New variational Bayesian approaches for statistical data mining : with applications to profiling and differentiating habitual consumption behaviour of customers in the wireless telecommunication industry

This thesis investigates profiling and differentiating customers through the use of statistical data mining techniques. The business application of our work centres on examining individuals’ seldomly studied yet critical consumption behaviour over an extensive time period within the context of the wireless telecommunication industry; consumption behaviour (as oppose to purchasing behaviour) is behaviour that has been performed so frequently that it become habitual and involves minimal intentions or decision making. Key variables investigated are the activity initialised timestamp and cell tower location as well as the activity type and usage quantity (e.g., voice call with duration in seconds); and the research focuses are on customers’ spatial and temporal usage behaviour. The main methodological emphasis is on the development of clustering models based on Gaussian mixture models (GMMs) which are fitted with the use of the recently developed variational Bayesian (VB) method. VB is an efficient deterministic alternative to the popular but computationally demandingMarkov chainMonte Carlo (MCMC) methods. The standard VBGMMalgorithm is extended by allowing component splitting such that it is robust to initial parameter choices and can automatically and efficiently determine the number of components. The new algorithm we propose allows more effective modelling of individuals’ highly heterogeneous and spiky spatial usage behaviour, or more generally human mobility patterns; the term spiky describes data patterns with large areas of low probability mixed with small areas of high probability. Customers are then characterised and segmented based on the fitted GMM which corresponds to how each of them uses the products/services spatially in their daily lives; this is essentially their likely lifestyle and occupational traits. Other significant research contributions include fitting GMMs using VB to circular data i.e., the temporal usage behaviour, and developing clustering algorithms suitable for high dimensional data based on the use of VB-GMM.

A longitudinal study of corporate earnings guidance in Australia’s continuous disclosure environment

Since the introduction of a statutory‐backed continuous disclosure regime (CDR) in 1994, regulatory reforms have significantly increased litigation risk in Australia for failure to disclose material information or for false and misleading disclosure. However, there is almost no empirical research on the impact of the reforms on corporate disclosure behaviour. Motivated by the absence of research and using management earnings forecasts (MEFs) as a disclosure proxy, this study examines (1) why managers issue earnings forecasts, (2) what firm‐specific factors influence MEF characteristics, and (3) how MEF behaviour changes as litigation risk increases. Based on theories in information economics, a theoretical framework for MEF behaviour is formulated which includes antecedent influencing factors related to firms‟ internal and external environments. Applying this framework, hypotheses are developed and tested using multivariate models and a large sample of hand-collected MEFs (7,213) issued by top 500 ASX-listed companies over the 1994 to 2008 period. The results reveal strong support for the hypotheses. First, MEFs are issued to reduce information asymmetry, litigation risk and signal superior performance. Second, firms with better financial performance, smaller earnings changes, and lower operating uncertainty provide better quality MEFs. Third, forecast frequency and quality (accuracy, timeliness and precision) noticeably improve as litigation risk increases. However, managers appear to be still reluctant to disclose earnings forecasts when there are large earnings changes, and an asymmetric treatment of news type continues to prevail (a good news bias). Thus, the findings generally provide support for the effectiveness of the CDR regulatory reforms in improving disclosure behaviour and will be valuable to market participants and corporate regulators in understanding the implications of management forecasting decisions and areas for further improvement.

Two monoclonal antibodies to precisely the same epitope of type ii collagen select non-crossreactive phage clones by phage display: Implications for autoimmunity and molecular mimicry

Two monoclonal antibodies (mAb) CB268 and CII-C1 to type II collagen (CII) react with precisely the same conformational epitope constituted by the residues ARGLT on the three chains of the CII triple helix. The antibodies share structural similarity, with most differences in the complementarity determining region 3 of the heavy chain (HCDR3). The fine reactivity of these mAbs was investigated by screening two nonameric phage-displayed random peptide libraries. For each mAb, there were phage clones (phagotopes) that reacted strongly by ELISA only with the selecting mAb, and inhibited binding to CII only for that mAb, not the alternate mAb. Nonetheless, a synthetic peptide RRLPFGSQM corresponding to an insert from a highly reactive CII-C1-selected phagotope, which was unreactive (and non-inhibitory) with CB268, inhibited the reactivity of CB268 with CII. Most phage-displayed peptides contained a motif in the first part of the molecule that consisted of two basic residues adjacent to at least one hydrophobic residue (e.g. RRL or LRR), but the second portion of the peptides differed for the two mAbs. We predict that conserved CDR sequences interact with the basic-basic-hydrophobic motif, whereas non-conserved amino acids in the binding sites (especially HCDR3) interact with unique peptide sequences and limit cross-reactivity. The observation that two mAbs can react identically with a single epitope on one antigen (CII), but show no cross-reactivity when tested against a second (phagotope) indicates that microorganisms could exhibit mimics capable of initiating autoimmunity without this being evident from conventional assays.