Modern Language Processing that Portfolio Managers can leverage
Information is life blood for trading! Portfolio managers are constantly looking to make trades by buying and selling stocks to benefit their portfolios.
Portfolio managers deal with a wealth of information, in the form of text. This includes, but is not limited to, news articles, social media posts, earnings reports, regulatory submissions, research reports, etc. News makes up a substantial part of the information that is consumed by investment professionals on a daily basis. These sources provide valuable insights that can impact investment decisions, however, extracting the meaningful information from the sea of texts is challenging. Portfolio managers must sift through an avalanche of information, in real time, especially to identify insights. This process not only demands significant time and resources but also puts managers at a risk of missing out on crucial bits of information. Ensuring the quality and reliability of textual data is also a challenge. Since portfolio managers use information from a variety of sources including social media, it is imperative to carefully evaluate sources and to consider potential biases. Portfolio managers must also remove irrelevant bits of information, a laborious and time-consuming process and requires the support of automation.
Extracting actionable insights from text data requires sophisticated text analytics techniques. To best navigate these challenges, portfolio managers must rely on a combination of human expertise and modern language processing technologies like TextDistil from Lead Semantics.
Automatic Language processing to the rescue
TextDistil is a robust text processing tool that uses modern Natural language processing to extract knowledge from large bodies of text. TextDistil can serve as a valuable tool in assessing long-term financial risk objectives by enabling efficient filtering
and automated understanding. Portfolio managers that have a focus on ESG investments can also incorporate TextDistil in their daily analysis workflows to assess the ESG performance of companies in their portfolios.
Overall, staying current with the latest AI, Language and Knowledge technologies and continuously refining analytical processes helps portfolio managers to leverage the text data that is available abundantly all around. Successfully harnessing textual information empowers portfolio managers to make informed investment decisions, mitigate risk, and seize new opportunities in an increasingly complex and dynamic trading landscape.
