nep-for New Economics Papers
on Forecasting
Issue of 2013‒04‒20
eighteen papers chosen by
Rob J Hyndman
Monash University

  1. Money demand and the role of monetary indicators in forecasting euro area inflation By Christian Dreger; Jürgen Wolters
  2. Are business tendency surveys useful to forecast private investment in Peru? A non-linear approach By Arenas, Paúl; Morales, Daniel
  3. Incorporating theoretical restrictions into forecasting by projection methods By Raffaella Giacomini
  4. Forecasting financial market activity using a semiparametric fractionally integrated Log-ACD By Yuanhua Feng; Chen Zhou
  5. Spatial Chow-Lin Models for Completing Growth Rates in Cross-sections By Wolfgang Polasek
  6. Announcements of interest rate forecasts: Do policymakers stick to them? By Nikola Mirkov; Gisle James Natvik
  7. The Consumer confidence index and short-term private consumption forecasting in Peru By Cuenca, Leonidas; Flores, Julio; Morales, Daniel
  8. Nowcasting with Daily Data By Michele Modugno; Lucrezia Reichlin; Domenico Giannone; Marta Banbura
  9. Asymmetric forecasting and commitment policy in a robust control problem By Taro Ikeda
  10. Estimating investors' behavior and errorsin probabilistic forecasts by the Kolmogorov entropy and noise colors of multifractal attractors By Dominique, C-Rene
  11. Double Whammy - How ICT Projects are Fooled by Randomness and Screwed by Political Intent By Alexander Budzier; Bent Flyvbjerg
  12. Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox By Roberto Casarin; Stefano Grassi; Francesco Ravazzolo; Herman K. van Dijk
  13. Aggregation of information and beliefs on prediction markets with non-bayesian traders By Matthieu Segol
  14. "Realized Stochastic Volatility with Leverage and Long Memory" By Shinichiro Shirota; Takayuki Hizu; Yasuhiro Omori
  15. Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold By Mensi, Walid; Beljid, Makram; Boubaker, Adel; Managi, Shunsuke
  16. Wage Rigidity: A Solution to Several Asset Pricing Puzzles By Jack Favilukis; Xiaoji Lin
  17. Projections of dynamic generational tables and longevity risk in Chile By Javier Alonso; David Tuesta; Diego Torres; Begona Villamide
  18. The projection of sales revenue for selected company in sector 56 - food and beverage service activities---Planowanie przychodów ze sprzedaży na przykładzie przedsiębiorstwa z branży 56 - działalność usługowa związana z wyżywieniem By Rafal Koziarski

  1. By: Christian Dreger; Jürgen Wolters
    Abstract: This paper examines the stability of money demand and the forecasting performance of a broad monetary aggregate (M3) in predicting euro area inflation. Excess liquidity is measured as the difference between the actual money stock and its fundamental value, the latter determined by a money demand function. The out-of sample forecasting performance is compared to widely used alternatives, such as the term structure of interest rates. The results indicate that the evolution of M3 is still in line with money demand even in the period of the financial and economic crisis. Monetary indi-cators are useful to predict inflation, if the forecasting equations are based on measures of excess liquidity.
    Keywords: Money demand, excess liquidity, inflation forecasts
    JEL: C22 C52 E41
    Date: 2013–04
    URL: http://d.repec.org/n?u=RePEc:wsr:wpaper:y:2013:i:119&r=for
  2. By: Arenas, Paúl (Universidad Nacional Mayor de San Marcos); Morales, Daniel (Rímac Seguros)
    Abstract: We use the results of business tendency surveys (BTS) to forecast private investment growth in Peru, exploring the possible non-linear link between the BTS and private investment for forecasting purposes. We find that business confidence indices extracted from BTS, in particular the one calculated by the Central Reserve Bank of Peru (CRBP), are useful to forecast private investment growth in Peru. Moreover, models constructed only with indices extracted from BTS have a higher predictive power than models including control variables such as lagged GDP growth, inflation or interest rates. We also find that non-linear models are not superior to linear ones in forecasting Peruvian private investment. Additionally, the linear model finally selected would allow us to estimate real private investment growth for the current quarter with a 75-day lead with respect to the official publication date, almost twice the lead associated with the estimation methodology used by practitioners.
