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Improving the accuracy of outlook price forecasts: An application to livestock markets.

机译:提高前景价格预测的准确性:在畜牧市场上的应用。

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摘要

The performance and economic value of public outlook forecasts has been of continuing interest to agricultural economists and market participants. This dissertation provide new and powerful evidence on the performance of outlook forecasts relative to futures prices in hog and cattle markets over the last three decades and evaluates numerous time-series models and combinatory procedures as forecasting techniques to improve the predictive accuracy of hog price outlook forecasts. Many of these forecasting techniques have never been applied to livestock markets. Quarterly data from the mid- to late-1970s through 2007 for up to three-quarter ahead is available from four prominent outlook programs: University of Illinois/Purdue University, Iowa State University, University of Missouri, and the Economic Research Service of the U.S. Department of Agriculture (USDA). Overall, results show that in general, futures outperform outlook with some differences statistical significant. However, a combination of futures and outlook forecasts generally provide lower forecast errors than futures alone, and therefore, outlook forecasts of hog and cattle prices provide incremental information relative to futures prices. When compared to numerous time-series models, Iowa's estimates are in general outperformed with statistical insignificant differences. However, even with the use of simple time-series models, findings from the encompassing tests highlight the efficacy of improving Iowa's price forecasting performance via composite procedures. Finally, given the potential benefits of forecast combination, numerous combinatory techniques are evaluated in a true out-of-sample context. A true out-of-sample evaluation of composite forecasts is an issue not always carefully considered in the literature. Results show that significant forecast error reductions can be obtained from the combination of outlook, futures and two simple time-series models under most of the methods considered. More interesting, the simple average composite shows an outstanding performance that tends to increase at longer horizons, a result consistent with previous literature. In addition, evidence says that the accuracy of futures prices is stellar at the first horizon, but weaker at distant horizons, suggesting that the value of market forecasts lies primarily in the short-run.
机译:公众前景预测的表现和经济价值一直受到农业经济学家和市场参与者的关注。本文为近三十年来生猪和牛市场的前景预测相对于期货价格的表现提供了新的有力证据,并评估了许多时间序列模型和组合程序作为预测技术,以提高生猪价格前景预测的预测准确性。其中许多预测技术从未应用于畜牧市场。四个著名的展望计划提供了从1970年代中期至2007年末的季度数据,最多可提前四分之三:伊利诺伊大学/普渡大学,爱荷华州立大学,密苏里大学和美国经济研究局农业部(USDA)。总体而言,结果表明,总体而言,期货表现优于前景,但存在一些统计差异。但是,期货和前景预测的组合通常提供的预测误差比单独的期货要低,因此,生猪和牛价格的前景预测提供了相对于期货价格的增量信息。与众多时间序列模型相比,爱荷华州的估计值总体上在统计上无显着差异,其表现要好于其他。但是,即使使用简单的时间序列模型,涵盖测试的结果也突出显示了通过复合程序改善爱荷华州价格预测性能的功效。最后,鉴于预测组合的潜在好处,在真实的样本外环境中评估了许多组合技术。对综合预测进行真正的样本外评估是一个在文献中并不总是认真考虑的问题。结果表明,在大多数考虑的方法下,可以通过结合前景,期货和两个简单​​的时间序列模型来获得显着的预测误差减少。更有趣的是,简单的平均复合材料显示出出色的性能,并且在较长的时间范围内倾向于增加,这一结果与以前的文献一致。此外,有证据表明,期货价格的准确性在最初的视野中是恒星,但在较远的视野中则较弱,这表明市场预测的价值主要在于短期。

著录项

  • 作者

    Colino, Evelyn Del Valle.;

  • 作者单位

    University of Illinois at Urbana-Champaign.;

  • 授予单位 University of Illinois at Urbana-Champaign.;
  • 学科 Economics Agricultural.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 150 p.
  • 总页数 150
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农业经济;
  • 关键词

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