nep-for New Economics Papers
on Forecasting
Issue of 2011‒08‒02
fourteen papers chosen by
Rob J Hyndman
Monash University

  1. Forecasting the price of oil By Ron Alquist; Lutz Kilian; Robert J. Vigfusson
  2. Forecasting inflation with gradual regime shifts and exogenous information By Andrés González; Kirstin Hubrich; Timo Teräsvirta
  3. International organisations’ vs. private analysts’ forecasts: an evaluation By Ildeberta Abreu
  4. GFC-Robust Risk Management Under the Basel Accord Using Extreme Value Methodologies By Paulo Araújo Santos; Juan-Ángel Jiménez-Martín; Michael McAleer; Teodosio Pérez Amaral
  5. Asset Returns Under Model Uncertainty: Evidence from the euro area, the U.K. and the U.S. By João Sousa; Ricardo M. Sousa
  6. Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures By Roberto Casarin; Chia-Lin Chang; Juan-Ángel Jiménez-Martín; Michael McAleer; Teodosio Pérez Amaral
  7. Banking relationships and sell-side research By Ozgur E. Ergungor; Leonardo Madureira; Nandkumar Nayar; Ajai K. Singh
  8. Progress in Medicine, Limits to Life and Forecasting Mortality By Carlo Favero; Marco Giacoletti
  9. Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions By Athanasopoulos, George; Guillén, Osmani Teixeira de Carvalho; Issler, João Victor; Vahid, Farshid
  10. Value at Risk forecasting with the ARMA-GARCH family of models in times of increased volatility By Milan Rippel; Ivo Jánský
  11. An Early Warning System to Predict the House Price Bubbles By Christian Dreger; Konstantin A. Kholodilin
  12. Forecasting world and regional aviation Jet-Fuel demands to the mid term (2025). By Chevallier, Julien; Chèze, Benoît; Gastineau, Pascal
  13. The "CAPS" Prediction System and Stock Market Returns By Avery, Christopher; Chevalier, Judith; Zeckhauser, Richard J.
  14. Over-optimism in Forecasts by Official Budget Agencies and Its Implications By Jeffrey A. Frankel

  1. By: Ron Alquist; Lutz Kilian; Robert J. Vigfusson
    Abstract: We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need to know about the choice of sample period and about the tradeoffs between alternative oil price series and model specifications? Are real or nominal oil prices predictable based on macroeconomic aggregates? Does this predictability translate into gains in out-of-sample forecast accuracy compared with conventional no-change forecasts? How useful are oil futures markets in forecasting the price of oil? How useful are survey forecasts? How does one evaluate the sensitivity of a baseline oil price forecast to alternative assumptions about future demand and supply conditions? How does one quantify risks associated with oil price forecasts? Can joint forecasts of the price of oil and of U.S. real GDP growth be improved upon by allowing for asymmetries?
    Date: 2011
  2. By: Andrés González (Banco de la República, Bogotá, Colombia.); Kirstin Hubrich (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Timo Teräsvirta (CREATES, Aarhus University, Denmark.)
    Abstract: We propose a new method for medium-term forecasting using exogenous information. We first show how a shifting-mean autoregressive model can be used to describe characteristic features in inflation series. This implies that we decompose the inflation process into a slowly moving nonstationary component and dynamic short-run fluctuations around it. An important feature of our model is that it provides a way of combining the information in the sample and exogenous information about the quantity to be forecast. This makes it possible to form a single model-based inflation forecast that also incorporates the exogenous information. We demonstrate, both theoretically and by simulations, how this is done by using the penalised likelihood for estimating the model parameters. In forecasting inflation, the central bank inflation target, if it exists, is a natural example of such exogenous information. We illustrate the application of our method by an out-of-sample forecasting experiment for euro area and UK inflation. We find that for euro area inflation taking the exogenous information into account improves the forecasting accuracy compared to that of a number of relevant benchmark models but this is not so for the UK. Explanations to these outcomes are discussed. JEL Classification: C22, C52, C53, E31, E47.
    Keywords: Nonlinear forecast, nonlinear model, nonlinear trend, penalised likelihood, structural shift, time-varying parameter.