    Keywords: Business Tendency Surveys, Business cycles, Private Investment, Forecasting
    JEL: E22 E27 E32 E37
    Date: 2013–04
    URL: http://d.repec.org/n?u=RePEc:rbp:wpaper:2013-003&r=for
  3. By: Raffaella Giacomini (University College London)
    Abstract: We propose a method for modifying a given density forecast in a way that incorporates the information contained in theory-based moment conditions. An example is "improving" the forecasts from atheoretical econometric models, such as factor models or Bayesian VARs, by ensuring that they satisfy theoretical restrictions given for example by Euler equations or Taylor rules. The method yields a new density (and thus point-) forecast which has a simple and convenient analytical expression and which by construction satisfies the theoretical restrictions. The method is flexible and can be used in the realistic situation in which economic theory does not specify a likelihood for the variables of interest, and thus cannot be readily used for forecasting.
    Date: 2012
    URL: http://d.repec.org/n?u=RePEc:red:sed012:548&r=for
  4. By: Yuanhua Feng (University of Paderborn); Chen Zhou (University of Paderborn)
    Abstract: This paper discusses forecasting of long memory and a nonparametric scale function in nonnegative financial processes based on a fractionally integrated Log-ACD (FI-Log-ACD) and its semiparametric extension (Semi-FI-Log-ACD). Necessary and sufficient conditions for the existence of a stationary solution of the FI-Log-ACD are obtained. Properties of this model under log-normal assumption are summarized. A linear predictor based on the truncated AR(oo) form of the logarithmic process is proposed. It is shown that this proposal is an approximately best linear predictor. Approximate variances of the prediction errors for an individual observation and for the conditional mean are obtained. Forecasting intervals for these quantities in the log- and the original processes are calculated under log-normal assumption. The proposals are applied to forecasting daily trading volumes and daily trading numbers in financial market.
    Keywords: Approximately best linear predictor, FI-Log-ACD, financial forecasting, long memory time series, nonparametric methods, Semi-FI-Log-ACD
    Date: 2013–04
    URL: http://d.repec.org/n?u=RePEc:pdn:wpaper:59&r=for
  5. By: Wolfgang Polasek (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria and University of Porto, Portugal)
    Abstract: Growth rate data that are collected incompletely in cross-sections is a quite frequent problem. Chow and Lin (1971) have developed a method for predicting unobserved disaggregated time series and we propose an extension of the procedure for completing cross-sectional growth rates similar to the spatial Chow-Lin method of Liano et al. (2009). Disaggregated growth rates cannot be predicted directly and requires a system estimation of two Chow-Lin prediction models, where we compare classical and Bayesian estimation and prediction methods. We demonstrate the procedure for Spanish regional GDP growth rates between 2000 and 2004 at a NUTS-3 level. We evaluate the growth rate forecasts by accuracy criteria, because for the Spanish data-set we can compare the predicted with the observed values.
    Keywords: Interpolation, missing disaggregated values in spatial econometrics, MCMC, Spatial Chow-Lin methods, predicting growth rates data, spatial autoregression (SAR), forecast evaluation, outliers
    JEL: C11 C15 C52 E17 R12
    Date: 2013–04
    URL: http://d.repec.org/n?u=RePEc:ihs:ihsesp:295&r=for
  6. By: Nikola Mirkov (Universität St.Gallen); Gisle James Natvik (Norges Bank (Central Bank of Norway))
    Abstract: If central banks value the ex-post accuracy of their forecasts, previously announced interest rate paths might affect the current policy rate. We explore whether this "forecast adherence" has influenced the monetary policies of the Reserve Bank of New Zealand and the Norges Bank, the two central banks with the longest history of publishing interest rate paths. We derive and estimate a policy rule for a central bank that is reluctant to deviate from its forecasts. The rule can nest a variety of interest rate rules. We find that policymakers appear to be constrained by their most recently announced forecasts.
