Modelling and Forecasting Dynamic VaR Thresholds for Risk Management and Regulation

The paper presents methods of estimating Value-at-Risk (VaR) thresholds utilising two calibrated models and three conditional volatility or GARCH models. These are used to estimate and forecast the VaR thresholds of an equally-weighted portfolio, comprising: the S & P500, CAC40, FTSE100 a Swiss market index (SMI). On the basis of the number of (non-)violations of the Basel Accord thresholds, the best performing model is PS-GARCH, followed by VARMA-AGARCH, then Portfolio-GARCH and the RiskmetricsTM -EWMA models, both of which would attract a penalty of 0.5. The worst forecasts are obtained from the standard normal method based on historical variances.Value at Risk (VaR) modelling, forecasting risk thresholds, Portfolio Spillover-Garch, risk management and regulation Acknowledgements: The authors wish to thank Felix Chan, Suhejla Hoti, Alex Zsimayer and seminar participants at the Institute of Economics, Academia Sinica, Taiwan, Ling Tung Institute of Technology, Griffith University, Queensland University of Technology, and University of Queensland for helpful comments and suggestions. The first and second authors wish to thank the Australian Research Council for financial support. The third author wishes to acknowledge a University Postgraduate Award and an International Postgraduate Research Scholarship at the University of Western Australia.

An Interpretable Machine Vision Approach to Human Activity Recognition using Photoplethysmograph Sensor Data

The current gold standard for human activity recognition (HAR) is based on the use of cameras. However, the poor scalability of camera systems renders them impractical in pursuit of the goal of wider adoption of HAR in mobile computing contexts. Consequently, researchers instead rely on wearable sensors and in particular inertial sensors. A particularly prevalent wearable is the smart watch which due to its integrated inertial and optical sensing capabilities holds great potential for realising better HAR in a non-obtrusive way. This paper seeks to simplify the wearable approach to HAR through determining if the wrist-mounted optical sensor alone typically found in a smartwatch or similar device can be used as a useful source of data for activity recognition. The approach has the potential to eliminate the need for the inertial sensing element which would in turn reduce the cost of and complexity of smartwatches and fitness trackers. This could potentially commoditise the hardware requirements for HAR while retaining the functionality of both heart rate monitoring and activity capture all from a single optical sensor. Our approach relies on the adoption of machine vision for activity recognition based on suitably scaled plots of the optical signals. We take this approach so as to produce classifications that are easily explainable and interpretable by non-technical users. More specifically, images of photoplethysmography signal time series are used to retrain the penultimate layer of a convolutional neural network which has initially been trained on the ImageNet database. We then use the 2048 dimensional features from the penultimate layer as input to a support vector machine. Results from the experiment yielded an average classification accuracy of 92.3%. This result outperforms that of an optical and inertial sensor combined (78%) and illustrates the capability of HAR systems using...Comment: 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Scienc

Multidimensional Heterogeneity and Platform Design

One of the most salient issues faced by platforms like newspapers and credit card issuers is that users are heterogeneous in the value they bring to other users or to the platform. We develop a model with multi-dimensional heterogeneity where a monopoly platform chooses (price or non-price) instruments. Users play two roles: 1) they are users of the platform’s services with heterogeneous preferences over instruments and platform characteristics; 2) they make heterogeneous contributions that endogenously determine these characteristics. The marginal (private or social) value of an instrument or characteristic includes the classical direct impact on profit and on (relevant) participants’ utilities, but also includes a novel sorting effect of marginal users and consequent further impact on platform characteristics. The sorting effect is quantified by the covariance, within the set of marginal users, between user preferences and user contributions towards characteristics. The private optimum departs from efficiency by prescribing lower quantities and catering to the tastes of marginal (rather than average) users. Under reasonable conditions, optimal allocations may be implemented uniquely by allowing each instrument to be contingent on all characteristics. We discuss applications to newspapers, broadcast media, credit cards, and suggest simple extensions to the case of imperfect competition in insurance provision and college admissions

Discounting in developing countries: a pilot experiment in Timor-Leste

We conduct laboratory experiments in Timor-Leste designed to test if individual discount rates vary with the time horizon for which the rate is elicited. Our experiments test a design that has been successfully employed in field experiments in developed countries, and that avoids several confounds of previous procedures. We find that there is considerable heterogeneity in individual discount rates, and that this heterogeneity is associated with observable demographic characteristics. We also find evidence that is consistent with exponential discounting behavior, although our sample sizes do not allow us to definitively reject alternative specifications. We discuss modifications of our laboratory experiments that would facilitate field experiments in Timor-Leste.

Risk-weighted assets and market value: How relevant is audit quality?

The constant financial scandals and the recent world economic crises have intensified the debate on Audit Quality and the reliability of financial reporting in the capital markets. More robust banking supervision and efficient risk management contribute to better capital adequacy in banks and, consequently, promote financial stability in the banking sector. The present study aims to analyse the relationship between the Risk-Weighted Assets of several European banks and their respective market value, in order to identify the influence of audit quality on this practice. For this purpose, a sample of 94 banks from 22 European countries is used, covering the period from 2007 to 2020. The variables under analysis take the form of bank-specific, institutional, and macroeconomic variables. The results show that Risk-Weighted Assets, the size of banks, and Non-performing loans have a negative influence on the market value. On the other hand, Profitability and Audit Quality have a positive influence.Os constantes escândalos financeiros e as recentes crises económicas mundiais, têm vindo a pôr em causa a Qualidade de Auditoria e a confiabilidade do relato financeiro no mercado de capitais. Uma supervisão bancária mais robusta e uma eficiente gestão de risco contribuem para uma melhor adequação de capital nos bancos e, consequentemente, promovem a estabilidade financeira no setor bancário. O presente estudo tem como objetivo analisar a relação entre o Risk-Weighted Assets de vários bancos Europeus e o seu respectivo valor de mercado, a fim de identificar a influência da qualidade da auditoria nesta relação. Para o efeito, é utilizada uma amostra de 94 bancos de 22 países europeus, entre o período de 2007 a 2020. As variáveis em análise assumem a forma de variáveis específicas do banco, institucionais e macroeconómicas. Os resultados demonstram que o Risk-Weighted Assets, a dimensão dos bancos e os empréstimos em incumprimento têm uma influência negativa no valor de mercado. Por outro lado, a rendibilidade e a qualidade de auditoria têm uma influência positiva