    Date: 2011–07
  3. By: Ildeberta Abreu
    Abstract: This paper evaluates the performance of the macroeconomic forecasts disclosed by three leading international organisations - the IMF, the European Commission and the OECD - and compares it with that of the mean forecasts of two surveys of private analysts - the Consensus Economics and The Economist. The publication of forecasts twice a year by international organisations always receives a great deal of public attention but the timely forecasts disclosed monthly by private institutions have been gaining increased visibility. The aim of this work is to help forecast users in answering the question of how much (little) confidence they should place in the alternative forecasts that are available at each moment. The evaluation covers real GDP growth and inflation projections for nine main advanced economies, over the period 1991-2009. Several evaluation criteria are used. The quantitative accuracy of forecasts is assessed and their unbiasedness and efficiency is tested. The directional accuracy of forecasts and the ability to predict economic recessions are also examined. The results suggest that the forecasting performance of the international organisations is broadly similar to that of the surveys of private analysts. By and large, current-year forecasts present desirable features and clearly outperform year-ahead forecasts for which evidence is more mixed both in terms of quantitative and qualitative accuracy.
    JEL: E37
    Date: 2011
  4. By: Paulo Araújo Santos; Juan-Ángel Jiménez-Martín; Michael McAleer (University of Canterbury); Teodosio Pérez Amaral
    Abstract: In McAleer et al. (2010b), a robust risk management strategy to the Global Financial Crisis (GFC) was proposed under the Basel II Accord by selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models. The robust forecast was based on the median of the point VaR forecasts of a set of conditional volatility models. In this paper we provide further evidence on the suitability of the median as a GFC-robust strategy by using an additional set of new extreme value forecasting models and by extending the sample period for comparison. These extreme value models include DPOT and Conditional EVT. Such models might be expected to be useful in explaining financial data, especially in the presence of extreme shocks that arise during a GFC. Our empirical results confirm that the median remains GFC-robust even in the presence of these new extreme value models. This is illustrated by using the S&P500 index before, during and after the 2008-09 GFC. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria, including several tests for independence of the violations. The strategy based on the median, or more generally, on combined forecasts of single models, is straightforward to incorporate into existing computer software packages that are used by banks and other financial institutions.
    Keywords: Value-at-Risk (VaR); DPOT; daily capital charges; robust forecasts; violation penalties; optimizing strategy; aggressive risk management; conservative risk management; Basel; global financial crisis
    JEL: G32 G11 C53 C22
    Date: 2011–07–01
  5. By: João Sousa; Ricardo M. Sousa
    Abstract: The goal of this paper is to analyze predictability of future asset returns in the context of modeluncertainty. Using data for the Euro Area, the US and the U.K., we show that one can improve the forecasts of stock returns using a Bayesian Model Averaging (BMA) approach, and there is a large amount of model uncertainty.<br>The empirical evidence for the Euro Area suggests that several macroeconomic, financial and macro-financial variables are consistently among the most prominent determinants of risk premium.As for the US, only a few number of predictors play an important role. In the case UK, future stock returns are better forecasted by financial variables. These results are corroborated for both the M-open and the M-closed perspectives and in the context of "in-sample" and out-of-sample" forecasting. Finally, we highlight that the predictive ability of the BMA framework is stronger at longer periods, and clearly outperforms the constant expected returns and the autoregressive benchmark models.
    JEL: E21 G11 E44
    Date: 2011
  6. By: Roberto Casarin; Chia-Lin Chang; Juan-Ángel Jiménez-Martín; Michael McAleer (University of Canterbury); Teodosio Pérez Amaral
    Abstract: It is well known that the Basel II Accord requires banks and other Authorized Deposit-taking Institutions (ADIs) to communicate their daily risk forecasts to the appropriate monetary authorities at the beginning of each trading day, using one or more risk models, whether individually or as combinations, to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and associated capital costs of ADIs, depending in part on the number of previous violations, whereby realised losses exceed the estimated VaR. McAleer et al. (2009) proposed a new approach to model selection for predicting VaR, consisting of combining alternative risk models, and comparing conservative and aggressive strategies for choosing between VaR models. This paper addresses the question of risk management of risk, namely VaR of VIX futures prices, and extends the approaches given in McAleer et al. (2009) and Chang et al. (2011) to examine how different risk management strategies performed during the 2008-09 global financial crisis (GFC). The empirical results suggest that an aggressive strategy of choosing the Supremum of single model forecasts, as compared with Bayesian and non-Bayesian combinations of models, is preferred to other alternatives, and is robust during the GFC. However, this strategy implies relatively high numbers of violations and accumulated losses, which are admissible under the Basel II Accord.
