英文标题：
《Machine Learning for Better Models for Predicting Bond Prices》
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作者：
Swetava Ganguli, Jared Dunnmon
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最新提交年份：
2017
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英文摘要：
Bond prices are a reflection of extremely complex market interactions and policies, making prediction of future prices difficult. This task becomes even more challenging due to the dearth of relevant information, and accuracy is not the only consideration--in trading situations, time is of the essence. Thus, machine learning in the context of bond price predictions should be both fast and accurate. In this course project, we use a dataset describing the previous 10 trades of a large number of bonds among other relevant descriptive metrics to predict future bond prices. Each of 762,678 bonds in the dataset is described by a total of 61 attributes, including a ground truth trade price. We evaluate the performance of various supervised learning algorithms for regression followed by ensemble methods, with feature and model selection considerations being treated in detail. We further evaluate all methods on both accuracy and speed. Finally, we propose a novel hybrid time-series aided machine learning method that could be applied to such datasets in future work.
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中文摘要：
债券价格反映了极其复杂的市场互动和政策，因此很难预测未来的价格。由于缺乏相关信息，这项任务变得更具挑战性，准确性并不是唯一的考虑因素——在交易情况下，时间至关重要。因此，在债券价格预测的背景下，机器学习应该既快速又准确。在本课程项目中，我们使用一个数据集来描述大量债券的前10次交易以及其他相关的描述性指标，以预测未来的债券价格。数据集中的762678份债券中的每一份都由61个属性描述，其中包括一个地面真实交易价格。我们评估了各种用于回归的监督学习算法的性能，然后是集成方法，并详细讨论了特征和模型选择问题。我们进一步评估了所有方法的准确性和速度。最后，我们提出了一种新的混合时间序列辅助机器学习方法，可以在未来的工作中应用于此类数据集。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类：Computer Science 计算机科学
二级分类：Computational Engineering, Finance, and Science 计算工程、金融和科学
分类描述：Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的，集中在技术和工具，使挑战性的计算模拟能够执行，其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4（经济学）中的材料。
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