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Business Analytics Seminars

The seminars are on Fridays at 11am in Room 498, Merewether Building (cnr of City Road and Butlin Avenue), unless otherwise specified.

The seminar organiser is Artem Prokhorov.

7th May 2014 - 11:00 am

Speaker:

Professor Pavel Shevchenko,

Affiliation:

Senior Principal Research Scientist; CSIRO - Computational Informatics

Venue:

Rm 498 Merewether Bldg H04

Title:

Loss Distribution Approach for Operational Risk Capital Modelling: Challenges and Pitfalls

Abstract:

The management of operational risk in the banking industry has undergone explosive changes over the last decade due to substantial changes in the operational environment. Globalization, deregulation, the use of complex financial products and changes in information technology have resulted in exposure to new risks very different from market and credit risks. In response, Basel Committee for Banking Supervision has developed a regulatory Basel II framework that introduced operational risk category and corresponding capital requirements. Over the past five years, many major banks have received accreditation under the Basel II Advanced Measurement Approach by adopting the Loss Distribution Approach (LDA) despite there being a number of unresolved methodological challenges in its implementation. Different approaches and methods are still under hot debate. This talk is devoted to quantitative issues in operational risk LDA such as modelling large losses, methods to combine different data sources (internal data, external data and scenario analysis) and modelling dependence which are still unresolved issues in operational risk capital modelling. Presented results are based on our work with the banking industry, discussions with regulators and academic research.

 

16th May 2014 - 11:00 am

Speaker:

Dr Demetris Christodolou,

Affiliation:

Discipline of Accounting; The University of Sydney

Venue:

Rm 498 Merewether Bldg H04

Title:

Identification and Intepretation of Estimates from the Rank Deficient Accounting Data Matrix

Abstract:

Regression models that rely on inputs from published financial statements ignore the fact that the observed accounting data matrix is rank deficient by design. The standard practice is to identify zero-parameter restrictions on the accounting matrix in order to impose full rank and enable estimation but this approach renders the interpretation of recovered estimates as composite deviations from the identity parameters that have been omitted. The alternative approach would be to identify suitable restrictions on linear combinations, but again the interpretation of estimates is conditional on validity of the restriction. This is a standard result in the analysis of intercepts but there is lack of insight on how to deal with rank deficient systems of slope coefficients, and this has proven to be an acute problem for empirical accounting research that fails to acknowledge the relevant effects. We discuss the problem of identification and interpretation of estimates from the rank deficient accounting data matrix, particularly within the context of equity pricing models.

* joint work with Professor Richard Gerlach