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on Forecasting |
| By: | Michael P. Clements (ICMA Centre, Henley Business School, University of Reading); Ana Beatriz Galvao |
| Abstract: | The effects of data uncertainty on real-time decision-making can be reduced by predicting early revisions to US GDP growth. We show that survey forecasts efficiently anticipate the first-revised estimate of GDP, but that forecasting models incorporating monthly economic indicators and daily equity returns provide superior forecasts of the second-revised estimate. We consider the implications of these findings for analyses of the impact of surprises in GDP revision announcements on equity markets, and for analyses of the impact of anticipated future revisions on announcement-day returns. |
| Keywords: | Survey forecasts, data revisions, economic indicators, stock returns, macro announcements |
| JEL: | C53 |
| Date: | 2014–08 |
| URL: | http://d.repec.org/n?u=RePEc:rdg:icmadp:icma-dp2014-06&r=for |
| By: | Issler, João Victor; Notini, Hilton Hostalacio |
| Abstract: | This paper has several original contributions. The rst is to employ a superiorinterpolation method that enables to estimate, nowcast and forecast monthly BrazilianGDP for 1980-2012 in an integrated way; see Bernanke, Gertler and Watson (1997,Brookings Papers on Economic Activity). Second, along the spirit of Mariano andMurasawa (2003, Journal of Applied Econometrics), we propose and test a myriad ofinterpolation models and interpolation auxiliary series all coincident with GDP froma business-cycle dating point of view. Based on these results, we nally choose the mostappropriate monthly indicator for Brazilian GDP. Third, this monthly GDP estimateis compared to an economic activity indicator widely used by practitioners in Brazil- the Brazilian Economic Activity Index - (IBC-Br). We found that the our monthlyGDP tracks economic activity better than IBC-Br. This happens by construction,since our state-space approach imposes the restriction (discipline) that our monthlyestimate must add up to the quarterly observed series in any given quarter, whichmay not hold regarding IBC-Br. Moreover, our method has the advantage to be easilyimplemented: it only requires conditioning on two observed series for estimation, whileestimating IBC-Br requires the availability of hundreds of monthly series. Third, ina nowcasting and forecasting exercise, we illustrate the advantages of our integratedapproach. Finally, we compare the chronology of recessions of our monthly estimatewith those done elsewhere. |
| Date: | 2014–09–18 |
| URL: | http://d.repec.org/n?u=RePEc:fgv:epgewp:757&r=for |
| By: | Costantini, Mauro (Brunel University); Cuaresma, Jesus Crespo (Vienna University of Economics and Business); Hlouskova, Jaroslava (Institute for Advanced Studies, Vienna) |
| Abstract: | We provide a systematic comparison of the out-of-sample forecasts based on multivariate macroeconomic models and forecast combinations for the euro against the US dollar, the British pound, the Swiss franc and the Japanese yen. We use profit maximization measures based on directional accuracy and trading strategies in addition to standard loss minimization measures. When comparing predictive accuracy and profit measures, data snooping bias free tests are used. The results indicate that forecast combinations help to improve over benchmark trading strategies for the exchange rate against the US dollar and the British pound, although the excess return per unit of deviation is limited. For the euro against the Swiss franc or the Japanese yen, no evidence of generalized improvement in profit measures over the benchmark is found. |
| Keywords: | Exchange rate forecasting, Forecast combination, Multivariate time series models, Profitability |
| JEL: | C53 F31 F37 |
| Date: | 2014–09 |
| URL: | http://d.repec.org/n?u=RePEc:ihs:ihsesp:305&r=for |
| By: | Sasa Zikovic; Rafal Weron; Ivana Tomas Zikovic |
| Abstract: | In this paper we analyze the relative performance of 13 VaR models using daily returns of WTI, Brent, natural gas and heating oil one-month futures contracts. After obtaining VaR estimates we evaluate the statistical significance of the differences in performance of the analyzed VaR models. We employ the simulation-based methodology proposed by Zikovic and Filer (2013), which allows us to rank competing VaR models. Somewhat surprisingly, the obtained results indicate that for a large number of different VaR models there is no statistical difference in their performance, as measured by the Lopez size adjusted score. However, filtered historical simulation (FHS) and the semiparametric BRW model stand out as robust and consistent approaches that – in most cases – significantly outperform the remaining VaR models. |
| Keywords: | Energy markets; Risk management; Value at Risk; Multicriteria classification |
| JEL: | C14 C22 C52 C53 G24 |
| Date: | 2014–10–03 |
| URL: | http://d.repec.org/n?u=RePEc:wuu:wpaper:hsc1412&r=for |
| By: | IIZUKA Nobuo |
| Abstract: | Directional analysis is employed to evaluate the rationality and usefulness of a data set of monthly forecasts for the coincident index in ESRI's Indexes of Business Conditions by professional forecasters. Using Japanese ESP Forecast Survey data, our findings indicate that consensus forecasts with horizons of up to four months are valuable, whereas the Leading Index in ESRI's Indexes of Business Conditions is only valuable with horizons of up to two months. This finding suggests that the predictability of Leading DI can be improved with the aid of coincident DI forecasts. |
| Date: | 2013–10 |
| URL: | http://d.repec.org/n?u=RePEc:esj:esridp:305&r=for |