This paper reviews the literature examining how costs of monitoring for, acquiring, and
analyzing firm disclosures–collectively,“disclosure processing costs”–affect investor …

Researchers have various ways to measure liquidity but most of them come with both merits
and demerits. This study provides a literature review of low‐frequency liquidity measures …

We use deep neural networks to estimate an asset pricing model for individual stock returns
that takes advantage of the vast amount of conditioning information, keeps a fully flexible …

We propose a nonparametric method to study which characteristics provide incremental
information for the cross-section of expected returns. We use the adaptive group LASSO to …

Unprecedented non-pharmaceutical interventions targeted to curb the spread of COVID-19
exerted a dramatic impact on the global economy and financial markets. This study is the …

We find that social capital, as captured by secular norms and social networks surrounding
corporate headquarters, is negatively associated with levels of CEO compensation. This …

We propose a new method to estimate the bid-ask spread when quote data are not
available. Compared to other low-frequency estimates, this method utilizes a wider …

Liquidity plays an important role in global research. We identify high-quality liquidity proxies
based on low-frequency (daily) data, which provide 1,000× to 10,000× computational …

Purpose This paper aims to explore the influence of the COVID-19 outbreak and the
Government's disease control measures on the stock returns and liquidity of Vietnam-listed …

We use the search volume index (SVI) of the stock ticker provided by Google Trends to
capture the active attention that retail investors pay to stocks. Based on the analysis of S&P …