    Keywords: Interest rates, Forecasts, Taylor rule, Adherence
    JEL: E43 E52 E58
    Date: 2013–04–11
    URL: http://d.repec.org/n?u=RePEc:bno:worpap:2013_11&r=for
  7. By: Cuenca, Leonidas (Apoyo Consultoría); Flores, Julio (Apoyo Consultoría); Morales, Daniel (Rímac Seguros)
    Abstract: The Consumer Confidence Index of APOYO Consultoría (INDICCA) is computed based on the responses to ten questions of a monthly survey in the city of Lima which aim to reflect the consumers’ spending intentions. We evaluate some sub-components of INDICCA in terms of their predictive and explanatory power of private consumption. In this process, we also evaluate the disaggregation on socioeconomic levels of this index, and a synthetic indicator of confidence based on dynamic factor models suggested by Jonsson and Lindén (2009) as an alternative way to combine the information contained in the sub-components of this index. We find that the explanatory and predictive power of private consumption models in Peru is enhanced when consumer confidence indices are included. However, this improvement is only marginal when other control variables such as employment or inflation are added. In particular, the optimal consumer confidence indicator is the synthetic indicator constructed with the dynamic factor model procedure. The results presented in this paper, although valid for some sub-components, are still inconclusive for the overall INDICCA.
    Keywords: consumer confidence, consumer tendency surveys, private consumption, forecasting
    JEL: E21 E27 C22
    Date: 2013–04
    URL: http://d.repec.org/n?u=RePEc:rbp:wpaper:2013-004&r=for
  8. By: Michele Modugno (ECB); Lucrezia Reichlin (London Business School); Domenico Giannone (Université Libre de Bruxelles); Marta Banbura (European Central Bank)
    Abstract: Economists have imperfect knowledge of the present state of the economy and even of the recent past. Many key statistics are released with a long delay and they are subsequently revised. As a consequence, unlike weather forecasters, who know what is the weather today and only have to predict the weather tomorrow, economists have to forecast the present and even the recent past. The problem of predicting the present, the very near future and the very recent past is labelled as nowcasting and is the subject of this paper.
    Date: 2012
    URL: http://d.repec.org/n?u=RePEc:red:sed012:555&r=for
  9. By: Taro Ikeda (Kurume University, Faculty of Economics)
    Abstract: This paper provides a piece of results regarding asymmetric forecasting and commitment monetary policy with a robust control algorithm. Previous studies provide no clarification of the connection between asymmetric preference and robust commitment policy. Three results emerge from general equilibrium modeling with asymmetric preference: (i) the condition for system stability implies an average inflation bias with respect to asymmetry (ii) the effect of asymmetry can be mitigated if policy makers relinquish a concern for robustness, and (iii) commitment policy may be superior to discretionary policy under widely used calibration sets, regardless of asymmetry.
    Keywords: asymmetric forecasting, commitment monetary policy, robust control
    JEL: E50 E52 E58
    Date: 2013–04
    URL: http://d.repec.org/n?u=RePEc:koe:wpaper:1306&r=for
  10. By: Dominique, C-Rene
    Abstract: This paper investigates the impact of the Kolmogorov-Sinai entropy on both the accuracy of probabilistic forecasts and the sluggishness of economic growth. It first posits the Gaussian process Zt (indexed by the Hurst exponent H) as the output of a reflexive dynamic input/output system governed by some type of attractor. It next indexes families of attractors by the Hausdorff measure (D0) and assesses the uncertainty level plaguing probabilistic forecast in each family. The D0 signature of attractors is next applied to the S&P-500 Index The result allows the construction of the dynamic history of the index and establishes robust links between the Hausdorff dimension, investors’ behavior, and economic growth
    Keywords: Stochastic processes, Housdorff dimension, forecasts, entrupy, attractors (strange, complex, low dimensional, chaotic), investors’ behavior, economic growth.
    JEL: G1
    Date: 2013–04–13
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:46231&r=for
  11. By: Alexander Budzier; Bent Flyvbjerg
    Abstract: The cost-benefit analysis formulates the holy trinity of objectives of project management - cost, schedule, and benefits. As our previous research has shown, ICT projects deviate from their initial cost estimate by more than 10% in 8 out of 10 cases. Academic research has argued that Optimism Bias and Black Swan Blindness cause forecasts to fall short of actual costs. Firstly, optimism bias has been linked to effects of deception and delusion, which is caused by taking the inside-view and ignoring distributional information when making decisions. Secondly, we argued before that Black Swan Blindness makes decision-makers ignore outlying events even if decisions and judgements are based on the outside view. Using a sample of 1,471 ICT projects with a total value of USD 241 billion - we answer the question: Can we show the different effects of Normal Performance, Delusion, and Deception? We calculated the cumulative distribution function (CDF) of (actual-forecast)/forecast. Our results show that the CDF changes at two tipping points - the first one transforms an exponential function into a Gaussian bell curve. The second tipping point transforms the bell curve into a power law distribution with the power of 2. We argue that these results show that project performance up to the first tipping point is politically motivated and project performance above the second tipping point indicates that project managers and decision-makers are fooled by random outliers, because they are blind to thick tails. We then show that Black Swan ICT projects are a significant source of uncertainty to an organisation and that management needs to be aware of.
