nep-for New Economics Papers
on Forecasting
Issue of 2012‒02‒20
thirteen papers chosen by
Rob J Hyndman
Monash University

  1. Forecasting multivariate volatility in larger dimensions: some practical issues By Adam E Clements; Ayesha Scott; Annastiina Silvennoinen
  2. Forecasting economic activity with higher frequency targeted predictors By Guido Bulligan; Massimiliano Marcellino; Fabrizio Venditti
  3. Real-Time Analysis of Oil Price Risks Using Forecast Scenarios By Christiane Baumeister; Lutz Kilian
  4. Testing the Rational Expectations Hypothesis on the Retail Trade Sector Using Survey Data from Malaysia By Puah, Chin-Hong; Chong, Lucy Lee-Yun; Jais, Mohamad
  5. Fertility forecasting: using Bayesian methods to extrapolate trends while preserving cohort features By Carl Schmertmann; Joshua R. Goldstein; Mikko Myrskylä; Emilio Zagheni
  6. Forecasting malaysian business cycle movement: empirical evidence from composite leading indicator By Wong, Shirly Siew-Ling; Abu Mansor, Shazali; Puah, Chin-Hong; Liew, Venus Khim-Sen
  7. Time-varying conditional Johnson SU density in value-at-risk (VaR) methodology By Cayton, Peter Julian A.; Mapa, Dennis S.
  8. Evaluating the calibration of multi-step-ahead density forecasts using raw moments By Knüppel, Malte
  9. The interdependences of central bank’s forecasts and economic agents inflation expectations.Empirical study By Magdalena Szyszko
  10. Volatility timing and portfolio selection: How best to forecast volatility By Adam E Clements; Annastiina Silvennoinen
  11. Identifying News Shocks with Forecast Data By Yasuo Hirose; Takushi Kurozumi
  12. Official forecasts and management of oil windfalls By Torfinn Harding and Frederick van der Ploeg
  13. Identifying speculative bubbles with an in finite hidden Markov model By Song, Yong; Shi, Shuping

  1. By: Adam E Clements (QUT); Ayesha Scott (QUT); Annastiina Silvennoinen (QUT)
    Abstract: The importance of covariance modelling has long been recognised in the field of portfolio management and large dimensional multivariate problems are increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating whether simpler moving average based correlation forecasting methods have equal predictive accuracy as their more complex multivariate GARCH counterparts for large dimensional problems. We find simpler forecasting techniques do provide equal (and often superior) predictive accuracy in a minimum variance sense. A portfolio allocation problem is used to compare forecasting methods. The global minimum variance portfolio and Model Confidence Set (Hansen, Lunde, and Nason (2003)) are used to compare methods, whilst portfolio weight stability and computational time are also considered.
    Keywords: Volatility, multivariate GARCH, portfolio allocation
    JEL: C22 G11 G17
    Date: 2012–02–06
  2. By: Guido Bulligan (Bank of Italy); Massimiliano Marcellino (European University Institute, Bocconi University); Fabrizio Venditti (Bank of Italy)
    Abstract: In this paper we explore the performance of bridge and factor models in forecasting quarterly aggregates in the very short-term subject to a pre-selection of monthly indicators. Starting from a large information set, we select a subset of targeted predictors using data reduction techniques as in Bai and Ng (2008). We then compare a Diffusion Index forecasting model as in Stock and Watson (2002), with a Bridge model specified with an automated General-To-Specific routine. We apply these techniques to forecasting Italian GDP growth and its main components from the demand side and find that Bridge models outperform naive forecasts and compare favorably against factor models. Results for France, Germany, Spain and the euro area confirm these findings.
    Keywords: short-term GDP forecast, factor models, bridge models, General To Specific
    JEL: C52 C53 E37
    Date: 2012–01
  3. By: Christiane Baumeister; Lutz Kilian
    Abstract: Recently, there has been increased interest in real-time forecasts of the real price of crude oil. Standard oil price forecasts based on reduced-form regressions or based on oil futures prices do not allow consumers of forecasts to explore how much the forecast would change relative to the baseline forecast under alternative scenarios about future oil demand and oil supply conditions. Such scenario analysis is of central importance for end-users of oil price forecasts interested in evaluating the risks underlying these forecasts. We show how policy-relevant forecast scenarios can be constructed from recently proposed structural vector autoregressive models of the global oil market and how changes in the probability weights attached to these scenarios affect the upside and downside risks embodied in the baseline real-time oil price forecast. Such risk analysis helps forecast users understand what assumptions are driving the forecast. An application to real-time data for December 2010 illustrates the use of these tools in conjunction with reduced-form vector autoregressive forecasts of the real price of oil, the superior realtime forecast accuracy of which has recently been established.
