Our webinars will boost your expertise in the latest trends in the industry and share insight into the FDP charter.
Data Supply Chain Management is the collection, organization, flow and streamlining of data – including any pre-processing and normalization steps - to make it usable, guided by domain knowledge, for the next downstream process. Typically, this next step involves analysis via traditional statistical or contemporary machine learning tools. The end goal of the exercise is to generate insights that can imply customer value, inform revenue or pricing metrics, optimize costs and help gain a competitive advantage in the marketplace.
In particular, this webinar will discuss:
Rick Roche, CAIA
Discover the latest trends in quantitative model development. AI and Machine Learning in Investment Management is an insider’s look into the opaque world of quantitative investing and the emergence of Artificial Intelligence, Big and small Data.
Roche will separate fact from fiction and hype from reality. Learn how asset managers are deploying algorithms and advanced statistical modeling to classify and monetize varied and differentiated sources of potential alpha. Although quants have not taken over Wall Street (not yet, anyway), the audience will be surprised to hear just how widespread automated trading systems (ATS) and algorithmic investing are being deployed in today’s equity markets.
Roche reveals some of the largest practitioners of quantitative investment management and emerging players in the quant investing space. Increasingly, asset managers are combining human and machine intelligence in the investment decision-making process. There’s a virtual arms race fueled by 1,000+ alternative data set and tech vendors frantically hiring data scientists, computer engineers and math PhDs. No previous experience required!
In 2019, the CFA Institute addressed emerging FinTech applications by requiring exam takers to have a basic understanding of artificial intelligence, big data and robo-advisory algorithms.
“CFA Exam to Add Big Data, Artificial Intelligence as Topics”, Bloomberg, 5/9/17
Webinar Recordings & Slide Decks
A conversation with ... George Mussali & Mike Chen
Date: April 1, 2020
Description: ESG investing is an area of active interest for both the investment and academic communities. Despite the intense interest, there currently is no agreed upon definition of ESG investing, or how to best build investment portfolios that incorporate both return and sustainability dimensions. (Both are important for sustainability-minded investors.) In this article, the authors categorize the broad types of ESG investing currently in the market and introduce an ESG investment framework. This results in a portfolio that optimally combines the dual objectives of alpha and sustainability outperformance. TOPICS: Portfolio theory, portfolio construction, ESG investing
A Conversation with ... Michael Oliver Weinberg and Peter Strikwerda
Title: Usage of Alternative Data and ML in Asset Classes
Date: March 25th, 2020
A Conversation with ... Tony Guida
Date: March 5, 2020
Description: Tony Guida co-wrote and edited the book "Big Data and Machine Learning in Quantitative Investment", one of the required readings for the upcoming exam. This webinar is titled "Long Term Machine Learning Predictions for US equity" and is a user case study of Chapter 7 of the book which Tony co-wrote with Guillaume Coqueret.
Tony Guida works together with the equity Portfolio Managers to develop systematic investment strategies. Tony’s work is focused primarily on extracting market inefficiencies from different sources from traditional fundamentals, market signals, alternative data, and machine learning. His expertise is in mid to low frequency in equities. ony started his career at Unigestion in 2006 where he joined the quantitative equity low volatility team to work as a research analyst. He evolved into a member of the research and investment committee for Minimum Variance Strategies, where he led the factor investing research group for institutional clients. In 2015, he moved to Edhec Risk Scientific Beta as a Senior Consultant for Risk allocation and factor strategies before going to a major UK pension fund in 2016 to build the in-house systematic equity, co-managing 6 billion GBP as a senior quantitative portfolio manager. He joined RAM-Active Investments in January 2019. Tony is editor-in-chief for the Journal of Machine Learning in Finance and he is chair of the EMEA machineByte Think Tank.
A Conversation with ... Joe Simonian
Date: February 27, 2020
Description: Joe Simonian is the founder and CIO at Autonomous Investment Technologies, LLC, as well as the co-editor of The Journal of Financial Data Science.
Previously Joe held the role of Senior Investment Strategist at Acadian Asset Management and Director of Quantitative Research at Natixis Investment Managers, where he led the quantitative research and portfolio strategy for the Portfolio Research and Consulting Group. He is also a member of the investment oversight committee. Prior to working at Natixis, Joseph was the Principal Research Analyst at Global Institutional Solutions. He was also the Vice President of Portfolio Management at J.P. Morgan and PIMCO. Joseph gained his PhD from University of California, Santa Barbara, MA from Columbia University, New York, and BA from University of California, Los Angeles. He has been widely published in leading industry journals and is the co-editor of the Journal of Financial Data Science.
A Conversation with ... Seoyoung Kim
Date: February 19, 2020
Description: Dr. Seoyoung Kim is a Professor of Business Analytics at Santa Clara University and co-author of "Zero-Revelation RegTech: Detecting Risk through Linguistic Analysis of Corporate Emails and Newsl"
Natural language processing is a fast-growing area of data science for the finance industry. Recent advances in financial technology (FinTech) have dramatically transformed the financial landscape with respect to the way we access, invest, and transfer financial capital. In this article, the authors explore a promising avenue for the use of natural-language processing in an effective yet non-invasive method by which to monitor the health and integrity of financial institutions and corporations in general by analyzing corporate emails and news.
A Conversation with ... Gene Getman
Date: January 29, 2020
Description: Gene Getman is a Client Portfolio Manager for the 1798 Alternatives group, focused on Investor Relations for the Hedge Fund business. He is the Product Specialist for the 1798 Q Strategy and other innovative or capacity constrained alternative investment strategies based in New York. More importantly: Gene is the co-author of "Big Data is a Big Deal: An investor’s guide to the applications and challenges of alternative data" Note: The "Big Data" paper is a required reading for the March 2020 exam.
A Conversation With ... Guen Dondé
Description: Our conversation with Guen Dondé, head of Research at the Institute of Business Ethics. Co-researcher of "IBE Ethics at Work" and "Implications of AI on Business Ethics". Thought provoking, engaging, and great learning overall! Note: three readings on the March 2020 exam were discussed during this webinar.
Panelists: Guen Dondé, Kathryn Wilkens, Sr. Advisor FDP Institute, Mehrzad Mahdavi, Executive Director, FDP Institute,
FDPI Candidate Orientation for the March 2020 Exam
Description: This webinar features members of the FDP Curriculum Team as well as Candidate Relations. The following topics are discussed: Curriculum materials, exam format, and available resources. For each topic we discussed the required readings, keywords, learning objectives and sample questions.
Panelists: Mehrzad Mahdavi, Executive Director, FDP Institute, Hossein Kazemi, Sr. Advisor FDP Institute, Keith Black, Managing Director Content Strategy CAIA.