10 research outputs found

    Adaptive Forecasting of Exchange Rates with Panel Data

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    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.exchange rate forecasting; panel data; forecast combinations; market timing

    Adaptive Forecasting of Exchange Rates with Panel Data

    No full text
    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 horizonsExchange rate forecasting, panel data, forecast combinations, market timing

    Front side plasmonic effect on thin silicon epitaxial solar cells

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    We study the effect of metal nanoparticles, showing localised plasmonic resonances, on the spectrally resolved efficiency of thin film crystalline silicon solar cells. We investigate model structures: silver (Ag) nanodiscs on the surface of epitaxial cells grown on highly doped silicon substrates, with a controlled micron-scale thickness. The cells have no back reflector in order to exclusively study the effect of the front surface on their optical properties. The nanodiscs were deposited through hole-mask colloidal lithography, which is a low-cost, bottom-up and extremely versatile technique. As opposed to many other works, we use as benchmarks both bare silicon cells and cells with a dielectric antireflection coating. We optically observe a resonance showing an absorption increase, found to be controllable by the discs parameters. We also see an increase in short-circuit current with respect to bare cells, but we see a decrease in efficiency with respect to cells with a dielectric antireflection coating, due to losses at short wavelengths. As the material properties are not notably affected by the particles deposition, we show that the main loss mechanisms are an important parasitic absorption in the nanoparticles and destructive interferences

    Silver nanodiscs for light scattering in thin epitaxial silicon solar cells: Influence of the disc radius

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    The effect of silver nanoparticles showing localised plasmonic resonances on the efficiency of thin film silicon solar cells is studied. Silver (Ag) nanodiscs were deposited on the surface of silicon cells grown on highly doped silicon substrates, through hole-mask colloidal lithography, which is a low-cost and bottom-up technique. The cells have no back reflector in order to exclusively study the effect of the front surface on their properties. Cells with nanoparticles were compared with both bare silicon cells and cells with an antireflection coating. We optically observe a resonance showing an absorption increase controllable by the disc radius. We also see an increase in efficiency with respect to bare cells, but we see a decrease in efficiency with respect to cells with an antireflection coating due to losses at wavelengths below the plasmon resonance. As the material properties are not notably affected by the particles deposition, the loss mechanism is an important absorption in the nanoparticles. We confirm this by numerical simulations

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