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Articoli di riviste sul tema "Risk (Insurance) – Mathematical models"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 29 gennaio 2023

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1

Prokopjeva, Evgenija, Evgeny Tankov, Tatyana Shibaeva, and Elena Perekhozheva. "Behavioral models in insurance risk management." Investment Management and Financial Innovations 18, no. 4 (October 21, 2021): 80–94. http://dx.doi.org/10.21511/imfi.18(4).2021.08.

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Behavioral characteristics attributed to consumers of insurance services are a relevant factor for analyzing the current situation in the insurance market and developing effective strategies for insurers’ actions. In turn, considering these characteristics allows the insurer to be more successful in the highly competitive field, achieving mutual satisfaction in interacting with the customer. This study is aimed to develop cognitive models of the situation (frame) “Insurance”, taking into account the specifics of the Russian insurance market and systemic factors affecting participants’ behavior

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Drissi, Ramzi. "Mathematical Risk Modeling: an Application in Three Cases of Insurance Contracts." International Journal of Advances in Management and Economics 8, no. 6 (October 30, 2019): 01–10. http://dx.doi.org/10.31270/ijame/v08/i06/2019/1.

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Risk is often defined as the degree of uncertainty regarding the future. This general definition of risk can be extended to define different types of risks according to the source of the underlying uncertainty. In this context, the objective of this paper is to mathematically model risks in insurance. The choice of methods and techniques that allow the construction of the model significantly influence the responses obtained. We approach these different issues by modeling risks in three base cases: basic insurance of goods, life insurance, and financial risk insurance. Our findings show that ri

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3

Zhuk, Tetyana. "Mathematical Models of Reinsurance." Mohyla Mathematical Journal 3 (January 29, 2021): 31–37. http://dx.doi.org/10.18523/2617-70803202031-37.

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Insurance provides financial security and protection of the independence of the insured person. Its principles are quite simple: insurance protects investments, life and property. You regularly pay a certain amount of money in exchange for a guarantee that in case of unforeseen circumstances (accident, illness, death, property damage) the insurance company will protect you in the form of financial compensation.Reinsurance, in turn, has a significant impact on ensuring the financial stability of the insurer. Because for each type of insurance there is a possibility of large and very large risks

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4

Chen, Liansheng, and Jinhua Tao. "Mixed Insurance Risk Models." Missouri Journal of Mathematical Sciences 8, no. 1 (February 1996): 3–10. http://dx.doi.org/10.35834/1996/0801003.

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5

Korstanje, Maximiliano Emanuel, and Babu P. George. "What does insurance purchase behaviour say about risks?" International Journal of Disaster Resilience in the Built Environment 6, no. 3 (September 14, 2015): 289–99. http://dx.doi.org/10.1108/ijdrbe-09-2012-0030.

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Purpose – This paper aims to explore the world of insurances as rites of adaptancy and resiliency before risk and disasters. The research on risks, both perceived and real, has become a frequent theme of academic research in the recent past. Design/methodology/approach – The information given by the superintendencia de Seguros de Buenos Aires involves 100 per cent of the insurances companies of Argentina. The reading of insurance demands corresponds with a new method in the studies of risks. Findings – Using advanced probability theory and quantitative techniques, risk management researchers h

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6

Lefèvre, Claude, and Philippe Picard. "RISK MODELS IN INSURANCE AND EPIDEMICS: A BRIDGE THROUGH RANDOMIZED POLYNOMIALS." Probability in the Engineering and Informational Sciences 29, no. 3 (March 23, 2015): 399–420. http://dx.doi.org/10.1017/s0269964815000066.

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The purpose of this work is to construct a bridge between two classical topics in applied probability: the finite-time ruin probability in insurance and the final outcome distribution in epidemics. The two risk problems are reformulated in terms of the joint right-tail and left-tail distributions of order statistics for a sample of uniforms. This allows us to show that the hidden algebraic structures are of polynomial type, namely Appell in insurance and Abel–Gontcharoff in epidemics. These polynomials are defined with random parameters, which makes their mathematical study interesting in itse

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Shkolnyk, Inna, Eugenia Bondarenko, and Valery Balev. "Estimation of the capacity of the Ukrainian stock market’s risk insurance sector." Insurance Markets and Companies 8, no. 1 (November 24, 2017): 34–47. http://dx.doi.org/10.21511/ins.08(1).2017.04.

