Anomalies in the oversight of Australian auditors

This commentary identifies and comments on anomalies in the oversight of Australian auditors and audit firms. Regulatory and professional oversight and inspection of Australian auditors and audit firms arise from a number of sources, highlighting its multi-faceted nature. This makes it impossible to identify a single body with ultimate responsibility for auditor oversight. Three recent Australian reviews commissioned by the Financial Reporting Council, together with an evaluation of the roles of the various regulatory and professional bodies, are used in this commentary as a platform from which to identify a number of significant anomalies in oversight processes. Major anomalies highlighted arise from the overlapping nature of the duties and functions of the various bodies and the variation in oversight across different categories of audit service providers. Policymakers should closely examine the issues raised in the paper if auditor oversight is to be undertaken in an effective and efficient manner.

Market liquidity risk factor and financial market anomalies : evidence from the Chinese stock market

The Chinese stock market is an order-driven market and hence its characteristics are structurally different from quote-driven markets. There are no studies that consider the role of the market liquidity risk factor in determining cross-sectional stock returns in a model including financial market anomalies for order-driven markets. Our aim is to test whether financial market anomalies such as firm size, the book-to-market ratio, the turnover rate, and momentum both with and without the inclusion of the market liquidity risk factor in the case of the Chinese stock market can explain cross-sectional stock returns. The empirical framework is based on the model proposed by Avramov and Chordia (AC, 2006). Our main finding is that the AC model can capture financial market anomalies except momentum when we include the market liquidity risk factor on the Chinese stock market.

Detection of cross-channel anomalies from multiple data channels

We identify and formulate a novel problem: crosschannel anomaly detection from multiple data channels. Cross channel anomalies are common amongst the individual channel anomalies, and are often portent of significant events. Using spectral approaches, we propose a two-stage detection method: anomaly detection at a single-channel level, followed by the detection of cross-channel anomalies from the amalgamation of single channel anomalies. Our mathematical analysis shows that our method is likely to reduce the false alarm rate. We demonstrate our method in two applications: document understanding with multiple text corpora, and detection of repeated anomalies in video surveillance. The experimental results consistently demonstrate the superior performance of our method compared with related state-of-art methods, including the one-class SVM and principal component pursuit. In addition, our framework can be deployed in a decentralized manner, lending itself for large scale data stream analysis.

Firm heterogeneity and calendar anomalies

While the calendar anomalies and financial market relationship is one of the oldest relationships in financial economics, we treat this relationship differently by addressing two unknown issues: (a) Do calendar anomalies have a heterogeneous effect on firm returns and firm volatility depending on the sectoral location of firms? and (b) Do calendar anomalies affect firm returns and firm volatility differently depending on firm size? Unlike the assumption in this literature that firms are homogeneous, we show that they are in fact heterogeneous. Using 560 firms listed on the New York Stock Exchange (NYSE) over the period 5 January 2000 to 31 December 2008, we find fresh results, previously undocumented in this literature. We find evidence of calendar anomalies affecting returns and return volatility of firms differently depending on their sectoral locations and size.