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earnings forecasters, we see that small adjustments to the model forecasts lead to more forecast accuracy. Based on past track …
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used to construct a forecast. Second, we discuss random projection regression, where artificial predictors are formed by … randomly weighting the original predictors. Using recent results from random matrix theory, we obtain a tight bound on the mean … squared forecast error for both randomized methods. We identify settings in which one randomized method results in more …
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This paper assesses the performance of a number of long-term interest rate forecast approaches, namely time series … is compared using out of sample forecast errors, where a random walk forecast acts as benchmark. It is found that for … approaches do not outperform the random walk, or a somewhat more sophisticated time series model, on a 3 month forecast horizon …
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In this paper we study what professional forecasters actually explain. We use spectral analysis and state space modeling to decompose economic time series into a trend, a business-cycle, and an irregular component. To examine which components are captured by professional forecasters we regress...
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