Dacheng Xiu (@dachxiu) profile picture

Dacheng Xiu

@dachxiu

Dad, Husband, Fin Econometrician, Statistician

 Chicago, IL
faculty.chicagobooth.edu/dacheng.xiu/
Joined February 2017
  • Tweets39
  • Following63
  • Followers701
R.I.P. Christopher Sims (21 Oct. 1942 - 14 March 2026) - a giant in macroeconomics and one of the finest human beings I have ever met -
Image from Markus K. Brunnermeier (@MarkusEconomist)
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📢 SoFiE Summer School 2025: Financial Machine Learning 📍 Yale SOM | July 28 – Aug 1 Deep dive into ML/AI in finance: factor models, NLP, deep learning, AI-driven asset pricing. 🔗 Apply by May 16: yalesurvey.ca1.qualtrics.com… #Finance #MachineLearning #SoFiE #AI #Econometrics
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Dacheng Xiu retweeted
NBER (@nberpubs) profile picture
NBER
@nberpubs6 Feb 2025
Some machine learning methods — like "old-school" Ridge — outperform sparsity-oriented approaches in leveraging weak signals for economic prediction, from Zhouyu Shen and @dachxiu nber.org/papers/w33421
Image from NBER (@nberpubs)
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Some machine learning models unlock economic forecasting potential, according to @ChicagoBooth PhD student Zhouyu Shen and Booth’s @dachxiu. #AI ms.spr.ly/6016WYF06
Turning Weak Signals into Strong Predictions

Turning Weak Signals into Strong Predictions

Why some machine learning models unlock economic forecasting potential.

chicagobooth.edu
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Some machine learning models unlock economic forecasting potential, according to @ChicagoBooth PhD student Zhouyu Shen and Booth’s @dachxiu. #AI ms.spr.ly/6011Wr85N
Turning Weak Signals into Strong Predictions

Turning Weak Signals into Strong Predictions

Why some machine learning models unlock economic forecasting potential.

chicagobooth.edu
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Some machine learning models unlock economic forecasting potential, according to @ChicagoBooth PhD student Zhouyu Shen and Booth’s @dachxiu. #AI ms.spr.ly/6010WRKUC
Turning Weak Signals into Strong Predictions

Turning Weak Signals into Strong Predictions

Why some machine learning models unlock economic forecasting potential.

chicagobooth.edu
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Dacheng Xiu retweeted
NBER (@nberpubs) profile picture
NBER
@nberpubs27 Oct 2024
The economic consequences of statistical learning for arbitrage pricing in a high-dimensional setting, from Rui Da, @ProfStefanNagel, and @dachxiu nber.org/papers/w33070
Image from NBER (@nberpubs)
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What does #AI see in the market that you might not? 📈 Here are 10 ways investors should be using large language models, according to research. (👇 🧵) ms.spr.ly/6010mKYpI
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ICYMI: New working paper, "Can Machines Learn Weak Signals?," by @ChicagoBooth's @dachxiu and Zhouyu Shen. ow.ly/iQ2450QLJkr
Can Machines Learn Weak Signals? | Becker Friedman Institute

Can Machines Learn Weak Signals? | Becker Friedman Institute

In high-dimensional regression scenarios with low signal-to-noise ratios, we assess the predictive performance of several machine learning algorithms. Theoretical insights show Ridge regression’s...

bfi.uchicago.edu
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In this Q&A, Chicago Booth’s @dachxiu discusses the implications of machine learning for the financial markets. ms.spr.ly/6015ifo03
In Finance, Humans Were the First Machines

In Finance, Humans Were the First Machines

A Q&A with Chicago Booth’s Dacheng Xiu on the implications of machine learning for the financial markets.

chicagobooth.edu
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#AI has been adopted across #fintech and is changing the landscape of lending, trading, valuation, etc. Join @AICenter_Booth @dachxiu @christinaqi @avinashgod and James Bray (@CapitalGroup) for a virtual discussion on 2/24 ms.spr.ly/60105TmsE
Fintech and AI: Looking Ahead

Fintech and AI: Looking Ahead

At this Booth event, hear experts discuss how AI has been adopted across the financial sector and plays an important role in FinTech.

eventbrite.com
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I just taught MBA students at Booth how to use ChatGPT to do their homework for my FinTech class. It’d be odd to discourage them from using it in a class about AI.
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How risky are your stocks, commodities, treasuries, FX, or bitcoins? We develop a robust inference procedure on volatility using transaction-level prices that are potentially contaminated by market microstructure friction econometricsociety.org/publi…
Image from Econometrica (@ecmaEditors)
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Incoming Associate Editors continued: Merih Sevilir @KelleySchool Andrea Vedolin @BUQuestrom Dacheng Xiu @dachxiu
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#SpecialIssue: Big Data in Finance Edited by Itay Goldstein, Chester S Spatt, Mao Ye #EditorsChoice: Selecting Directors Using Machine Learning by Isil Erel @FisherOSU, Léa Stern @UWFosterSchool, @ChenhaoTan @UChicago, Michael S Weisbach @FisherOSU academic.oup.com/rfs/issue/3…
Image from Society for Financial Studies (@SFSjournals)
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RFS presents a special issue on New Methods in the Cross-Section, edited by G Andrew Karolyi @CornellMBA and Stijn Van Nieuwerburgh @SVNieuwerburgh @Columbia_Biz, featuring an editor’s choice by Eugene Fama @ChicagoBooth and Kenneth French @TuckSchool academic.oup.com/rfs/issue/3…
Image from Society for Financial Studies (@SFSjournals)
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Replying to @NYGovCuomo @HealthNYGov
Statistical evidence as follows. #SocialDistancing nydailynews.com/opinion/ny-o…
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A single word in a news report—a well-placed “undervalue,” for example—can drive a company’s stock price up or down: ow.ly/cPBo50yE8ic
Image from Chicago Booth Review (@chicagoboothrev)
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Forthcoming: Empirical Asset Pricing via Machine Learning by Shihao Gu @ChicagoBooth, Bryan Kelly @YaleSOM, and Dacheng Xiu @dachxiu @ChicagoBooth academic.oup.com/rfs/advance…
Empirical Asset Pricing via Machine Learning

Empirical Asset Pricing via Machine Learning

Abstract. We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premiums

academic.oup.com
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Forthcoming soon: Feng @CityUHongKong @StefanoGiglioEc @YaleSOM and @dachxiu @ChicagoBooth develop tests of the marginal importance of an asset pricing factor relative to existing "factor zoo." They find: many recently discovered factors are redundant. doi.org/10.1111/jofi.12883
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