nep-for New Economics Papers
on Forecasting
Issue of 2007‒03‒17
seven papers chosen by
Rob J Hyndman
Monash University

  1. Predicting the Term Structure of Interest Rates: Incorporating parameter uncertainty, model uncertainty and macroeconomic information By Michiel D. de Pooter; Francesco Ravazzolo; Dick van Dijk
  2. Financial Expectations, Consumption and Saving: A Microeconomic Analysis. By Sarah Brown; Karl Taylor
  3. The Taylor rule and interest rate uncertainty in the U.S. 1955-2006 By Mandler, Martin
  4. Accurate Value-at-Risk Forecast with the (good old) Normal-GARCH Model By Christoph Hartz; Stefan Mittnik; Marc S. Paolella
  5. An Introduction to World Economic Long Wave-Crises and Depressions: From Study to Anticipation By dong, congcong
  6. Option Pricing under Stochastic Volatility and Trading Volume By Sadayuki Ono
  7. Previsão da eficácia ofensiva do futebol profissional: Um caso Português By Caiado, Jorge; Vieira, Aníbal; Bonito, Ana; Reis, Carlos; Fernandes, Francisco

  1. By: Michiel D. de Pooter (Erasmus Universiteit Rotterdam); Francesco Ravazzolo (Erasmus Universiteit Rotterdam); Dick van Dijk (Erasmus Universiteit Rotterdam)
    Abstract: We forecast the term structure of U.S. Treasury zero-coupon bond yields by analyzing a range of models that have been used in the literature. We assess the relevance of parameter uncertainty by examining the added value of using Bayesian inference compared to frequentist estimation techniques, and model uncertainty by combining forecasts from individual models. Following current literature we also investigate the benefits of incorporating macroeconomic information in yield curve models. Our results show that adding macroeconomic factors is very beneficial for improving the out-of-sample forecasting performance of individual models. Despite this, the predictive accuracy of models varies over time considerably, irrespective of using the Bayesian or frequentist approach. We show that mitigating model uncertainty by combining forecasts leads to substantial gains in forecasting performance, especially when applying Bayesian model averaging.
    Keywords: Term structure of interest rates; Nelson-Siegel model; Affine term structure model; forecast combination; Bayesian analysis
    JEL: C5 C11 C32 E43 E47 F47
    Date: 2007–03–09
  2. By: Sarah Brown; Karl Taylor (Department of Economics, The University of Sheffield)
    Abstract: We explore the determinants of individuals´ financial expectations using data from the British Household Panel Survey (BHPS) 1991-2001. Our findings suggest that individuals´ financial predictions are influenced by both the life cycle and the business cycle. We also investigate the extent to which the accuracy of past financial expectations affects current financial expectations. Interestingly, only past financial optimism matters, regardless of the accuracy of the prediction. We also explore the relationship between financial realisations and expectations and we find that expectations tend to fall short of financial realisations. Finally, we investigate the relationship between financial expectations, savings and consumption. Our findings suggest that financial optimism is inversely associated with savings and that current financial expectations serve to predict future consumption.
    Keywords: Consumption, Financial Expectations, Financial Realisations, Forecasting Accuracy, Savings.
    JEL: D10 D84 E32
    Date: 2006–05
  3. By: Mandler, Martin
    Abstract: We use a Taylor rule with time-varying policy coefficients in combination with an unobserved components model for the output gap to estimate the uncertainty about future values of the Federal Funds Rate. The model makes it possible to separate ex-ante interest rate uncertainty into three components: 1) uncertainty about the Fed's future policy coefficients, 2) uncertainty about future economic fundamentals, and 3) residual uncertainty. The results show important changes in uncertainty about future short-term interest rates over time with peaks in the late 1960s/early 1970s, mid 1970s and late 1970s/early 1980s. While for one-quarter forecasts uncertainty about the Fed's policy reaction is more important than uncertainty about economic fundamentals this result is reversed for the two-quarter forecast horizon. Results from a modified model with regime shifts in the variance of the policy shocks confirm the previous findings but show changes in residual uncertainty to be important as well.
    Keywords: monetary policy rules; interest rate uncertainty; Kalman filter
    JEL: C53 C32 E52
    Date: 2007–03
  4. By: Christoph Hartz (University of Munich); Stefan Mittnik (University of Munich, Center for Financial Studies and ifo); Marc S. Paolella (University of Zurich)
    Abstract: A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.
    Keywords: Bootstrap, GARCH, Value-at-Risk
    JEL: C22 C53 C63 G12
    Date: 2006–11–03
  5. By: dong, congcong
    Abstract: As is considered in this paper,none of the ever existing long wave theories can totally describe or correctly explain the chronic fluctuating characters of the capitalist world economy system since the year 1857. Based on Karl Marx’s greatest work “Capital” and combined with considerable quantities of historical materials such as all kinds of writings about economic long wave both at home and abroad,the paper analyzes four inherently identical waves,tries to draw a fluctuating graph of the world economy with the wavelength supposed to be 50 years,and then forecasts the future of the world.
    Keywords: economic crisis; long wave; forecasting
    JEL: E37 E32 E17 E11
    Date: 2006–02–27
  6. By: Sadayuki Ono
    Abstract: This paper presents a pricing formula for European options derived from a model in which changes in the underlying price and trading volumes are jointly determined by exogenous events. This specification makes increments to the volatility depend on the current level of volatility and news and thereby accounts for the observed persistence in volatility. Moreover, it makes volatility an observable variable. The model accounts well for time varying volatility smiles and term structures, and that out-of-sample price forecasts for a sample of call options are superior to the benchmark ad hoc procedure of plugging implicit volatilities into the Black-Scholes formula.
    Keywords: Option valuation, trading volume, the stochastic volatility and volume (SVV) model
    JEL: G12 C52 C53
    Date: 2007–03
  7. By: Caiado, Jorge; Vieira, Aníbal; Bonito, Ana; Reis, Carlos; Fernandes, Francisco
    Abstract: The forecast plays an important role in the planning, the decision-making and control in any domain of activity, including the sportive phenomenon of the soccer. The experience has shown that the extrapolative or not casual models (univariate models), that use only the information of its past values to forecast the future, can often predict future with more accuracy than causal or multivariate models. In this paper, we model and forecast the offensive effectiveness of the soccer team Sport Lisbon and Benfica, in Portuguese soccer league, by using deterministic methods (linear trend, moving average, exponential smoothing, holt, naïve) and stochastic models (ARMA models, random walk). The model selection criteria used in our study were the mean squared error, the mean absolute error and the mean absolute percentage error based in a one-step forecast of the last three observations.
    Keywords: Exponential smoothing; Soccer; Moving average; ARMA model; Forecast.; Exponential smoothing, soccer, moving average, ARMA model, forecast.
    JEL: C53 L83
    Date: 2006

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