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Machine Learning Versus Economic Restrictions: Evidence from Stock Return Predictability · Study

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PreprintMachine Learning Versus Economic Restrictions: Evidence from Stock Return Predictability

Doron Avramov2019

OA

Preprintgreen2019

Machine Learning Versus Economic Restrictions: Evidence from Stock Return Predictability

Doron Avramov · Si Cheng · Lior Metzker

74 citations·0/0 files stored·SSRN Electronic Journal

No readable copy stored yet — this record is metadata only.

Financial Markets and Investment Strategies Financial Analysis and Corporate Governance Stock Market Forecasting Methods

Abstract

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Citations in this library

Stored only when both papers are in the corpus — 74 citations exist upstream.

References

1993Common risk factors in the returns on stocks and bonds 1997On Persistence in Mutual Fund Performance 1973Risk, Return, and Equilibrium: Empirical Tests 2002Illiquidity and stock returns: cross-section and time-series effects 2014A five-factor asset pricing model 2003Liquidity Risk and Expected Stock Returns 2008Market Liquidity and Funding Liquidity 2007A Comprehensive Look at The Empirical Performance of Equity Premium Prediction

Cited by

2020Does it pay to follow anomalies research? Machine learning approach with international evidence 2022Machine Learning Goes Global: Cross-Sectional Return Predictability in International Stock Markets 2022Asset Pricing and Machine Learning: A critical review 2022Enhancing stock market anomalies with machine learning 2021The Promises and Pitfalls of Machine Learning for Predicting Stock Returns

Details

Year2019

Typepreprint

Published2019-01-01

VenueSSRN Electronic Journal

ISSN-L1556-5068

Languageen

Citations74

Files0 public / 0

ShelfFinancial Markets and Investment Strategies

Identifiers

doi10.2139/ssrn.3450322

openalex_workW2980306936

Links

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