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Day of the Week and the Cross-Section of Returns

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TLDR
This paper found that long short anomaly returns are strongly related to the day of the week and that mood increases from Thursday to Friday and decreases on Monday, while the exact opposite pattern is observed on Fridays.
Abstract
This paper documents a new empirical fact. Long-short anomaly returns are strongly related to the day of the week. Anomalies for which the speculative leg is the short (long) leg experience the highest (lowest) strategy returns on Monday. The exact opposite pattern is observed on Fridays. The effects are large; Monday (Friday) alone accounts for over 100% of monthly returns for all anomalies examined for which the short (long) leg is the speculative leg. Consistent with a mispricing explanation, the pattern is fully driven by the speculative leg of the strategy. The observed patterns are consistent with the abundance of evidence in the psychology literature documenting that mood increases from Thursday to Friday and decreases on Monday.

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Anomalies and News

TL;DR: This article found that stock return anomalies are 50% higher on corporate news days and six times higher on earnings announcement days and that these results could be explained by dynamic risk, mispricing due to biased expectations, or data mining.
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Mood Betas and Seasonalities in Stock Returns

TL;DR: In this paper, the authors hypothesize that assets' different sensitivities to investor mood explain the cross-sectional seasonality of stock returns and imply other seasonalities, such as the periodic outperformance of certain stocks during the same calendar months or weekdays.
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Bitcoin time-of-day, day-of-week and month-of-year effects in returns and trading volume

TL;DR: In this paper, the authors report intra-day time-of-day, day-ofweek, and month-ofyear effects for Bitcoin returns and trading volume using more than 15 million observations from seven global and continuously-traded Bitcoin exchanges.
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The cross-section of intraday and overnight returns

TL;DR: The authors investigate cross-sectional variation in stock returns over the trading day and overnight to shed light on what drives asset pricing anomalies, finding that a mispricing factor earns positive returns throughout the day but performs poorly at the end of the day.
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Recurring Firm Events and Predictable Returns: The Within-Firm Time Series

TL;DR: This article reviewed the literature on recurring firm events and predictable returns and found that common firm events recur on a predictable basis and that these events tend to be associated with large positive returns in the period when the events are predicted to occur (without conditioning on the outcome or existence of the event itself).
References
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Journal ArticleDOI

Risk, Return, and Equilibrium: Empirical Tests

TL;DR: In this article, the relationship between average return and risk for New York Stock Exchange common stocks was tested using a two-parameter portfolio model and models of market equilibrium derived from the two parameter portfolio model.
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The relationship between return and market value of common stocks

TL;DR: Scholes et al. as discussed by the authors examined the relationship between the total market value of the common stock of a firm and its return and found that small firms had higher risk adjusted returns than large firms.
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Illiquidity and Stock Returns: Cross-Section and Time-Series Effects

TL;DR: In this paper, the effects of stock illiquidity on stock return have been investigated and it was shown that expected market illiquidities positively affects ex ante stock excess return (usually called risk premium) over time.
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Financial ratios and the probabilistic prediction of bankruptcy

TL;DR: In this paper, the authors present some empirical results of a study predicting corporate failure as evidenced by the event of bankruptcy, and the methodology is one of maximum likelihood estimation of the so-called conditional logit model, in which the data set used in this study is from the seventies (1970-76).
Posted Content

Contrarian Investment, Extrapolation, and Risk

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