Operational risk and its relationship with institution size in the Hungarian banking sector

In addition to credit, market and liquidity risk, measuring and managing operational risk (risk associated with people, systems, processes and external events) is a great challenge for banks. In 2010, around HUF 35 billion in operational risk losses were reported in the banking sector overall, which is significant relative to the pre-tax profits of the banking sector. To a large extent, banks’ operational risk measurement methods rely on loss events which have already occurred. If an individual institution has insufficient data for modelling or wishes to include the experiences of extreme events, it should use external data or transpose the risk exposure of the banking sector onto itself. The empirical analysis of the Hungarian banking sector’s operational risk data confirms that, similarly to foreign banking sectors and banking groups (which have been already analysed in the relevant literature), there is a significant relationship in the Hungarian banking sector between institution size as defined by gross income and total operational risk losses recorded during the specific period. However, the most significant correlation can be observed between institution size and the frequency of operational risk losses. This result could provide basis for the systemic analysis of operational risk and support simpler operational risk capital allocation methods. Nonetheless, due to the relatively short time series and the significant dispersion of data, we could not robustly assess the sufficiency of the capital already allocated for operational risk.banks, financial risk, risk management, operational risk

Size-Change Termination as a Contract

Termination is an important but undecidable program property, which has led to a large body of work on static methods for conservatively predicting or enforcing termination. One such method is the size-change termination approach of Lee, Jones, and Ben-Amram, which operates in two phases: (1) abstract programs into "size-change graphs," and (2) check these graphs for the size-change property: the existence of paths that lead to infinite decreasing sequences. We transpose these two phases with an operational semantics that accounts for the run-time enforcement of the size-change property, postponing (or entirely avoiding) program abstraction. This choice has two key consequences: (1) size-change termination can be checked at run-time and (2) termination can be rephrased as a safety property analyzed using existing methods for systematic abstraction. We formulate run-time size-change checks as contracts in the style of Findler and Felleisen. The result compliments existing contracts that enforce partial correctness specifications to obtain contracts for total correctness. Our approach combines the robustness of the size-change principle for termination with the precise information available at run-time. It has tunable overhead and can check for nontermination without the conservativeness necessary in static checking. To obtain a sound and computable termination analysis, we apply existing abstract interpretation techniques directly to the operational semantics, avoiding the need for custom abstractions for termination. The resulting analyzer is competitive with with existing, purpose-built analyzers

The influence of size on cost behaviour associated with tactical and operational flexibility

This paper contributes with an empirical analysis, using a sample of farms, on the influence of size on cost behaviour under operational and tactical flexibility. Results indicate that small farms behave advantageously with respect to biggest farms in situations of operational and tactical flexibility. On the one hand, the increase in indirect costs with product diversification is higher in bigger farms than in smaller. On the other hand, while most farms are flexible enough to avoid cost stickiness, the biggest face considerable rigidities in downsizing indirect costs when activity decreases.Agricultural economics, Tactical flexibility, Operational flexibility, Cost behaviour, Size.

Operational Markov condition for quantum processes

We derive a necessary and sufficient condition for a quantum process to be Markovian which coincides with the classical one in the relevant limit. Our condition unifies all previously known definitions for quantum Markov processes by accounting for all potentially detectable memory effects. We then derive a family of measures of non-Markovianity with clear operational interpretations, such as the size of the memory required to simulate a process, or the experimental falsifiability of a Markovian hypothesis.Comment: 5+3 pages, 4 figures; split off from earlier version of arXiv:1512.0058

Optimizing the process of supercritical extraction of lemon balm (Melissa Officinalis L.)

This work investigates the process of extraction of lemon balm (Melissa officinalis L.) by treatment with carbon dioxide at supercritical conditions. The process kinetics is studied at different operational conditions, and the influence of some important regime parameters (pressure, temperature particle size, solvent flow-rate) on the extraction yield is experimentally determined. Besides the information for process intensity at particular operational regimes, the results are useful for selection of favourable operational conditions for better extraction, i.e. for production of larger quantity of extracted substances from unit mass of raw material

Reducing regression test size by exclusion.

Operational software is constantly evolving. Regression testing is used to identify the unintended consequences of evolutionary changes. As most changes affect only a small proportion of the system, the challenge is to ensure that the regression test set is both safe (all relevant tests are used) and unclusive (only relevant tests are used). Previous approaches to reducing test sets struggle to find safe and inclusive tests by looking only at the changed code. We use decomposition program slicing to safely reduce the size of regression test sets by identifying those parts of a system that could not have been affected by a change; this information will then direct the selection of regression tests by eliminating tests that are not relevant to the change. The technique properly accounts for additions and deletions of code. We extend and use Rothermel and Harrold’s framework for measuring the safety of regression test sets and introduce new safety and precision measures that do not require a priori knowledge of the exact number of modification-revealing tests. We then analytically evaluate and compare our techniques for producing reduced regression test sets