ANALYSIS OF ROBUST CHAIN LADDER METHOD IN ESTIMATING AUSTRALIAN MOTOR INSURANCE RESERVES WITH OUTLYING DATASET

Reserves are one of the most crucial components for an insurance company to make sure it has enough money to pay off all the incurred claims. The presence of outliers in the incurred claims data harbors risk on inaccurately predicting reserves to cover claim amounts, usually achieved by the standard chain ladder reserving method. To remedy the effect of the outliers, the robust chain ladder reserving method is used by setting the median value to predict estimated reserve. On this research, we utilized both methods on various datasets. The purpose of this paper is to determine the best method that can be utilized by insurance company in various scenario to obtain the most optimized reserved estimate that can minimize the risk of being unable to pay the insurance claim or even the risk of over allocating reserves that could pose profitability issue. The primary data used are the Australian domestic motor insurance claims from 2012 to 2017, obtained from Australian Prudential Regulation Authority (APRA). The dataset is then manipulated to have outliers. After calculating the estimation, the result is compared to assess the strength of the methods using Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) calculation. In conclusion, we found that the robust chain ladder reserving method works better in an outlying dataset. We also identify cases in which robust chain ladder are not appropriately used

Intensity modulated radiation therapy and arc therapy: validation and evolution as applied to tumours of the head and neck, abdominal and pelvic regions

Intensiteitsgemoduleerde radiotherapie (IMRT) laat een betere controle over de dosisdistributie (DD) toe dan meer conventionele bestralingstechnieken. Zo is het met IMRT mogelijk om concave DDs te bereiken en om de risico-organen conformeel uit te sparen. IMRT werd in het UZG klinisch toegepast voor een hele waaier van tumorlocalisaties. De toepassing van IMRT voor de bestraling van hoofd- en halstumoren (HHT) vormt het onderwerp van het eerste deel van deze thesis. De planningsstrategie voor herbestralingen en bestraling van HHT, uitgaande van de keel en de mondholte wordt beschreven, evenals de eerste klinische resultaten hiervan. IMRT voor tumoren van de neus(bij)holten leidt tot minstens even goede lokale controle (LC) en overleving als conventionele bestralingstechnieken, en dit zonder stralingsgeïnduceerde blindheid. IMRT leidt dus tot een gunstiger toxiciteitprofiel maar heeft nog geen bewijs kunnen leveren van een gunstig effect op LC of overleving. De meeste hervallen van HHT worden gezien in het gebied dat tot een hoge dosis bestraald werd, wat erop wijst dat deze “hoge dosis” niet volstaat om alle clonogene tumorcellen uit te schakelen. We startten een studie op, om de mogelijkheid van dosisescalatie op geleide van biologische beeldvorming uit te testen. Naast de toepassing en klinische validatie van IMRT bestond het werk in het kader van deze thesis ook uit de ontwikkeling en het klinisch opstarten van intensiteitgemoduleerde arc therapie (IMAT). IMAT is een rotationele vorm van IMRT (d.w.z. de gantry draait rond tijdens de bestraling), waarbij de modulatie van de intensiteit bereikt wordt door overlappende arcs. IMAT heeft enkele duidelijke voordelen ten opzichte van IMRT in bepaalde situaties. Als het doelvolume concaaf rond een risico-orgaan ligt met een grote diameter, biedt IMAT eigenlijk een oneindig aantal bundelrichtingen aan. Een planningsstrategie voor IMAT werd ontwikkeld, en type-oplossingen voor totaal abdominale bestraling en rectumbestraling werden onderzocht en klinisch toegepast

Systematic comparison of designs and emulators for computer experiments using a library of test functions

As computational resources have become faster and more economical, scientific research has transitioned from using only physical experiments to using simulationbased exploration. A body of literature has since grown aimed at the design and analysis of so-called computer experiments. While this literature is large and active, little work has been focused on comparing methods. This project presents ways of comparing and evaluating both design and emulation methods for computer experiments. Using a suite of test functions — in this work we introduce the Virtual Library of Computer Experiments a procedure is established which can provide guidance as to how to proceed in simulation problems. An illustrative comparison is performed for each context; putting three emulators, then four experimental designs up against each other; while also highlighting possible considerations for test function choice

