Irene Aldridge on Big Data's Potential Impact on Market Stability & Trader Profitability


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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

financial services.

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. None of this information is financial advice.


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186 episodes