Testing Market Response to Auditor Change Filings: a comparison of machine learning classifiers

The use of textual information contained in company filings with the Securities Exchange Commission (SEC), including annual reports on Form 10-K, quarterly reports on Form 10-Q, and current reports on Form 8-K, has gained the increased attention of finance and accounting researchers. In this paper we use a set of machine learning methods to predict the market response to changes in a firm\u27s auditor as reported in public filings. We vectorize the text of 8-K filings to test whether the resulting feature matrix can explain the sign of the market response to the filing. Specifically, using classification algorithms and a sample consisting of the Item 4.01 text of 8-K documents, which provides information on changes in auditors of companies that are registered with the SEC, we predict the sign of the cumulative abnormal return (CAR) around 8-K filing dates. We report the correct classification performance and time efficiency of the classification algorithms. Our results show some improvement over the naïve classification method

Acoustic Emission as a Screening Tool for Ceramic Matrix Composites

Ceramic matrix composites are composite materials with ceramic fibers in a high temperature matrix of ceramic or glass-ceramic. This emerging class of materials is viewed as enabling for efficiency improvements in many energy conversion systems. The key controlling property of ceramic matrix composites is a relatively weak interface between the matrix and the fiber that aids crack deflection and fiber pullout resulting in greatly increased toughness over monolithic ceramics. United Technologies Research Center has been investigating glass-ceramic composite systems as a tool to understand processing effects on material performance related to the performance of the weak interface. Changes in the interface have been shown to affect the mechanical performance observed in flexural testing and subsequent microstructural investigations have confirmed the performance (or lack thereof) of the interface coating. Recently, the addition of acoustic emission testing during flexural testing has aided the understanding of the characteristics of the interface and its performance. The acoustic emission onset stress changes with strength and toughness and this could be a quality tool in screening the material before further development and use. The results of testing and analysis will be shown and additional material from other ceramic matrix composite systems may be included to show trends

Consolidating information in option transactions

Underlying each stock trades hundreds of options at different strike prices and maturities. The order flow from these option transactions reveals important information about the underlying stock price movement and its volatility. How to aggregate the trade information of different option contracts underlying the same stock presents an interesting and important question for developing microstructure theories and price dis-covery mechanisms in the derivatives markets. This paper takes options on QQQQ, the Nasdaq 100 tracking stock, as an example and examines different order flow consolidation schemes in terms of their effectiveness in extracting information about the underlying stock price and volatility movements. The analysis shows that an effective consolidation scheme shall account for both the liquidity of each option contract and the contract’s particular exposure to stock price and volatility movements. Based on our proposed consolida-tion scheme, we identify significant relations between the appropriately aggregated options order flows and the ex post stock returns and return volatilities. In particular, the aggregated stock buy pressure positively predicts future stock returns and the aggregated volatility buy pressure positively predicts future changes in return volatilities up to five minutes. JEL Classification: G14, G12, G13

Modeling Market Reactions to Auditor Changes Using Variable Selection Algorithms: A Meta-Analysis

Market reactions to auditor change filings have been studied over a long period in the literature. We provide a review of the literature on market response to auditor changes and identify a superset of variables used in published research. Applying methods from machine learning to optimize variable selection, we build models that explain market reaction to auditor changes. We compare the performance of our models with the performance of the models that use subsets of variables examined in a select list of studies in the literature. Our meta-analysis results in an improvement in model fit compared to the analysis used in prior studies

Whole Cell Cryo-Electron Tomography Reveals Distinct Disassembly Intermediates of Vaccinia Virus

At each round of infection, viruses fall apart to release their genome for replication, and then reassemble into stable particles within the same host cell. For most viruses, the structural details that underlie these disassembly and assembly reactions are poorly understood. Cryo-electron tomography (cryo-ET), a unique method to investigate large and asymmetric structures at the near molecular resolution, was previously used to study the complex structure of vaccinia virus (VV). Here we study the disassembly of VV by cryo-ET on intact, rapidly frozen, mammalian cells, infected for up to 60 minutes. Binding to the cell surface induced distinct structural rearrangements of the core, such as a shape change, the rearrangement of its surface spikes and de-condensation of the viral DNA. We propose that the cell surface induced changes, in particular the decondensation of the viral genome, are a prerequisite for the subsequent release of the vaccinia DNA into the cytoplasm, which is followed by its cytoplasmic replication. Generally, this is the first study that employs whole cell cryo-ET to address structural details of pathogen-host cell interaction