheu (Department of Economics, University of Toronto, Canada; RCEA, Italy) |
| Abstract: | This paper proposes new dynamic component models of returns and realized covariance (RCOV) matrices based on time-varying Wishart distributions. Bayesian estimation and model comparison is conducted with a range of multivariate GARCH models and existing RCOV models from the literature. The main method of model comparison consists of a term-structure of density forecasts of returns for multiple forecast horizons. The new joint return-RCOV models provide superior density forecasts for returns from forecast horizons of 1 day to 3 months ahead as well as improved point forecasts for realized covariances. Global minimum variance portfolio selection is improved for forecast horizons up to 3 weeks out. |
| Keywords: | Wishart distribution, predictive likelihoods, density forecasts, realized covariance targeting, MCMC |
| JEL: | C11 C32 C53 G17 |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:49_12&r=for |
| By: | Maximo Camacho; Jaime Martinez-Martin |
| Abstract: | This paper proposes two refinements to the single-index dynamic factor model developed by Aruoba and Diebold (AD, 2010) to monitor US economic activity in real time. First, we adapt the model to include survey data and financial indicators. Second, we examine the predictive performance of the model when the goal is to forecast GDP growth. We find that our model is unequivocally the preferred alternative to compute backcasts. In nowcasting and forecasting, our model is able to forecast growth as well as AD and much better than several baseline alternatives. In addition, we find that our model could be used to predict more accurately the US business cycles. |
| Keywords: | real-time forecasting, US GDP, business cycles. |
| JEL: | E32 C22 E27 |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:bbv:wpaper:1210&r=for |
| By: | Christian , Pierdzioch (Helmut Schmidt University, Hamburg); Rülke, Jan-Christoph (WHU – Otto Beisheim School of Management,); Stadtmann, Georg (Europa-Universität Viadrina) |
| Abstract: | Survey data of forecasts of the housing market may provide a particularly rich data nvironment for researchers and policymakers to study developments in housing markets. Based on the approach advanced by Elliott et al. (Rev. Ec. Studies. 72, 1197-1125, 2005), we studied the properties of a large set of survey data of housing starts in the United States. We document the heterogeneity of forecasts, analyze the shape of forecasters’ loss function, study the rationality of forecasts, and the temporal variation in forecasts. |
| Keywords: | Housing starts; Loss function; Rationality of forecasts |
| JEL: | D84 |
| Date: | 2012–06–27 |
| URL: | http://d.repec.org/n?u=RePEc:ris:vhsuwp:2012_118&r=for |
| By: | Claudia Godbout (Bank of Canada, International Department, 234 Wellington Street, Ottawa, Ontario K1A 0G9, Canada.); Marco J. Lombardi (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.) |
| Abstract: | While the usefulness of factor models has been acknowledged over recent years, little attention has been devoted to the forecasting power of these models for the Japanese economy. In this paper, we aim at assessing the relative performance of factor models over different samples, including the recent financial crisis. To do so, we construct factor models to forecast Japanese GDP and its subcomponents, using 38 data series (including daily, monthly and quarterly variables) over the period 1991 to 2010. Overall, we find that factor models perform well at tracking GDP movements and anticipating turning points. For most of the components, we report that factor models yield lower forecasting errors than a simple AR process or an indicator model based on Purchasing Managers' Indicators (PMIs). In line with previous studies, we conclude that the largest improvements in terms of forecasting accuracy are found for more volatile periods, such as the recent financial crisis. However, unlike previous studies, we do not find evident links between the volatility of the components and the relative advantage of using factor models. Finally, we show that adding the PMI index as an independent explanatory variable improves the forecasting properties of the factor models. JEL Classification: C50, C53, E37, E47. |
| Keywords: | Japan, forecasting, nowcasting, factor models, mixed frequency. |
| Date: | 2012–03 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20121428&r=for |
| By: | Pierdzioch, Christian; Rülke, Jan Christoph; Stadtmann, Georg |
| Abstract: | We used Wall Street Journal survey data for the period 2006 - 2010 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices, where anti-herding is less strong in the case of medium-term forecasts, especially in the case of housing starts. -- |
| Keywords: | Forecasts of house prices and housing starts,Herding |