    Keywords: Median strategy; Value-at-Risk; daily capital charges; violation penalties; aggressive risk management; conservative risk management; Basel Accord; VIX futures; Bayesian strategy; quantiles; forecast densities
    JEL: G32 C53 C22 C11
    Date: 2011–07–01
  7. By: Ozgur E. Ergungor; Leonardo Madureira; Nandkumar Nayar; Ajai K. Singh
    Abstract: This paper examines disclosures by sell-side analysts when their institution has a lending relationship with the firms being covered. Lending-affiliated analysts’ earnings forecasts are found to be more accurate relative to forecasts by other analysts but this differential accuracy manifests itself only after the advent of the loan. Despite this increased earnings forecast accuracy, lending-affiliated analysts exhibit undue optimism in their brokerage recommendations and forecasts of long term growth. The optimism exists both before and after the lending commences. The evidence suggests that any insights into the covered firm via thelending relationship are employed by bank analysts in a selective manner. They appear unwilling to compromise on disclosures where expost accuracy is clearly revealed, possibly to preserve their own personal reputation. However, they are overly optimistic on other disclosures where resolution is less readily verifiable, possibly to promote their lending client’s financial standing.
    Keywords: Forecasting ; Investment banking
    Date: 2011
  8. By: Carlo Favero; Marco Giacoletti
    Abstract: In this paper we propose a model to forecast future mortality that includes information on the limits to life and on progress in medicine. We apply the model to forecasting future mortality and survival rates for the males population in England andWales. Our proposal extends the benchmark stochastic mortality model along two dimensions. First, we try and deal explicitly with tail risk in the cross-sectional estimation. by including information about the "limit to life" in the sample used to construct factors for the cross-sectional dimension of mortality rates. Second, we propose to substitute the usual stochastic trend model adopted for the time series of risk factors with a predictive framework based on available evidence on medical progress and causes of death. The model projects very little variability for limits to life over the next ten years and predicts that in 2020 the probability that an individual age 65 will survive until 85 is 20% with an upper bound of 23% and a lower bound of 17%.
    Date: 2011
  9. By: Athanasopoulos, George; Guillén, Osmani Teixeira de Carvalho; Issler, João Victor; Vahid, Farshid
    Abstract: We study the joint determination of the lag length, the dimension of the cointegrating space andthe rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using modelselection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditionalcriteria and criteria with data-dependant penalties and we prove its consistency. A MonteCarlo study explores the finite sample performance of this procedure and evaluates the forecastingaccuracy of models selected by this procedure. Two empirical applications confirm the usefulnessof the model selection procedure proposed here for forecasting.
    Date: 2011–01–27
  10. By: Milan Rippel (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic); Ivo Jánský (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic)
    Abstract: The paper evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices - DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model mean using the ARMA processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are estimated on the data from the in-sample period and their forecasting accuracy is evaluated on the out-of-sample data, which are more volatile. The main aim of the paper is to test whether a model estimated on data with lower volatility can be used in periods with higher volatility. The evaluation is based on the conditional coverage test and is performed on each stock index separately. The primary result of the paper is that the volatility is best modelled using a GARCH process and that an ARMA process pattern cannot be found in analyzed time series.
