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Bringing Semantic Intelligence to Financial Markets

机译:将语义智能带入金融市场

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The most successful hedge-funds in today's financial markets are consuming large amounts of alternative data, including satellite imagery, point-of-sale data, news, social media and publications from the web. This new trend is driven by the fact that traditional factors have become less predictive in recent years, requiring sophisticated investors to explore new data sources. The majority of this new alternative content is unstructured and hence must first be converted into structured analytics data in order to be used systematically. Instead of building such capabilities themselves, financial firms are turning towards companies that specialize in this field. In this talk, Kevin will discuss some of the practical challenges of giving structure to unstructured content, how entities and ontologies may be used to link data and the ways in which semantic intelligence can be derived for use in financial trading algorithms.
机译:当今金融市场上最成功的对冲基金正在消耗大量替代数据,包括卫星图像,销售点数据,新闻,社交媒体和网络出版物。这种新趋势是由以下事实驱动的:近年来,传统因素的预测性越来越低,需要经验丰富的投资者探索新的数据源。这种新的替代内容的大部分都是非结构化的,因此必须首先转换为结构化的分析数据,以便系统地使用。金融公司没有自己建立这种能力,而是转向专门从事这一领域的公司。在本次演讲中,Kevin将讨论将结构赋予非结构化内容的一些实际挑战,如何使用实体和本体来链接数据以及如何导出语义智能以用于金融交易算法的方法。

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