| JEL: | E37 D84 C33 |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:euvwdp:318&r=for |
| By: | Yin Liao |
| Abstract: | Recent literature has focuses on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets. |
| JEL: | C13 C32 C52 C53 G17 |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:acb:camaaa:2012-26&r=for |
| By: | Mark J. Jensen (Federal Reserve Bank of Atlanta, USA); John M. Maheu (University of Toronto, Canada; RCEA, Italy) |
| Abstract: | In this paper we extend the parametric, asymmetric, stochastic volatility model (ASV), where returns are correlated with volatility, by flexibly modeling the bivariate distribution of the return and volatility innovations nonparametrically. Its novelty is in modeling the joint, conditional, return-volatility, distribution with a infinite mixture of bivariate Normal distributions with mean zero vectors, but having unknown mixture weights and covariance matrices. This semiparametric ASV model nests stochastic volatility models whose innovations are distributed as either Normal or Student-t distributions, plus the response in volatility to unexpected return shocks is more general than the fixed asymmetric response with the ASV model. The unknown mixture parameters are modeled with a Dirichlet Process prior. This prior ensures a parsimonious, finite, posterior, mixture that bests represents the distribution of the innovations and a straightforward sampler of the conditional posteriors. We develop a Bayesian Markov chain Monte Carlo sampler to fully characterize the parametric and distributional uncertainty. Nested model comparisons and out-of-sample predictions with the cumulative marginal-likelihoods, and one-day-ahead, predictive log-Bayes factors between the semiparametric and parametric versions of the ASV model shows the semiparametric model forecasting more accurate empirical market returns. A major reason is how volatility responds to an unexpected market movement. When the market is tranquil, expected volatility reacts to a negative (positive) price shock by rising (initially declining, but then rising when the positive shock is large). However, when the market is volatile, the degree of asymmetry and the size of the response in expected volatility is muted. In other words, when times are good, no news is good news, but when times are bad, neither good nor bad news matters with regards to volatility. |
| Keywords: | Bayesian nonparametrics, cumulative Bayes factor, Dirichlet process mixture, infinite mixture model, leverage effect, marginal likelihood, MCMC, non-normal, stochastic volatility, volatility-return relationship |
| JEL: | C11 C14 C53 C58 |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:45_12&r=for |
| By: | Mark J. Jensen (Federal Reserve Bank of Atlanta, USA); John M. Maheu (Department of Economics, University of Toronto, Canada; RCEA, Italy) |
| Abstract: | This paper proposes a Bayesian nonparametric modeling approach for the return distribution in multivariate GARCH models. In contrast to the parametric literature the return distribution can display general forms of asymmetry and thick tails. An innite mixture of multivariate normals is given a exible Dirichlet process prior. The GARCH functional form enters into each of the components of this mixture. We discuss conjugate methods that allow for scale mixtures and nonconjugate methods which provide mixing over both the location and scale of the normal components. MCMC methods are introduced for posterior simulation and computation of the predictive density. Bayes factors and density forecasts with comparisons to GARCH models with Student-t innovations demonstrate the gains from our exible modeling approach. |
| JEL: | C11 C14 C32 C58 |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:48_12&r=for |
| By: | Guorui Bian (Department of Statistics East China Normal University.); Michael McAleer (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute, The Netherlands, Department of Quantitative Economics, Complutense University of Madrid, and Institute of Economic Research, Kyoto University.); Wing-Keung Wong (Department of Economics, Hong Kong Baptist University.) |
| Abstract: | In this paper, we develop a modified maximum likelihood (MML) estimator for the multiple linear regression model with underlying student t distribution. We obtain the closed form of the estimators, derive the asymptotic properties, and demonstrate that the MML estimator is more appropriate for estimating the parameters of the Capital Asset Pricing Model by comparing its performance with least squares estimators (LSE) on the monthly returns of US portfolios. The empirical results reveal that the MML estimators are more efficient than LSE in terms of the relative efficiency of one-step-ahead forecast mean square error in small samples. |
| Keywords: | Maximum likelihood estimators; Modified maximum likelihood estimators; Student t family; Capital asset pricing model; Robustness. |
