Irene Aldridge joins us to discuss how Big Data can have an impact on the market stability and trader profitability.
Irene Aldridge is a co-author of “Big Data Science in Finance” (with
Marco Avellaneda, Wiley 2020), an internationally-recognized
quantitative and Big Data Finance researcher, Adjunct Professor at
Cornell University and President and Managing Director, Research, of
AbleMarkets, a Big Data for Capital Markets company. She was named to
the Forbes’ Top 40-Over-40 Women’s List in 2017. Prior to AbleMarkets,
Aldridge designed and ran high-frequency trading strategies in a
$20-million cross-asset portfolio. Still previously, Aldridge was, in
reverse order, a quant on a trading floor; in charge of risk
quantification of commercial loans; Basel regulation team lead;
technology equities researcher; lead systems architect on large
integration projects, including web security and trading floor
globalization. Aldridge started her career as software engineer in
Aldridge holds a BE in Electrical Engineering from Cooper Union, and MS
in Financial Engineering from Columbia University, and an MBA from
INSEAD. In addition, Aldridge studied in two PhD programs: Operations
Research at Columbia University (ABD) and FInance (ABD). Aldridge is the
author of multiple academic papers and several books. Most notable
titles include “Big Data Science in Finance” (co-authored with Marco
Avellaneda, Wiley, 2020), “Real-Time Risk: What Investors Should Know
About Fintech, High-Frequency Trading, Flash Crashes” (co-authored with
Steve Krawciw, Wiley, 2017), “High-Frequency Trading: A Practical Guide
to Algorithmic Strategies and Trading Systems” (2nd edition, translated
into Chinese, Wiley 2013), and “The Quant Investor’s Almanac 2011: A
Road Map to Investing” (Wiley, 2010). Her recent academic publications
include “Neural Networks in Finance: Design and Performance” (with Marco
Avellaneda in the Journal of Financial Data Science, 2019), “Big Data in
Portfolio Management” (Journal of Financial Data Science, 2019), “ETFs,
High-Frequency Trading and Flash Crashes” (Journal of Portfolio
Management, 2016), and “High-Frequency Runs and Flash Crash
Predictability” (Journal of Portfolio Management, 2014). Aldridge
presently serves on the Editorial Advisory Board for the Journal of
Applied Data Science to Finance.
View this episode on our website here.
*Disclaimer. Richard Carthon is the Founder of Crypto Current. All opinions expressed by members of the Crypto Current Team, Richard or his guest on this podcast are solely their opinions and do not reflect the opinions of Crypto Current. You should not treat any opinion expressed by Richard as a specific inducement to make a particular investment or follow a particular strategy but only as an expression of his opinion. This podcast is for informational purposes only.
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