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A Rational Theory of Mutual Funds' Attention Allocation

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TLDR
In this article, a new attention allocation model that uses the state of the business cycle to predict information choices, which in turn predict observable patterns of portfolio investments and returns is developed.
Abstract
The question of whether and how mutual fund managers provide valuable services for their clients motivates one of the largest literatures in finance. One candidate explanation is that funds process information about future asset values and use that information to invest in high-valued assets. But formal theories are scarce because information choice models with many assets are difficult to solve as well as difficult to test. This paper tackles both problems by developing a new attention allocation model that uses the state of the business cycle to predict information choices, which in turn, predict observable patterns of portfolio investments and returns. The predictions about fund portfolios' covariance with payoff shocks, cross-fund portfolio and return dispersion, and their excess returns are all supported by the data. These findings offer new evidence that some investment managers have skill and that attention is allocated rationally.

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Do Investors Care about Carbon Risk

TL;DR: This paper found that stocks of firms with higher total carbon dioxide emissions (and changes in emissions) earn higher returns, controlling for size, book-to-market, and other return predictors.
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Disclosure Processing Costs, Investors’ Information Choice, and Equity Market Outcomes: A Review

TL;DR: This paper reviewed the literature examining how costs of monitoring for, acquiring, and analyzing firm disclosures (collectively, "disclosure processing costs") affect investor information choices, trades, and market outcomes.
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Is Sell-side Research More Valuable in Bad Times?

Roger Loh, +1 more
- 01 Jun 2018 - 
TL;DR: In this article, the authors find that in bad times, analyst revisions have a larger stock price impact, earnings forecast errors per unit of uncertainty fall, and analyst reports are more frequent and longer.
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Big Data in Finance and the Growth of Large Firms

TL;DR: In this article, the authors explore the hypothesis that big data disproportionately benefits big firms and find that when investors can process more data, large firm investment costs fall by more, enabling large firms to grow larger.
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Do Funds Make More When They Trade More

TL;DR: This article found that active mutual funds perform better after trading more and that the time-series relation between a fund's turnover and its subsequent benchmark-adjusted return is especially strong for small, high-fee funds.
References
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Book

Elements of information theory

TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Journal ArticleDOI

Business conditions and expected returns on stocks and bonds

TL;DR: For example, this paper found that expected returns on common stocks and long-term bonds contain a term or maturity premium that has a clear business-cycle pattern (low near peaks, high near troughs).
Journal ArticleDOI

By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior

TL;DR: This paper presented a consumption-based model that explains a wide variety of dynamic asset pricing phenomena, including the procyclical variation of stock prices, the long-horizon predictability of excess stock returns, and the countercyclical variations of stock market volatility.
Journal ArticleDOI

Investor sentiment and the cross-section of stock returns

TL;DR: The authors study how investor sentiment affects the cross-section of stock returns and find that when sentiment is low, subsequent returns are relatively high for small stocks, young stocks, high volatility stocks, unprofitable stocks, non-dividend-paying stocks, extreme growth stocks, and distressed stocks.
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