Related papers: Publication Bias in Asset Pricing Research
The mainstream media has much leeway in what it chooses to cover and how it covers it. These choices have real-world consequences on what people know and their subsequent behaviors. However, the lack of objective measures to evaluate…
In this paper, we address one of the main puzzles in finance observed in the stock market by proponents of behavioral finance: the stock predictability puzzle. We offer a statistical model within the context of rational finance which can be…
Recent research has found that select scientists have a disproportional share of highly cited papers. Researchers reasoned that this could not have happened if success in science was random and introduced a hidden parameter Q, or talent, to…
Cross-sectional dispersion in firm-level realized skewness is significantly and negatively related to future stock market returns. The predictive power of skewness dispersion is robust to in-sample and out-of-sample estimation and is…
Open science is increasingly recognised worldwide, with preprint posting emerging as a key strategy. This study explores the factors influencing researchers' adoption of preprint publication, particularly the perceived effectiveness of this…
Experiments suggest that people fail to take into account interdependencies between their choices -- they do not broadly bracket. Researchers often instead assume that people narrowly bracket, but existing designs do not test it. We design…
The distribution of scientific citations for publications selected with different rules (author, topic, institution, country, journal, etc.) collapse on a single curve if one plots the citations relative to their mean value. We find that…
The statistics community, which has traditionally lacked a transparent and open peer-review system, faces a challenge of inconsistent paper quality, with some published work containing substantial errors. This problem resonates with…
Academic and scientific publishing practices have changed significantly in recent years. This paper presents an analysis of 17 million research papers published since 2000 to explore changes in authorship and content practices. It shows a…
Social learning is a fundamental mechanism shaping decision-making across numerous social networks, including social trading platforms. In those platforms, investors combine traditional investing with copying the behavior of others.…
Despite their prevalence in society, social biases are difficult to identify, primarily because human judgements in this domain can be unreliable. We take an unsupervised approach to identifying gender bias against women at a comment level…
The sudden appearance of modern machine learning (ML) phenomena like double descent and benign overfitting may leave many classically trained statisticians feeling uneasy -- these phenomena appear to go against the very core of statistical…
Advances in AI, and especially machine learning, are increasingly drawing research interest and efforts towards predictive process monitoring, the subfield of process mining (PM) that concerns predicting next events, process outcomes and…
CONTEXT: There is growing interest in establishing software engineering as an evidence-based discipline. To that end, replication is often used to gain confidence in empirical findings, as opposed to reproduction where the goal is showing…
Using frequency distributions of daily closing price time series of several financial market indexes, we investigate whether the bias away from an equiprobable sequence distribution found in the data, predicted by algorithmic information…
Online marketplace designers frequently run A/B tests to measure the impact of proposed product changes. However, given that marketplaces are inherently connected, total average treatment effect estimates obtained through Bernoulli…
Collaborative filtering algorithms have the advantage of not requiring sensitive user or item information to provide recommendations. However, they still suffer from fairness related issues, like popularity bias. In this work, we argue that…
In this paper, we examine the biases that arise when firms run A/B tests on continuous parameters to estimate global treatment effects on performance metrics of interest; we particularly focus on price experiments to measure the price…
In the information-based approach to asset pricing the market filtration is modelled explicitly as a superposition of signals concerning relevant market factors and independent noise. The rate at which the signal is revealed to the market…
The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of…