    Date: 2013–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1304.4590&r=for
  12. By: Roberto Casarin (University Ca’ Foscari of Venice and GRETA); Stefano Grassi (Aarhus University and CREATES); Francesco Ravazzolo (Norges Bank and BI Norwegian Business School); Herman K. van Dijk (Erasmus University Rotterdam, VU University Amsterdam and Tinbergen Institute)
    Abstract: This paper presents the Matlab package DeCo (Density Combination) which is based on the paper by Billio et al. (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from different models or other sources of information. The combination weights are time-varying and may depend on past predictive forecasting performances and other learning mechanisms. The core algorithm is the function DeCo which applies banks of parallel Sequential Monte Carlo algorithms to filter the time-varying combination weights. The DeCo procedure has been implemented both for standard CPU computing and for Graphical Process Unit (GPU) parallel computing. For the GPU implementation we use the Matlab parallel computing toolbox and show how to use General Purposes GPU computing almost effortless. This GPU implementation comes with a speed up of the execution time up to seventy times compared to a standard CPU Matlab implementation on a multicore CPU. We show the use of the package and the computational gain of the GPU version, through some simulation experiments and empirical applications.
    Keywords: Density Forecast Combination, Sequential Monte Carlo, Parallel Computing, GPU, Matlab
    JEL: C11 C15 C53 E37
    Date: 2013–08–04
    URL: http://d.repec.org/n?u=RePEc:aah:create:2013-09&r=for
  13. By: Matthieu Segol (UP1 UFR02 - Université Paris 1, Panthéon-Sorbonne - UFR d'Économie - Université Paris I - Panthéon-Sorbonne - PRES HESAM)
    Abstract: Prediction markets are specific financial markets designed to produce forecasts of future events, such as political election outcomes or economic policy decisions. Empirical studies have exhibited over the years the significant accuracy of these anticipations, which tends to give credit to the efficicent market hypothesis advocated by the literature. However the latter relies theoretically on rational behaviors, in sharp contrast with traders' actions observed on most prediction markets. Indeed, an important fraction of participants are subject to several judgement bias. Based on Ottaviani and Sorensen's (2010) approach, we develop a framework that allows to introduce these biased traders and to study the consequences on the equilibrium properties.
    Keywords: marché financier
    Date: 2012
    URL: http://d.repec.org/n?u=RePEc:hal:journl:dumas-00809694&r=for
  14. By: Shinichiro Shirota (Graduate School of Economics, University of Tokyo); Takayuki Hizu (Mitsubishi UFJ Trust and Banking); Yasuhiro Omori (Faculty of Economics, University of Tokyo)
    Abstract: The daily return and the realized volatility are simultaneously modeled in the stochastic volatility model with leverage and long memory. The dependent variable in the stochastic volatility model is the logarithm of the squared return, and its error distribution is approximated by a mixture of normals. In addition, we incorporate the logarithm of the realized volatility into the measurement equation, assuming that the latent log volatility follows an Autoregressive Fractionally Integrated Moving Average (ARFIMA) process to describe its long memory property. Using a state space representation, we propose an efficient Bayesian estimation method implemented using Markov chain Monte Carlo method (MCMC). Model comparisons are performed based on the marginal likelihood, and the volatility forecasting performances are investigated using S&P500 stock index returns.
    Date: 2013–03
    URL: http://d.repec.org/n?u=RePEc:tky:fseres:2013cf880&r=for
  15. By: Mensi, Walid; Beljid, Makram; Boubaker, Adel; Managi, Shunsuke
    Abstract: This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000-2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets.
