Key Features:Presents novel papers and a different outlook on microstructureUnique in bringing together contributions from the leading authors in the fieldComprehensive coverage of a broad range of diversified subtopicsScholarly book for academicians, regulators, policy makers and practitioners...

Mark-to-market accounting, as required by FAS No. 157, has been implicated as a contributor to the financial meltdown caused by the housing crisis and the consequent write-down of securities backed by mortgages (MBS) and collateralized debt obligations (CDO). In this paper, we investigate the...

Market microstructure is the study of how markets operate and how transaction dynamics can affect security price formation and behavior. The impact of microstructure on all areas of finance has been increasingly apparent. Empirical microstructure has opened the door for improved transaction cost...

We develop novel machine learning algorithms to construct metrics of visual readability in firms' annual reports. Firms increase their use of imagery content when there is more news coverage and greater asset growth during the year. Consistent with improvements in the information environment, an...

Trade signing algorithms that rely on quote data, tick data or both have been used extensively to assign a trade as either a buy or a sell. Leveraging the availability of a large panel of signed trade data in the corporate bond market, we explore machine learning methods to uncover a new trade...

We develop a novel approach to identify characteristics of images that are likely to, and found to, affect investment decisions. We also create new methodologies to quantify these characteristics. We hypothesize and find that our newly developed machine learning-based measure of...

We develop a novel approach to identify characteristics of images that are likely to, and found to, affect investment decisions. We also create new methodologies to quantify these characteristics. We hypothesize and find that our newly developed machine learning-based measure of...

Leveraging the availability of a large panel of signed trade data in the corporate bond market,we explore how machine learning methods can be used to improve upon standard tradedirection classification methods in markets in general, both with and without pre-trade transparency.Using the signed...

This study explores how the ethnicity of small business owners affects the influences of family ownership on their willingness to borrow. While the willingness issue is fundamental in the literature on small business debt financing, it has been understudied. We introduce an indirect measure of...