Abstract: We will briefly survey industry trends and techniques for using data to inform portfolio management and active trading. Bio: Dan Von Kohorn co-founded v2 Ratings, a quantitative investment ratings firm serving hedge funds and institutional investors. v2 Ratings integrates economic models with machine learning to rate securities based on risk-adjusted relative value. Dan is […]
Abstract: Many of the ideas and algorithms involved in machine learning/data science can be thought of as discovering geometric patterns and shapes in a collection of data points. From this perspective, common data science problems can be translated into geometry problems, and solved with (abstract) geometric tools. In this talk, I will explain how ideas […]
Abstract: This is an introductory overview of how to efficiently represent text (and images) for predictive analytics. Applications include Sentiment Analysis, classifying news stories or emails, building marketing models (acquisition, churn), and anomaly detection. The key technique is how to transform text (of varying length), as well as sentence or document structure, into a single, […]
Abstract: On a web portal users bid for projects, each one – users and projects – having many features. Due to a large number of projects at any point in time, only specific projects should be recommended to a user to potentially bid on on a daily basis. Because of the large size of underlying […]
Abstract: Domeyard is a low latency trading firm. This talk presents a common paradox in the context of quantitative trading and how advancements in technology can confront this problem. Bio: Christina Qi co-founded Domeyard LP, a quantitative hedge fund based in Boston. Domeyard leverages computational models to execute trades at extremely low latencies, deploying capital […]
Abstract: Buying a plane ticket is a time-consuming and frustrating process that often leaves the consumer unhappy. Flight prices are less transparent and fluctuate more than almost anything else a consumer buys, even though airfare is one of the most expensive purchases for a typical family. On average, consumers spend almost two weeks comparison shopping […]
In this interview with ODSC, Aparna and Hisham delve into term modeling and logistic regression at Dow Jones.
In this interview with ODSC, Dave explains the meaning behind Exaptive, and how his company facilitates “a-ha” moments. He also discusses some other high level topics, including how data science building blocks come together in an application that facilitates an end user’s cognitive process.
In this interview with ODSC, Rob shares some details about Maxpoint’s new open source Python package for bayesian logistic regressions. View Rob’s talk here.