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on Forecasting |
| By: | Leonardo Morales-Arias; Alexander Dross |
| Abstract: | This article investigates the statistical and economic implications of adaptive forecasting of exchange rates with panel data and alternative predictors. The candidate exchange rate predictors are drawn from (i) macroeconomic ‘fundamentals’, (ii) return/volatility of asset markets and (iii) cyclical and confidence indices. Exchange rate forecasts at various horizons are obtained from each of the potential predictors using single market, mean group and pooled estimates by means of rolling window and recursive forecasting schemes. The capabilities of single predictors and of adaptive techniques for combining the generated exchange rate forecasts are subsequently examined by means of statistical and economic performance measures. The forward premium and a predictor based on a Taylor rule yield the most promising forecasting results out of the macro ‘fundamentals’ considered. For recursive forecasting, confidence indices and volatility in-mean yield more accurate forecasts than most of the macro ‘fundamentals’. Adaptive forecast combinations techniques improve forecasting precision and lead to better market timing than most single predictors at higher horizons |
| Keywords: | Exchange rate forecasting, panel data, forecast combinations, market timing |
| JEL: | C20 F31 G12 |
| Date: | 2010–10 |
| URL: | http://d.repec.org/n?u=RePEc:kie:kieliw:1656&r=for |
| By: | Francesco C Billari; Rebecca Graziani; Eugenio Melilli |
| Abstract: | We develop a method for the derivation of expert-based stochastic population forecasts. The full probability distribution of forecasts is specified by expert opinions on future developments, elicited conditional on the realization of high, central, low scenarios. The procedure is applied to forecast the Italian population, using scenarios from the Italian National Statistical Office (ISTAT) and the Statistical Office of the European Union (EUROSTAT). |
| Keywords: | stochastic population forecasting, random scenario, conditional expert opinions, Italian population forecasts |
| Date: | 2010–11 |
| URL: | http://d.repec.org/n?u=RePEc:don:donwpa:033&r=for |
| By: | Chan, Tze-Haw; Lye, Chun Teck; Hooy, Chee-Wooi |
| Abstract: | Being a small and open economy, the stability and predictability of Malaysian foreign exchange are crucially important. However, despite the general failure of conventional monetary models, foreign exchange misalignments and authority intervention have both caused the forecasting process an uneasy task. The present paper employs the monetary-portfolio balance exchange rate model and its modified version in the analysis. We then compare two Artificial Neural Networks (ANNs) estimation procedures (MLFN and GRNN) with random walk (RW) in the modeling-prediction process of RM/USD during the post-Bretton Wood era (1990M1-2008M8). The out-of-sample forecasting assessment reveals that the ANNs have outperformed the RW, which in particular, the MLFNs outperform GRNNs where as the latter outperform the RW models with consistency in both the exchange rate models by all evaluation criteria. In addition, the findings also show that the modified model has superior forecasting performance than the first model. In brief, economic fundamentals are vital in forecasting and explaining the RM/USD exchange rate. The findings are beneficial in policy making, investment modeling as well as corporate planning. |
| Keywords: | Artificial Neural Networks; Forecasting; modified monetary-portfolio balance model; RM/USD |
| JEL: | C53 C45 F31 |
| Date: | 2010–04–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:26326&r=for |
| By: | Ralf Becker; Adam Clements; Robert O'Neill |
| Abstract: | In this paper we propose a novel methodology for forecasting variance convariance matrices (VCM) using kernel estimates. While the popular Riskmetrics methodology can be seen as a special case of our methodology, the generalisation is significant as it allows the researcher to use a number of variables to determine the kernel weights of past VCM. The complexity of the methodology scales with the number of explanatory variables used and not with the size of the VCM. This, as well as the automatic positive definiteness of the VCM forecasts are major improvements on currently available forecasting methods. An empirical analysis establishes the usefulness of our proposed methodology. |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:man:cgbcrp:151&r=for |
| By: | Yu-chin Chen (University of Washington and Hong Kong Institute for Monetary Research); Kwok Ping Tsang (Virginia Tech and Hong Kong Institute for Monetary Research); Wen Jen Tsay (Academia Sinica) |
| Abstract: | The "home bias" phenomenon states that empirically, economic agents often under-utilize opportunities beyond their country borders, and it is well-documented in various international pricing and purchase patterns. This bias manifests in the forms of fewer exchanges of goods and net equity-holdings, as well as less arbitrage of price differences across borders than theoretically predicted to be optimal. Our paper documents another form of home bias, where market participants appear to under-weigh information beyond their borders when making currency forecasts. Using monthly data from 1995 to 2010 for seven major exchange rates relative to the US dollar, we show that excess currency returns and the errors in investors' consensus forecasts not only depend on the interest differentials between the pair of countries, but they depend more strongly on interest rates in a broader set of countries. A global short interest differential and a global long interest differential are driving the results. |
| Keywords: | Survey Data, Excess Currency Returns, Global Shock |
| JEL: | F31 G12 D84 |
| Date: | 2010–10 |
| URL: | http://d.repec.org/n?u=RePEc:hkm:wpaper:272010&r=for |