| JEL: | C1 C2 G1 |
| Date: | 2012–04 |
| URL: | http://d.repec.org/n?u=RePEc:ucm:doicae:1209&r=for |
| By: | Luca Gambetti |
| Abstract: | This paper investigates the effects of government spending on the real exchange rate and the trade balance in the US using a new VAR identification procedure based on spending forecast revisions. I find that the real exchange rate appreciates and the trade balance deteriorates after a government spending shock, although the effects are quantitatively small. The findings broadly match the theoretical predictions of the standard Mundell-Fleming model and differ substantially from those existing in literature. Differences are attributable to the fact that, be- cause of fiscal foresight, the government spending is non-fundamental for the variables typically used in open economy VARs. Here, on the contrary, the estimated shock is fundamental. |
| Keywords: | VARs, fiscal policy, twin deficits, trade balance, Mundell-Fleming, forecast revisions, fiscal news, survey of professional forecasters. |
| JEL: | C32 E32 E62 |
| Date: | 2012–06–22 |
| URL: | http://d.repec.org/n?u=RePEc:aub:autbar:907.12&r=for |
| By: | Tesfatsion, Leigh; Aliprantis, Dionysios |
| Abstract: | This study proposes an explicit practical reformulation of the Day-Ahead Market (DAM) design implemented in centrally managed United States wholesale electrical power markets. This reformulation takes into account the financial nature of DAM outcomes as well as the temporal positioning of the DAM on any day D-1 within a cascade of market and administrative processes aimed at ensuring the efficient procurement of adequate power at each operating point of day D. A key aspect of the reformulation is that the non-profit Independent System Operator (ISO) or Regional Transmission Organization (RTO) managing the DAM is permitted to augment generation company supply offers and load-serving entity demand bids with ISO-determined virtual generation offers and demand bids. This added flexibility would help ISOs/RTOs to weigh the cost of alternative resource procurement opportunities and to hedge uncertainty regarding future variable generation and load levels. |
| Keywords: | Day-ahead market; economic dispatch; electrical energy; financial contracts; Forecasting; forward planning; unit commitment; virtual demand bid; virtual supply offer |
| JEL: | D4 D8 G1 Q4 |
| Date: | 2012–06–26 |
| URL: | http://d.repec.org/n?u=RePEc:isu:genres:35243&r=for |
| By: | Luca Gambetti |
| Abstract: | This paper investigates the effects of government spending on the real exchange rate and the trade balance in the US using a new VAR identification procedure based on spending forecast revisions. I find that the real exchange rate appreciates and the trade balance deteriorates after a government spending shock, although the effects are quantitatively small. The findings broadly match the theoretical predictions of the standard Mundell-Fleming model and differ substantially from those existing in literature. Differences are attributable to the fact that, because of fiscal foresight, the government spending is non-fundamental for the variables typically used in open economy VARs. Here, on the contrary, the estimated shock is fundamental. |
| Keywords: | VARs, fiscal policy, twin deficits, trade balance, Mundell-Fleming, forecast revisions, fiscal news, survey of professional forecasters |
| JEL: | C32 E32 E62 |
| Date: | 2012–05 |
| URL: | http://d.repec.org/n?u=RePEc:bge:wpaper:644&r=for |
| By: | de Vincent-Humphreys, Rupert (Bank of England); Noss, Joseph (Bank of England) |
| Abstract: | The prices of derivatives contracts can be used to estimate ‘risk-neutral’ probability density functions that give an indication of the weight investors place on different future prices of their underlying assets, were they risk-neutral. In the likely case that investors are risk-averse, this leads to differences between the risk-neutral probability density and the actual distribution of prices. But if this difference displays a systematic pattern over time, it may be exploited to transform the risk-neutral density into a ‘real-world’ density that better reflect agents’ actual expectations. This work offers a methodology for performing this transformation. The resulting real-world densities may better represent market participants’ views of future prices, and so offer an enhanced means of quantifying the uncertainty around financial variables. Comparison with their risk-neutral equivalents may also reveal new and useful information as to how attitudes towards risk are affecting pricing. |
| Keywords: | Asset prices; derivatives; expectations; options; option-implied density; risk premia; probability density forecasting; probability measure |
| JEL: | G10 G12 G13 |
