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Stock Return Predictability and the Adaptive Markets Hypothesis: Evidence from Century Long U.S. Data

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TLDR
This article studied the return predictability of the Dow Jones Industrial Average indices from 1900 to 2009 and found strong evidence that time-varying return prediction is driven by changing market conditions, consistent with the implications of the adaptive markets hypothesis.
Abstract
We study return predictability of the Dow Jones Industrial Average indices from 1900 to 2009. We find strong evidence that time-varying return predictability is driven by changing market conditions, consistent with the implications of the adaptive markets hypothesis. During market crashes, no return predictability is observed, but an extreme degree of uncertainty is associated with return predictability. During fundamental economic or political crises, stock returns have been highly predictable with a moderate degree of uncertainty. During economic bubbles, return predictability and its uncertainty have been smaller than normal times.

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Citations
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Deep learning networks for stock market analysis and prediction

TL;DR: A systematic analysis of the use of deep learning networks for stock market analysis and prediction using five-minute intraday data from the Korean KOSPI stock market as input data to examine the effects of three unsupervised feature extraction methods.
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The inefficiency of Bitcoin revisited: A dynamic approach

TL;DR: In this paper, the authors revisited the informational efficiency of the Bitcoin market and analyzed the time-varying behavior of long memory of returns on Bitcoin and volatility 2011 until 2017, using the Hurst exponent.
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Genetic algorithm-optimized long short-term memory network for stock market prediction

TL;DR: This research investigates the temporal property of stock market data by suggesting a systematic method to determine the time window size and topology for the LSTM network using GA.
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Efficient or adaptive markets? Evidence from major stock markets using very long run historic data

TL;DR: In this paper, the authors empirically investigated the Adaptive Market Hypothesis (AMH) in three of the most established stock markets in the world; the US, UK and Japanese markets using very long run data.
References
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Journal ArticleDOI

Efficient capital markets: a review of theory and empirical work*

Eugene F. Fama
- 01 May 1970 - 
TL;DR: Efficient Capital Markets: A Review of Theory and Empirical Work Author(s): Eugene Fama Source: The Journal of Finance, Vol. 25, No. 2, Papers and Proceedings of the Twenty-Eighth Annual Meeting of the American Finance Association New York, N.Y. December, 28-30, 1969 (May, 1970), pp. 383-417 as mentioned in this paper
Journal ArticleDOI

A Behavioral Model of Rational Choice

TL;DR: In this article, a model for the description of rational choice by organisms of limited computational ability is proposed, and the model is used to describe rational choice in organisms with limited computational abilities.
Journal ArticleDOI

Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency

TL;DR: In this article, the authors show that strategies that buy stocks that have performed well in the past and sell stocks that had performed poorly in past years generate significant positive returns over 3- to 12-month holding periods.
Journal ArticleDOI

The behavior of stock market prices

Book

The econometrics of financial markets

TL;DR: In this paper, Campbell, Lo, and MacKinlay present an attempt by three well-known and well-respected scholars to fill an acknowledged void in the empirical finance literature, a text covering the burgeoning field of empirical finance.
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