We present an integrated proteomics platform designed for performing differential analyses. Since reproducible results are essential for comparative studies, we explain how we improved reproducibility at every step of our laboratory processes, e.g. by taking advantage of the powerful laboratory information management system we developed. The differential capacity of our platform is validated by detecting known markers in a real sample and by a spiking experiment. We introduce an innovative two-dimensional (2-D) plot for displaying identification results combined with chromatographic data. This 2-D plot is very convenient for detecting differential proteins. We also adapt standard multivariate statistical techniques to show that peptide identification scores can be used for reliable and sensitive differential studies. The interest of the protein separation approach we generally apply is justified by numerous statistics, complemented by a comparison with a simple shotgun analysis performed on a small volume sample. By introducing an automatic integration step after mass spectrometry data identification, we are able to search numerous databases systematically, including the human genome and expressed sequence tags. Finally, we explain how rigorous data processing can be combined with the work of human experts to set high quality standards, and hence obtain reliable (false positive < 0.35%) and nonredundant protein identifications.

This study extends an examination of Quality investing in the US to the Australian market. Specifically, a Quality score is computed as the aggregate of eight fundamental accounting metrics. An investment strategy investing in the highest (lowest) quality stock quintile, that is, Quintile 5 (1) generates an average annual Daniel, Grinblatt, Titman and Wermers (DGTW)-adjusted alpha of 6.37% (−7.98%), which is significant at the 5% level over April 2000-March 2010. A two-way segmentation based on size first, and quality second, reveals that the strong positive quality effect is primarily driven by small stocks, as the average DGTW-alpha for the top-quality tercile of small stocks is 14.02%, significant at the 5% level. Statistically significant positive DGTW-alphas are also determined for quality micro and large stocks. The quality analysis is also applied to a sample of Active Equity Mutual Funds' stock holdings. Weak evidence of the quality return premium is detected at the fund level.

This study investigates how the quality of stocks owned by mutual funds affects the performance of those funds during 2000-2009. The quality of a stock is positively related to its size, while quality is inversely related to volatility. Evidently, stocks in the lowest quality decile perform particularly poorly amidst volatile market conditions with a mean monthly Daniel, Grinblatt, Titman and Wermers (DGTW) alpha 1.93% [25.73% per annum (pa)] less than high-quality stocks. Furthermore, funds which hold the lowest quality stocks exhibit substantial underperformance, particularly during market downturns, with funds in the lowest decile of quality incurring a mean monthly DGTW alpha 0.96% (12.14% pa) lower than their higher quality counterparts. Interestingly, we discover a trend to funds investing in higher quality stocks over time.

This study investigates how the quality of stocks owned by mutual funds affects the performance of those funds during 2000-2009. The quality of a stock is positively related to its size, while quality is inversely related to volatility. Evidently, stocks in the lowest quality decile perform particularly poorly amidst volatile market conditions with a mean monthly Daniel, Grinblatt, Titman and Wermers (DGTW) alpha 1.93% [25.73% per annum (pa)] less than high-quality stocks. Furthermore, funds which hold the lowest quality stocks exhibit substantial underperformance, particularly during market downturns, with funds in the lowest decile of quality incurring a mean monthly DGTW alpha 0.96% (12.14% pa) lower than their higher quality counterparts. Interestingly, we discover a trend to funds investing in higher quality stocks over time.