    Keywords: Econometric and statistical methods; International topics
    JEL: Q43 C53 E32
    Date: 2012
  4. By: Puah, Chin-Hong; Chong, Lucy Lee-Yun; Jais, Mohamad
    Abstract: The rational expectations hypothesis states that when people are expecting things to happen, using the available information, the predicted outcomes usually occur. This study utilized survey data provided by the Business Expectations Survey of Limited Companies to test whether forecasts of the Malaysian retail sector, based on gross revenue and capital expenditures, are rational. The empirical evidence illustrates that the decision-makers expectations in the retail sector are biased and too optimistic in forecasting gross revenue and capital expenditures.
    Keywords: REH; Unbiasedness; Non-serial Correlation; Weak-form Efficiency
    JEL: D84 L81 C12 C22
    Date: 2011–10
  5. By: Carl Schmertmann (Max Planck Institute for Demographic Research, Rostock, Germany); Joshua R. Goldstein (Max Planck Institute for Demographic Research, Rostock, Germany); Mikko Myrskylä (Max Planck Institute for Demographic Research, Rostock, Germany); Emilio Zagheni (Max Planck Institute for Demographic Research, Rostock, Germany)
    Abstract: There are already several documented examples of recent increases in cohort fertility in Scandinavia, but for most countries, cohorts are too young to see if cohort fertility has increased. We produce new estimates of completed cohort fertility for cohorts born in the 1970s. We combine the best of previous efforts, using cohort forecasting methods to preserve what demographers know about the age-pattern of fertility, and using trends in the age-period-cohort Lexis surface to tell us as much as possible about the way in which fertility appears to be changing over time. Our preliminary findings suggest that cohort fertility has stopped its long-term secular decline in the majority of low fertility countries around the world. In some cases, there is a clear suggestion of increase. As we further develop our models we expect to be able to make more precise statements about further trends and the certainty of our knowledge.
    Keywords: fertility
    JEL: J1 Z0
    Date: 2012–01
  6. By: Wong, Shirly Siew-Ling; Abu Mansor, Shazali; Puah, Chin-Hong; Liew, Venus Khim-Sen
    Abstract: Early detection of a turning point in a business cycle is crucial, as information about the changing phases in business cycles enables policy makers, the business community, and investors to cope better with unexpected events brought about by economic and business situations. The Malaysian economy is fortunate to own a publicly accessible composite of leading indicator (CLI) that is presumed capable of tracing the business cycle movement and thus contributes to the creation of an early signaling tool for short-term economic forecasting. Certainly, the usefulness of this CLI in monitoring the contemporary economic and business condition in Malaysia will be empirically appealing to the nation. Even though the present study can display the ability of the Malaysian CLI to trace the business cycle and offers advanced detection of business cycle turning points, the evidence of diminishing lead times foreseen by the CLI significantly weaken the fundamental function of a leading index as an early tool to signal economic vulnerability.
    Keywords: Business Cycle; Composite Leading Indicator; Early Signaling Tool
    JEL: E32 E17
    Date: 2012–02
  7. By: Cayton, Peter Julian A.; Mapa, Dennis S.
    Abstract: Stylized facts on financial time series data are the volatility of returns that follow non-normal conditions such as leverage effects and heavier tails leading returns to have heavier magnitudes of extreme losses. Value-at-risk is a standard method of forecasting possible future losses in investments. A procedure of estimating value-at-risk using time-varying conditional Johnson SU¬ distribution is introduced and assessed with econometric models. The Johnson distribution offers the ability to model higher parameters with time-varying structure using maximum likelihood estimation techniques. Two procedures of modeling with the Johnson distribution are introduced: joint estimation of the volatility and two-step procedure where estimation of the volatility is separate from the estimation of higher parameters. The procedures were demonstrated on Philippine-foreign exchange rates and the Philippine stock exchange index. They were assessed with forecast evaluation measures with comparison to different value-at-risk methodologies. The research opens up modeling procedures where manipulation of higher parameters can be integrated in the value-at-risk methodology.