    Keywords: VaR, risk analysis, conditional volatility, conditional coverage, garch, egarch, tarch, moving average process, autoregressive process
    JEL: C51 C52 C53 G24
    Date: 2011–07
  11. By: Christian Dreger; Konstantin A. Kholodilin
    Abstract: In this paper, we construct the country-specific chronologies of the house price bubbles for 12 OECD countries over the period 1969:Q1- 2010:Q2. These chronologies are obtained using a combination of a fundamental and a filter approaches. The resulting speculative bubble chronology is the one that provides the highest concordance between these two techniques. In addition, we suggest an early warning system based on three alternative approaches: signalling approach, logit and probit models. It is shown that the latter two models allow much more accurate predictions of the house price bubbles than the signalling approach. The prediction accuracy of the logit and probit models is high enough to make them useful in forecasting the future speculative bubbles in housing market. Thus, our method can be used by the policymakers in their attempts to timely detect the house price bubbles and attenuate their devastating effects on the domestic and world economy.
    Keywords: House prices, early warning system, OECD countries
    JEL: C25 C33 E32 E37
    Date: 2011
  12. By: Chevallier, Julien; Chèze, Benoît; Gastineau, Pascal
    Abstract: This article provides jet fuel demand projections at the worldwide level and for eight geographical zones until 2025. Air traffic forecasts are performed using dynamic panel-data econometrics. Then, the conversion of air traffic projections into quantities of jet fuel is accomplished by using a complementary approach to the ‘Traffic Efficiency’ method developed previously by the UK Department of Trade and Industry to support the Intergovernmental Panel on Climate Change (IPCC, 1999). According to our main scenario, air traffic should increase by about 100% between 2008 and 2025 at the world level, corresponding to a yearly average growth rate of 4.7%. World jet fuel demand is expected to increase by about 38% during the same period, corresponding to a yearly average growth rate of 1.9% per year. According to these results, energy efficiency improvements allow reducing the effect of air traffic rise on the increase in jet fuel demand, but do not annihilate it. Jet fuel demand is thus unlikely to diminish unless there is a radical technological shift, or air travel demand is restricted.
    Keywords: Energy efficiency; Jet fuel demand forecasts; Macro-level methodology;
    JEL: Q48 L93 C23
    Date: 2011
  13. By: Avery, Christopher (Harvard University); Chevalier, Judith (Yale University); Zeckhauser, Richard J. (Harvard University)
    Abstract: We study the predictive power of approximately 2.5 million stock picks submitted by individual users to the "CAPS" website run by the Motley Fool company ( These picks prove to be surprisingly informative about future stock prices. Indeed, a strategy of shorting stocks with a disproportionate number of negative picks on the site and buying stocks with a disproportionate number of positive picks produces a return of over nine percent per annum over the sample period. These results are mostly driven by the fact that negative picks on the site strongly predict future stock price declines; positive picks on the site produce returns that are statistically indistinguishable from the market. A Fama French decomposition suggests that these results are largely due to stock-picking rather than style factors or market timing.
    Date: 2011–07
  14. By: Jeffrey A. Frankel
    Abstract: The paper studies forecasts of real growth rates and budget balances made by official government agencies among 33 countries. In general, the forecasts are found: (i) to have a positive average bias, (ii) to be more biased in booms, (iii) to be even more biased at the 3-year horizon than at shorter horizons. This over-optimism in official forecasts can help explain excessive budget deficits, especially the failure to run surpluses during periods of high output: if a boom is forecasted to last indefinitely, retrenchment is treated as unnecessary. Many believe that better fiscal policy can be obtained by means of rules such as ceilings for the deficit or, better yet, the structural deficit. But we also find: (iv) countries subject to a budget rule, in the form of euroland’s Stability and Growth Path, make official forecasts of growth and budget deficits that are even more biased and more correlated with booms than do other countries. This effect may help explain frequent violations of the SGP. One country, Chile, has managed to overcome governments’ tendency to satisfy fiscal targets by wishful thinking rather than by action. As a result of budget institutions created in 2000, Chile’s official forecasts of growth and the budget have not been overly optimistic, even in booms. Unlike many countries in the North, Chile took advantage of the 2002-07 expansion to run budget surpluses, and so was able to ease in the 2008-09 recession.
    JEL: E62 H50
    Date: 2011–07

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