nep-for New Economics Papers
on Forecasting
Issue of 2017‒08‒06
four papers chosen by
Rob J Hyndman
Monash University

  1. Automated Earnings Forecasts:- Beat Analysts or Combine and Conquer? By Ball, Ryan; Ghysels, Eric
  2. Forecasting Inflation in Latin America with Core Measures By Pincheira, Pablo; Selaive, Jorge; Nolazco, Jose Luis
  3. Assessment of Density Forecast for Energy Commodities in Post-Financialization Era By Bisht Deepak; Laha, A. K.
  4. What do the shadow rates tell us about future inflation? By Kuusela, Annika; Hännikäinen, Jari

  1. By: Ball, Ryan; Ghysels, Eric
    Abstract: Prior studies attribute analysts' forecast superiority over time-series forecasting models to their access to a large set o firm, industry, and macroeconomic information (an information advantage), which they use to update their forecasts on a daily, weekly or monthly basis (a timing advantage). This study leverages recently developed mixed data sampling (MIDAS) regression methods to synthesize a broad spectrum of high frequency data to construct forecasts of firm-level earnings. We compare the accuracy of these forecasts to those of analysts at short horizons of one quarter or less. We find that our MIDAS forecasts are more accurate and have forecast errors that are smaller than analysts' when forecast dispersion is high and when the firm size is smaller. In addition, we find that combining our MIDAS forecasts with analysts' forecasts systematically outperforms analysts alone, which indicates that our MIDAS models provide information orthogonal to analysts. Our results provide preliminary support for the potential to automate the process of forecasting firm-level earnings, or other accounting performance measures, on a high-frequency basis.
    Date: 2017–07
  2. By: Pincheira, Pablo; Selaive, Jorge; Nolazco, Jose Luis
    Abstract: We explore the ability of core inflation to predict headline CPI annual inflation for a sample of 8 developing economies in Latin America during the period January 1995-May 2017. Our in-sample and out-of-sample results are roughly consistent in providing evidence of predictability in the great majority of our countries, although, as usual, a slightly stronger evidence of predictability comes from the in-sample analysis. The bulk of the out-of-sample evidence of predictability concentrates at the short horizons of 1 and 6 months. In contrast, at longer horizons of 12 and 24 months, we only find evidence of predictability for two countries: Chile and Colombia. This is both important and challenging, given that monetary authorities in our sample of developing countries are currently implementing or given steps toward the future implementation of inflation targeting regimes, which are heavily based on long run inflation forecasts.
    Keywords: Inflation, Forecasting, Time Series, Monetary Policy, Core Inflation, Developing Countries.
    JEL: E31 E37 E4 E47 E50 E52 E58 F4 F41 F47 O11 O23 O54
    Date: 2017–07–17
  3. By: Bisht Deepak; Laha, A. K.
    Abstract: Probability density for the future price of an asset can be estimated from historical asset prices or exchange-traded derivatives. In this paper, prices of futures and options contracts that embed the forward-looking information are used to obtain the density forecast of the underlying asset under Q- measure. Along with Probability Integral Transform (PIT), various statistical testes are conducted to determine whether the option-implied density forecast is unbiased under the real world measure, P. We have worked with the settlement prices of NYMEX traded futures and options contracts for WTI crude oil and Henry Hub natural gas during the post-financialization period of 2006 to 2013. Statistical analysis of the PIT values indicate that the option-implied density forecast is unbiased under the real world measure, P.
    Date: 2017–07–31
  4. By: Kuusela, Annika; Hännikäinen, Jari
    Abstract: This paper investigates whether shadow interest rates contain predictive power for U.S. inflation in a data-rich environment. We find that shadow rates are useful leading indicators of inflation. Shadow rates contain substantial in-sample and out-of-sample predictive power for inflation in both the zero lower bound (ZLB) and non-ZLB periods. We find that the shadow rate suggested by Wu and Xia (2016) contains more information about future inflation than the shadow rate suggested by Krippner (2015b).
    Keywords: shadow interest rates, zero lower bound, unconventional monetary policy, inflation forecasting, data-rich environment, factor models
    JEL: C38 C53 E37 E43 E44 E58
    Date: 2017–08–01

This nep-for issue is ©2017 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 For comments please write to the director of NEP, Marco Novarese at <>. 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.