Experts in Vega’s data science and statistics expert network apply empirical methods to complex datasets. The Vega team has vast experience managing large-scale datasets consisting of both structured and unstructured data. By developing rigorous, client-focused solutions, the Vega team helps our clients achieve superior results.

Statistical Analysis & Sampling

Vega develops and implements empirical analyses to answer our client’s economic and financial questions. We rely on flexible, robust, and defensible statistical techniques to address a wide range of issues including sampling, simulation, survival analysis, and other statistical techniques.

Big Data Management

Vega regularly works with large volumes of data. Our staff and in-house infrastructure have the capabilities to build, maintain, update, and most importantly, leverage extensive data to meet client needs. Our expertise enables us to conduct efficient and informative analytics. Our team is skilled at processing, normalizing, and enriching data. We also have experience maintaining datasets with billions of observations spanning many years. 

Web Scraping and Data Collection

Vega researches and collects large amounts of publicly available data. Drawing on our experience and creativity, we perform focused searches to identify and gather relevant and informative data unique to each engagement. Our team uses proprietary tools to scrape and compile custom datasets that address the needs of every client.

Text & Sentiment Analysis

Our team has experience analyzing and interpreting extracted text using sentiment analyses. We are able to build algorithms to classify millions of pages of documents and use proprietary tools to identify, categorize, index, and compile relevant documents based on content. In several engagements, Vega economists have also employed modern sentiment analysis.

Data Visualization

The Vega team creates intuitive, aesthetic, and compelling visualizations. Utilizing our programmatic dexterity, we make complex concepts accessible to all audiences. Our team is also able to streamline revisions and ensure consistency in visualizations by automating the generation process.

Artificial Intelligence (AI) & Machine Learning (ML)

Vega uses cutting edge AI and ML technology to guide data-driven analyses. By using complex state-of-the-art data science methods, we are able to process and analyze large volumes of complex information while reducing subjectivity and error. Our approach allows us to automate complex tasks and customize analysis of large datasets.

Below is a list of example engagements for our Data Science & Statistics practice:

Daniel Bauer

Hickman-Larson Chair in Actuarial Science and Associate Professor of Risk and Insurance at Wisconsin School of Business, University of Wisconsin-Madison

  • Data Science & Statistics
  • Insurance & Risk
Rajeev Bhattacharya

Visiting Professor of Finance in the Cox School of Business at SMU

  • Securities & Finance
  • Data Science & Statistics
  • Antitrust & Competition
  • Valuation
Mark J. Browne

Robert Clements Distinguished Chair in Risk Management and Insurance, Tobin College of Business at St. John's University

  • Data Science & Statistics
  • Insurance & Risk
Daphne Chen

Managing Director

  • Securities & Finance
  • Consumer Finance
  • Data Science & Statistics
Ethan Cohen-Cole

Senior Advisor at Vega Economics

  • Securities & Finance
  • Data Science & Statistics
  • Financial Institutions
  • Valuation
  • Consumer Finance
  • Healthcare & Health Economics
Frederico Finan

Associate Professor at the University of California, Berkeley

  • Data Science & Statistics
Timothy C. Haab

Dean's Chair for Transformative Initiatives and Professor and Chair of Agricultural, Environmental, and Development Economics at Ohio State University

  • Agriculture
  • Energy & Environmental Economics
  • Valuation
  • Data Science & Statistics
Paul Hanouna

Associate Professor in the Department of Finance of the Villanova School of Business at Villanova University

  • Corporate Finance
  • Securities & Finance
  • Data Science & Statistics
  • Financial Institutions
  • Real Estate
  • Antitrust & Competition
Haim Kassa

Associate Professor of Finance at the Farmer School of Business, Miami University

  • Securities & Finance
  • Data Science & Statistics
  • Financial Institutions
  • Antitrust & Competition
  • Valuation
Richard Libby

Founding Director, Perihelion Capital Advisors

  • Corporate Finance
  • Data Science & Statistics
  • Financial Institutions
Xiaodong Liu

Associate Professor in the Department of Economics, University of Colorado, Boulder

  • Data Science & Statistics
Cecilia Mo

Assistant Professor of Political Science at University of California, Berkeley

  • Data Science & Statistics
Michael A. Sadler

Senior lecturer in the Department of Finance and the Department of Economics at the McCombs School of Business at University of Texas at Austin

  • Data Science & Statistics
  • Valuation
  • Energy & Environmental Economics
Shu Shen

Associate Professor in the Department of Economics, University of California, Davis

  • Data Science & Statistics
  • Labor & Employment
Wei Tan

Managing Director at Mingde Economic Research Inc. and an Adjunct Professor at Johns Hopkins University

  • Data Science & Statistics
  • Antitrust & Competition
  • Valuation
Jay Vadiveloo

Professor at the University of Connecticut and Director of the Janet & Mark L Goldenson Center for Actuarial Research at the University of Connecticut

  • Data Science & Statistics
  • Insurance & Risk
October 22, 2021 | Expertise
Survey Implementation and Administration Capacities

Vega Economics is well-equipped with the capabilities and experience to efficiently assist our experts in designing and implementing surveys to reliably address the distinct issues in each case. Check out our Survey Implementation and Administration Capacities brochure to learn more about how the Vega team and experts approach surveys.

July 16, 2021 | Article
The Importance of Expert Economists in Spoofing Litigation

Regulatory and enforcement agencies, market exchanges, and at least one private party have brought legal actions for alleged spoofing in futures markets. To meet applicable standards of proof, attorneys are increasingly turning to expert testimony regarding statistics and econometrics to prove and refute spoofing allegations in litigation.

May 7, 2021 | Featured Expert
Dr. Haim Kassa, Associate Professor of Finance at the Farmer School of Business, Miami University

Our featured expert, Haim Kassa, is is an expert in the areas of investments and portfolio management and he is experienced in the design and testing of trading strategies using historical firm level data from the stock, bond, and option markets.

February 17, 2021 | Brochure
Data Analytics Capacities and Practices

To facilitate the most impactful analyses with big data, one needs more than powerful computers and fancy data tools. Check out Vega's Data Analytics capacities about how we are better at categorizing data, identifying gaps in data, troubleshooting, as well reading data and data results.

December 14, 2020 | Expertise
In the Spotlight: Collection and Visualization of Securities Data

Using proprietary tools, Vega creates customized datasets from a range of sources and deliver our analyses with clear and informative visualizations. To illustrate the automated tool we developed we highlight three example visualizations that we periodically update using our automated data tools.

December 3, 2020 | Article
Predicting Consumers' Choices in the Age of the Internet, AI, and Almost Perfect Tracking: Some Things Change, the Key Challenges Do Not

Vega expert Professor David Gal provides insight into the limits of artificial intelligence, machine learning, and big data, as well as those of traditional survey and experimental methods, in predicting consumer choices.