    Keywords: Stock markets, Commodity prices, Volatility spillovers, Hedge ratios, VAR-GARCH models, Energy price
    JEL: Q34 Q41
    Date: 2013–02–15
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:44395&r=for
  16. By: Jack Favilukis (London School of Economics); Xiaoji Lin (The Ohio State University)
    Abstract: In standard production based models labor income volatility is far too high and equity return volatility is far too low (excess volatility puzzle). We show that a simple modification of the standard model - infrequent renegotiation of labor income - allows the model to match both the smoother wages and the high equity return volatility observed in the data. Furthermore, the model produces several other hard to explain features of financial data: high unconditional Sharpe Ratios; time-varying equity premium, equity volatility, and Sharpe Ratio; as well a higher expected returns for value stocks over growth stocks. The intuition is that in standard models, highly pro-cyclical and volatile wages act as a hedge for the firm, reducing profits in good times and increasing them in bad times; this causes profit and returns to be too smooth. Infrequent renegotiation smoothes wages and smooth wages act like operating leverage, making profits more risky. Bad times and unproductive firms are especially risky because committed wage payments are high relative to output. Consistent with our model, we show that in the data wage growth can forecast long horizon returns, furthermore we find the same predictability at the industry level, with more rigid industries having stronger predictability.
    Date: 2012
    URL: http://d.repec.org/n?u=RePEc:red:sed012:589&r=for
  17. By: Javier Alonso; David Tuesta; Diego Torres; Begona Villamide
    Abstract: The increase in longevity risk is leading to serious challenges for economies. Industries such as insurance and pensions, which are most closely related to the management of the risks of an aging population, have for a number of years experienced direct effects of this kind. To counterbalance this, they have developed techniques for constructing mortality tables in order to project the future trends of life expectancy at birth and thus reduce the level of uncertainty that this market by its nature involves. Developed countries have led technical improvements for constructing these tables, while Latin American countries have lagged behind significantly in this respect. Given that these countries cannot yet develop tables weighted by social and medical aspects, it is highly probable that this situation will continue. That is why this study aims to construct a forecast for mortality rates, based on projection models of the ARMA (p, q) type and non-parametric contrast methodology. The study is based on the case of Chile, which provides most information for constructing a model for a Latin American country. The estimates show that the official mortality tables in Chile could include significant lags by 2050, which will have major negative effects on the pension and insurance industry, in the hypothetical case that they were not updated. In another exercise, using the mortality table estimated in this work, we found that if pensions in Chile are not to lose their purchasing power, the contribution rate would have to be increased by 8 percentage points in the case of men and 4 in the case of women. Given that Chile is the best developed country in the region with respect to mortality tables, the negative effects on the rest of Latin America could be even more worrisome.
    Keywords: Pensions, insurance, longevity risk, mortality tables, Latin America, Chile
    JEL: G23 J32 G22
    Date: 2013–04
    URL: http://d.repec.org/n?u=RePEc:bbv:wpaper:1315&r=for
  18. By: Rafal Koziarski (UE - Wroclaw University of Economics - Wroclaw University of Economics)
    Abstract: The present research project attempts to forecast future value of sales revenue for public company which operates in sector "restaurants and mobile food service activities" (i.e. in class 56.10 according to the NACE classification). Financial projection is prepared for a next year (it means 2012). Author try to estimate company's financial condition using fundamental analysis and analyzing its financial statements. Furthermore author using "steady state model" to predict future sales revenue.---Niniejszy projekt badawczy ma na celu sporządzenie prognozy przyszłej wartość przychodów ze sprzedaży w spółce akcyjnej, która działa w branży "restauracje i ruchome placówki gastronomiczne" (czyli w klasie 56.10 według klasyfikacji NACE). Prognoza finansowa jest przygotowana dla następnego roku (to znaczy 2012). Autor próbuje ocenić kondycję finansową firmy za pomocą analizy fundamentalnej i badania sprawozdań finansowych. Ponadto autor korzystając z metody "modelowania w stałych warunkach" stara się przewidzieć przyszłą wielkość sprzedaży.
    Keywords: sales planning, sales revenue projection, fundamental analysis, planowanie finansowe, prognoza sprzedaży, analiza finansowa
    Date: 2013–03–20
    URL: http://d.repec.org/n?u=RePEc:hal:wpaper:hal-00808100&r=for

This nep-for issue is ©2013 by Rob J Hyndman. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at http://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.