    Keywords: Time Varying Parameters; GARCH models; Nonnormal distributions; Risk Management
    JEL: G12 C53 G32 C22
    Date: 2012–01
  8. By: Knüppel, Malte
    Abstract: The evaluation of multi-step-ahead density forecasts is complicated by the serial correlation of the corresponding probability integral transforms. In the literature, three testing approaches can be found which take this problem into account. However, these approaches can be computationally burdensome, ignore important information and therefore lack power, or suffer from size distortions even asymptotically. In this work, a fourth testing approach based on raw moments is proposed. It is easy to implement, uses standard critical values, can include all moments regarded as important, and has correct asymptotic size. It is found to have good size and power properties if it is based directly on the (standardized) probability integral transforms. --
    Keywords: density forecast evaluation,normality tests
    JEL: C12 C52 C53
    Date: 2011
  9. By: Magdalena Szyszko (Wyższa Szkoła Bankowa w Poznaniu, Katedra Bankowości i Rynku Finansowego)
    Abstract: This paper focuses on the associations between the inflation forecasts of the central bank and inflation expectations of the households. The first part is of a descriptive nature. It gives the theoretical background of modern monetary policy focusing on the role of expectations. It also presents the idea of inflation forecast targeting. Then the framework of the inflation forecast targeting in four countries: the Czech Republic, Hungary, Poland and Romania is presented. The empirical part of the study is an attempt to find associations between the inflation forecasts results and inflation expectations of consumers derived on the basis of surveys. The theory gives sound background for the existence of such relationships.The interdependences are tested in several ways. The last part of the paper focuses on the results and conclusions.
    Keywords: inflation forecasts, inflation forecasts targeting, inflation expectations
    JEL: E52 E58
    Date: 2011
  10. By: Adam E Clements (QUT); Annastiina Silvennoinen (QUT)
    Abstract: Within the context of volatility timing and portfolio selection this paper considers how best to estimate a volatility model. Two issues are dealt with, namely the frequency of data used to construct volatility estimates, and the loss function used to estimate the parameters of a volatility model. We find support for the use of intraday data for estimating volatility which is consistent with earlier research. We also find that the choice of loss function is important and show that a simple mean squared error loss, overall provides the best forecasts of volatility upon which to form optimal portfolios.
    Keywords: Volatility, volatility timing, utility, portfolio allocation, realized volatility
    JEL: C22 G11 G17
    Date: 2011–10–12
  11. By: Yasuo Hirose; Takushi Kurozumi
    Abstract: Recent studies attempt to quantify the empirical importance of news shocks (ie., anticipated future schocks) in business cycle fluctuations. This paper identifies news schocks in a dynamic stochastic general equilibrium model estimated with not only actual data but also forecast data. The estimation results show new empirical evidence that antecipated future technology shocks are the most important driving force of U.S. business cycles. The use of the forecast data makes the anticipated shocks play a much more important role in fitting model-implied expectations to this data, since such shocks have persistent effects on the expectaions and thereby help to replicate the observed persistence of the forecasts.
    JEL: E30 E32
    Date: 2012–02
  12. By: Torfinn Harding and Frederick van der Ploeg (Statistics Norway)
    Abstract: Official forecasts for oil revenues and the burden of pensioners are used to estimate forward-looking fiscal policy rules for Norway and compared with permanent-income and bird-in-hand rules. The results suggest that fiscal reactions have been partial forward-looking with respect to the rising pension bill, but backward-looking with respect to oil and gas revenues. Solvency of the government finances might be an issue with the fiscal rules estimated from historical data. Simulation suggests that declining oil and gas revenue and the costs of a rapidly graying population will substantially deteriorate the net government asset position by 2060 unless fiscal policy becomes more prudent or current pension and fiscal reforms are successful.
    Keywords: oil windfalls; official forecasts; forward-looking fiscal policy rules; permanent income hypothesis; graying population; debt sustainability
    JEL: H20 H63 Q33
    Date: 2012–01
  13. By: Song, Yong; Shi, Shuping
    Abstract: This paper proposes an infinite hidden Markov model (iHMM) to detect, date stamp,and estimate speculative bubbles. Three features make this new approach attractive to practitioners. First, the iHMM is capable of capturing the nonlinear dynamics of different types of bubble behaviors as it allows an infinite number of regimes. Second, the implementation of this procedure is straightforward as the detection, dating, and estimation of bubbles are done simultaneously in a coherent Bayesian framework. Third, the iHMM, by assuming hierarchical structures, is parsimonious and superior in out-of-sample forecast. Two empirical applications are presented: one to the Argentinian money base, exchange rate, and consumer price from January 1983 to November 1989; and the other to the U.S. oil price from April 1983 to December 2010. We find prominent results, which have not been discovered by the existing finite hidden Markov model. Model comparison shows that the iHMM is strongly supported by the predictive likelihood.
    Keywords: speculative bubbles; in nite hidden Markov model; Dirichlet process
    JEL: C14 C15 C11
    Date: 2012–02–06

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