| Date: | 2012–06–21 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0455&r=for |
| By: | Philip Vermeulen (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany and CEPR.) |
| Abstract: | The survey based monthly US ISM production index and Eurozone manufacturing PMI output index provide early information on industrial output growth before the release of the official industrial production index. I use the Carlson and Parkin probability method to construct monthly growth estimates from the qualitative responses of the US ISM production index and the Eurozone manufacturing PMI output index. I apply the method under different assumptions on the cross-sectional distribution of output growth using the uniform, logistic and Laplace distribution. I show that alternative distribution assumptions lead to very similar estimates. I also test the performance of the different growth estimates in an out of sample forecasting exercise of actual industrial production growth. All growth estimates beat a simple autoregressive model of output growth. Distribution assumptions again matter little most of the time except during the financial crisis when the estimates constructed using the Laplace distributional assumption perform the best. My findings are consistent with recent findings of Bottazzi and Sechi (2006) that the distribution of firm growth rates has a Laplace distribution. JEL Classification: C18, E27. |
| Keywords: | Diffusion index, forecasting, purchasing managers’ surveys, ISM, PMI, qualitative response data, Carlson-Parkin method |
| Date: | 2012–02 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20121417&r=for |
| By: | Ana P. Palacios; J. Miguel Marín; Emiliano Quinto; Michael P. Wiper |
| Abstract: | Bacterial growth models are commonly used for the prediction of microbial safety and the shelf life of perishable foods. Growth is affected by several environmental factors such as temperature, acidity level and salt concentration. In this study, we develop two models to describe bacterial growth for multiple populations under both equal and different environmental conditions. Firstly, a semi-parametric model based on the Gompertz equation is proposed. Assuming that the parameters of the Gompertz equation may vary in relation to the running conditions under which the experiment is performed, we use feed forward neural networks to model the influence of these environmental factors on the growth parameters. Secondly, we propose a more general model which does not assume any underlying parametric form for the growth function. Thus, we consider a neural network as a primary growth model which includes the influencing environmental factors as inputs to the network. One of the main disadvantages of neural networks models is that they are often very difficult to tune which complicates fitting procedures. Here, we show that a simple, Bayesian approach to fitting these models can be implemented via the software package WinBugs. Our approach is illustrated using real experimental Listeria Monocytogenes growth data. |
| Keywords: | Bacterial population modeling, Growth functions, Neural networks, Bayesian inference |
| Date: | 2012–06 |
| URL: | http://d.repec.org/n?u=RePEc:cte:wsrepe:ws121610&r=for |
| By: | Anonymous |
| Abstract: | The purpose of this document is to describe the features of the Medium Term Outlook (MTO) covering the period 2011 to 2021. The MTO is a plausible future for the international and domestic agri-food sectors based on current policies in Canada and other countries as of Fall 2011. It serves as a benchmark for discussion and scenario analysis. The outlook makes specific assumptions and outlines their implications. Since it assumes that policies remain unchanged in the future it is therefore an extrapolation of what could occur based on current trends and underlying macroeconomic projections. In particular, there are no assumptions made regarding the outcome of the Doha round of trade negotiations. It also assumes no impact from climate change and from policy to mitigate climate change nor significant animal disease outbreaks or unusual climatic conditions over the period of the outlook. The starting point of the MTO is world agricultural commodities price projection based on the OECD/FAO Agricultural Outlook for 2009/2019 adjusted with more recent information. The Canadian macro-economic forecasts are from the Conference Board of Canada outlook published in September 2011 In addition, short-term price forecasts have been updated using United States Department of Agriculture (USDA) projections released in November 2011. |
| Keywords: | Outlook, Agriculture, Cereals, Oilseeds, Bio-fuels, Livestock, Red meats, Milk, Dairy products, Chicken, Turkey, Eggs, Agribusiness, Agricultural and Food Policy, Agricultural Finance, Financial Economics, |
| Date: | 2012–02 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaacem:126214&r=for |