ORiON

Editorial

Jaco Visagie — 2023-06-30

Anomaly detection using autoencoders with network analysis features

Richard Ball — 2023-06-27

Fraudulent activity within a financial ecosystem often involves the coordinated efforts of several bad actors. Expressing the interactions between participants in a system as a mathematical graph allows researchers to apply social network analysis to understand the nature of these relationships better. This article proposes and extends a unified approach using an autoencoder to detect anomalies in a transactional setting. The methodology begins with a neural architecture search to determine a best autoencoder model architecture configuration. This is followed by a threshold optimisation process to find a reconstruction error that best discriminates between normal and anomalous classes. Gaussian scaling is applied to the raw anomaly scores in order to represent the output in an interpretable and universally transferable form. The unified approach is extended by selecting and including network metrics as features, for the purposes of producing a model that can detect anomalies from both standard transactional data and network data representing the relationships between users within a financial system. Applying SHAP on the model output highlighted the strongest contributing or offsetting network metric features for all anomalies detected. The PageRank and degree centrality network metrics were most significant in detecting anomalous instances within the data. Including network metrics in the feature space generated encouraging model performance results, leading to a potential low operational cost of fraud.

Route overlap metrics to batch orders

Stephan E Visagie — 2023-06-27

In this study different metrics to perform order batching for a unidirectional cyclical picking system are investigated. Batches must be formed to minimise walking distance that is measured as the total number of cycles traversed by pickers.
Route overlap metrics are developed to approximate walking distance before picker routing. Thereby, information about route similarity is added to identify orders that are compatible for batching.
A span is the length of a section of picking line that a picker walks to collect the items in an order.
Three metrics based on the concept of a span are developed, namely the stops non-identical spans, the non-identical stops-spans and the stops-spans ratio metric.
Numerical experiments are carried out to determine the best combination between route overlap metric and batching method. A prominent South African retailer's distribution centre provides \(50\)~sample picking waves for an experimental set up with real-life data. The stops non-identical spans metric used together with greedy smallest entry heuristic to perform the batching consistently leads to a low number of cycles traversed to complete a picking wave relative to the other methods.

On the calibration of stochastic volatility models to estimate the real-world measure used in option pricing

Alexis Levendis — 2023-06-27

It is widely noted that the Heston stochastic volatility model fails to capture the fat tails often observed in daily equity returns. Adding random jumps improves the model’s ability to capture extreme events. This extension is known as the Bates stochastic volatility jump (SVJ) model. The model parameters for the Heston and Bates SVJ models are generally calibrated to option prices inducing the so-called risk-neutral measure. However, in the absence of a sufficiently liquid options market, one has to resort to calibration under the realworld measure. In this paper, we calibrate the Heston and Bates SVJ models to historical equity returns in the United States and South Africa using the efficient method of moments
(EMM). We then show how a real-world stochastic volatility model can be used in practice to test a simple volatility targeting strategy. Our findings suggest that stochastic volatility and jumps are both required to characterise equity returns in South Africa. Furthermore, volatility targeting is an effective strategy that allows investors to manage the downside risk of a portfolio.

Celebrating 50-years of OR in South Africa – a Bibliometric Analysis of contributions to International OR Literature

Hans Ittmann — 2023-06-27

The Operations Research Society of South Africa (ORSSA), the first Operations Research (OR) society in Africa, celebrated its 50^th anniversary at its annual conference in 2019. To commemorate the occasion a book, covering the history of the society, was launched at the conference. One area that was not covered in this book was the contribution of South Africans to the international OR literature. This paper endeavors to fill that void through a bibliographic analysis of papers published by South Africans over the 50-year period. A list of over 100 journals were used for this analysis. General empirical results are derived while a visual analysis of top author research networks is presented. The analysis demonstrates the contribution to the international OR/MS knowledge base of a small but vibrant national OR society at the most southern point of Africa.