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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 \u201cBig Data Science in Finance\u201d (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\u2019 Top 40-Over-40 Women\u2019s 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 \u201cBig Data Science in Finance\u201d (co-authored with Marco

Avellaneda, Wiley, 2020), \u201cReal-Time Risk: What Investors Should Know

About Fintech, High-Frequency Trading, Flash Crashes\u201d (co-authored with

Steve Krawciw, Wiley, 2017), \u201cHigh-Frequency Trading: A Practical Guide

to Algorithmic Strategies and Trading Systems\u201d (2nd edition, translated

into Chinese, Wiley 2013), and \u201cThe Quant Investor\u2019s Almanac 2011: A

Road Map to Investing\u201d (Wiley, 2010). Her recent academic publications

include \u201cNeural Networks in Finance: Design and Performance\u201d (with Marco

Avellaneda in the Journal of Financial Data Science, 2019), \u201cBig Data in

Portfolio Management\u201d (Journal of Financial Data Science, 2019), \u201cETFs,

High-Frequency Trading and Flash Crashes\u201d (Journal of Portfolio

Management, 2016), and \u201cHigh-Frequency Runs and Flash Crash

Predictability\u201d (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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