Cyber insurance as a risk manager

L’objectif de cette étude vise à comprendre comment les compagnies d’assurance Canadienne conceptualisent les cyber risques afin d’être en mesure de quantifier des pertes résiduelles ou en constante évolution. Par l’entremise de 10 entretiens qualitatif avec des professionnel de l’assurance, nous avons trouvé que la souscription à une cyber assurance peut aider les entrepreneurs à gérer les risques causés par la cyber criminalité. L’étude montre que la cyber assurance contribue à la compréhension et à la diffusion de connaissance en matière de cybercriminalité. Ceci est facilité par la recherche continue sur le phénomène et de la mise à jour ces polices d’assurance. Aussi, il a été trouvé que les professionnels de l’assurance facilitent l’application des mesures de prévention cyber. Cette gestion est permise grâce aux outils mis à disposition des assureurs afin d’évaluer les composantes de sécurité pour contrer les cyber attaques. Finalement, la recherche démontre que le milieu des assurances joue un rôle d’envergure dans la surveillance et la gouvernance des cyber risques.The goal of this research is to understand how Canadian insurance companies conceptualize cyber risks to quantify a residual or evolving loss. Through ten qualitative semi-structured interviews conducted with insurance professionals throughout Canada, we found that the purchase of cyber coverage contributes to the risk management efforts. Companies are increasingly looking to implement or enhance their cyber security measures through cyber insurance. In fact, the study found that cyber insurance can serve three purposes. The first is that it allows for a better understanding and diffusion of knowledge through the continuous research on cybercrimes and the revision of cyber policies. The second finding is that insurance professionals work with companies to assess and facilitate the integration of preventive measures. This is based on the tools they use to asses a company’s cyber security infrastructure. Finally, the study found that insurance companies have a considerable societal impact on the surveillance and governance of cybercrimes

Estimation of Hidden Markov Models and Their Applications in Finance

Movements of financial variables exhibit extreme fluctuations during periods of economic crisis and times of market uncertainty. They are also affected by institutional policies and intervention of regulatory authorities. These structural changes driving prices and other economic indicators can be captured reasonably by models featuring regime-switching capabilities. Hidden Markov models (HMM) modulating the model parameters to incorporate such regime-switching dynamics have been put forward in recent years, but many of them could still be further improved. In this research, we aim to address some of the inadequacies of previous regime-switching models in terms of their capacity to provide better forecasts and efficiency in estimating parameters. New models are developed, and their corresponding filtering results are obtained and tested on financial data sets. The contributions of this research work include the following: (i) Recursive filtering algorithms are constructed for a regime-switching financial model consistent with no-arbitrage pricing. An application to the filtering and forecasting of futures prices under a multivariate set-up is presented. (ii) The modelling of risk due to market and funding liquidity is considered by capturing the joint dynamics of three time series (Treasury-Eurodollar spread, VIX and S\&P 500 spread-derived metric), which mirror liquidity levels in the financial markets. HMM filters under a multi-regime mean- reverting model are established. (iii) Kalman filtering techniques and the change of reference probability-based filtering methods are integrated to obtain hybrid algorithms. A pairs trading investment strategy is supported by the combined power of both HMM and Kalman filters. It is shown that an investor is able to benefit from the proposed interplay of the two filtering methods. (iv) A zero-delay HMM is devised for the evolution of multivariate foreign exchange rate data under a high-frequency trading environment. Recursive filters for quantities that are functions of a Markov chain are derived, which in turn provide optimal parameter estimates. (v) An algorithm is designed for the efficient calculation of the joint probability function for the occupation time in a Markov-modulated model for asset returns under a general number of economic regimes. The algorithm is constructed with accessible implementation and practical considerations in mind

Community structure in the World Trade Network based on communicability distances

In this paper, we investigate the mesoscale structure of the World Trade Network. In this framework, a specific role is assumed by short and long-range interactions, and hence by the distance, between countries. Therefore, we identify clusters through a new procedure that exploits Estrada communicability distance and the vibrational communicability distance, which turn out to be particularly suitable for catching the inner structure of the economic network. The proposed methodology aims at finding the distance threshold that maximizes a specific modularity function defined for general metric spaces. Main advantages regard the computational efficiency of the procedure as well as the possibility to inspect intercluster and intracluster properties of the resulting communities. The numerical analysis highlights peculiar relationships between countries and provides a rich set of information that can hardly be achieved within alternative clustering approaches.Comment: 40 pages, 19 figure

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

Curve Estimation Based on Localised Principal Components - Theory and Applications

In this work, basic theory and some proposed developments to localised principal components and curves are introduced. In addition, some areas of application for local principal curves are explored. Only relatively recently, localised principal components utilising kernel-type weights have found their way into the statistical literature. In this study, the asymptotic behaviour of the method is investigated and extended to the context of local principal curves, where the characteristics of the points at which the curve stops at the edges are identified. This is used to develop a method that lets the curve `delay' convergence if desired, gaining more access to boundary regions of the data. Also, a method for automatic choice of the starting point to be one of the local modes within the data cloud is originated. The modified local principal curves' algorithm is then used for fitting multi-dimensional econometric data. Special attention is given to the role of the curve parametrisation, which serves as a feature extractor and also as a prediction tool when properly linked to time as a probable underlying latent variable. Local principal curves provide a good dimensionality reduction and feature extraction tool for insurance industry key indicators and consumer price indices. Also, through `calibrating' it with time, curve parametrisation is used for the purpose of predicting unemployment and inflation rates