American Academy in Berlin

This Viewpoint discusses the importance of federal funding of biomedical research from the National Institutes of Health to scientific discovery, advancements in individual and public health, and the support of the US’ community of scientists.

A long-lasting injectable drug was tested in seven African countries. But it's unclear when they'll have access to it.

October 01 2019 Regioning Differences: Translation and Critical Cartography Emily Apter Emily Apter Emily Apter is Julius Silver Professor of French and Comparative Literature and Chair of Comparative Literature at New York University. Her books include Unexceptional Politics: On Obstruction, Impasse and the Impolitic (Verso, 2018); Against World Literature: On The Politics of Untranslatability (2013); Dictionary of Untranslatables: A Philosophical Lexicon (2014); and The Translation Zone: A New Comparative Literature (2006). She is currently working on a book titled What Is Just Translation? Her essays have appeared in Political Concepts, October, PMLA, Comparative Literature, Art Journal, Third Text, Paragraph, Boundary 2, Artforum, and Critical Inquiry. In spring 2019 she was a Fellow at the American Academy in Berlin. In 2017–18 she served as President of the American Comparative Literature Association and spent fall 2014 as a Humanities Council Fellow at Princeton University. In 2003–2004 she was a Guggenheim Fellowship recipient. Search for other works by this author on: This Site Google Scholar Author and Article Information Emily Apter Emily Apter is Julius Silver Professor of French and Comparative Literature and Chair of Comparative Literature at New York University. Her books include Unexceptional Politics: On Obstruction, Impasse and the Impolitic (Verso, 2018); Against World Literature: On The Politics of Untranslatability (2013); Dictionary of Untranslatables: A Philosophical Lexicon (2014); and The Translation Zone: A New Comparative Literature (2006). She is currently working on a book titled What Is Just Translation? Her essays have appeared in Political Concepts, October, PMLA, Comparative Literature, Art Journal, Third Text, Paragraph, Boundary 2, Artforum, and Critical Inquiry. In spring 2019 she was a Fellow at the American Academy in Berlin. In 2017–18 she served as President of the American Comparative Literature Association and spent fall 2014 as a Humanities Council Fellow at Princeton University. In 2003–2004 she was a Guggenheim Fellowship recipient. Online Issn: 2162-2582 Print Issn: 2162-2574 © 2019 ARTMargins and the Massachusetts Institute of Technology2019ARTMargins and the Massachusetts Institute of Technology ARTMargins (2019) 8 (3): 55–78. https://doi.org/10.1162/artm_a_00244 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Emily Apter; Regioning Differences: Translation and Critical Cartography. ARTMargins 2019; 8 (3): 55–78. doi: https://doi.org/10.1162/artm_a_00244 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsARTMargins Search Advanced Search This content is only available as a PDF. © 2019 ARTMargins and the Massachusetts Institute of Technology2019ARTMargins and the Massachusetts Institute of Technology Article PDF first page preview Close Modal You do not currently have access to this content.

Five charterholders featured in the CFA Institute Global Brand Campaign tell their stories and offer career advice.

More and more investors are tracking and analyzing news flows and text sentiments in large, unstructured datasets and mining data in a split second for investment-relevant information. Often, the goal is to incorporate findings into trading strategies and algorithms, to back-test investment theses, or to improve risk-monitoring activities. Finding information of interest in large, textual databases is becoming easier as semantic analytic technologies mature. Tools already abound to help companies monitor the sentiment toward their brands by evaluating “big data” repositories, such as customer comments. Text and news analytics for investing is a newer niche application, and many are now experimenting with investment use cases. As they do, the need to quantify and incorporate unstructured data into investing equations continues to grow, along with the volume of textual data: About 2.5 billion gigabytes of data were generated every day in 2012, according to IBM, and by some estimates, 75% of data are unstructured. Data sources that drive tools for investors are diverse and depend on the vendor of the analytics. Some vendors allow users to hand-pick data and custom aggregate it. A few examples of data sources for text analytics are news feeds, select blogs, social media data, RSS (rich site summary) feeds, customer relationship management (CRM) data, and audio and TV news transcripts, such as CNBC’s Squawk Box transcripts. News analytics have been used for years in equity investing, but now, investors are applying these tools in global macro strategies and foreign exchange (FX) trading as well as in commodities and fixed-income investing. Early adopters include quantitative hedge funds in the United States and United Kingdom. Machine learning capabilities are getting better at interpreting and almost understanding what news may mean, although many pitfalls still exist. Most news analytics tools use sentiment analysis algorithms that work with a simple scoring mechanism. Using natural language processing, the algorithm counts the number of positive words and the number of negative words in a text and then assesses which company name appears most in the text. The algorithm assigns a positive or negative score to the text, often including a relevance or probability score for the different entities. It then aggregates this data over the whole news flow and gives users an indication of whether certain companies or terms are trending positive or negative. Some tools score news sentiment and present it as a time series, measure the volume of media coverage, or capture deviations in media coverage that can be telling for investors. Other tools define and track entity relationships in massive textual datasets. The focus of news analytics tools is no longer on speed or reducing latency, according to Armando Gonzalez, president and CEO of RavenPack, a provider of news analytics for quantitative finance applications. “It’s about developing sustainable alpha or verifiable risk management strategies from unstructured data,” he says. “Can users reliably extract a durable signal from the vast amount of news and social content out there that lives for hours, days, weeks, and ideally months?”

Investors’ failure to understand the two different types of thinking is costly, says Nobel laureate Daniel Kahnman