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The purpose of the article is to determine the degree of financial interaction between the stock and insurance market, or, in other words, to determine the potential capacity of the stock market’s risk insurance sector for the Ukrainian insurance market. The authors examine the insurance not of all possible risks on the stock market, but only the most potentially important for the development of the stock market at this stage of economic development: insurance of professional risks of depositories and insurance of individual investments of individuals – participants of the stock market. In ord

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8

Nkeki, C. I., and G. O. S. Ekhaguere. "Some actuarial mathematical models for insuring the susceptibles of a communicable disease." International Journal of Financial Engineering 07, no. 02 (May 18, 2020): 2050014. http://dx.doi.org/10.1142/s2424786320500140.

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Using epidemiological and actuarial analysis, this paper formulates some new actuarial mathematical models, called S-I-DR-S models, for insuring the susceptibles of a population exposed to a communicable disease. Epidemiologically, the population is structured into four demographic groups, namely: susceptibles [Formula: see text], infectives [Formula: see text], diseased [Formula: see text] and recovered [Formula: see text], with the latter automatically re-entering the group of susceptibles [Formula: see text]. The insurance policies are targeted at the members of the susceptible group who fa

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9

Singh, Amrik, and K. R. Ramkumar. "Risk assessment for health insurance using equation modeling and machine learning." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 2 (July 26, 2021): 201–25. http://dx.doi.org/10.3233/kes-210065.

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Due to the advancement of medical sensor technologies new vectors can be added to the health insurance packages. Such medical sensors can help the health as well as the insurance sector to construct mathematical risk equation models with parameters that can map the real-life risk conditions. In this paper parameter analysis in terms of medical relevancy as well in terms of correlation has been done. Considering it as ‘inverse problem’ the mathematical relationship has been found and are tested against the ground truth between the risk indicators. The pairwise correlation analysis gives a stabl

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10

Khanlarzadeh, Sarvinaz. "Mathematical Modeling of the Risk Reinsurance Process." WSEAS TRANSACTIONS ON MATHEMATICS 21 (June 20, 2022): 447–60. http://dx.doi.org/10.37394/23206.2022.21.52.

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This paper presents a method for assessing financial risks and managing them to optimize the decision-making process. It is shown that the type of economic entity at risk and its activities in the financial market affect the specifics of financial risk management, which can be classified into three main groups: hedging, diversification, and insurance. The main instruments used for this purpose are also identified. Special attention is given to the dynamic properties of financial flows arising from the simulation of artificial financial instruments, as well as to their influence on the results

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11

Klepikova, O. А., and Z. M. Sokolovska. "The Information and Analytical Model of the Decision-Making Process for the Development of Health Insurance Programs." Business Inform 1, no. 516 (2021): 119–33. http://dx.doi.org/10.32983/2222-4459-2021-1-119-133.

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The article is aimed at studying and automating the stages of decision-making process for the development and implementation of health insurance products using the economic, mathematical, and simulation modeling. When analyzing the scientific works of scholars on the development of health insurance in Ukraine, the main stages of the decision-making process are allocated, the major of them are: the market need for an insurance product in the external environment; clear definition of the company’s tactical and strategic goals; examining the properties and characteristics of the insurance product

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Xie, Shengkun. "Improving Explainability of Major Risk Factors in Artificial Neural Networks for Auto Insurance Rate Regulation." Risks 9, no. 7 (July 2, 2021): 126. http://dx.doi.org/10.3390/risks9070126.

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In insurance rate-making, the use of statistical machine learning techniques such as artificial neural networks (ANN) is an emerging approach, and many insurance companies have been using them for pricing. However, due to the complexity of model specification and its implementation, model explainability may be essential to meet insurance pricing transparency for rate regulation purposes. This requirement may imply the need for estimating or evaluating the variable importance when complicated models are used. Furthermore, from both rate-making and rate-regulation perspectives, it is critical to

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Dashko, Vitaly Mikhailovich. "Modeling of fire risk management support in the residential sector during individual insurance." Technology of technosphere safety 97 (2022): 160–70. http://dx.doi.org/10.25257/tts.2022.3.97.160-170.

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Introduction. A significant factor influencing the reduction of the risk of death in case of fires in the residential sector is the presence of fire alarm systems (FAS) in residential premises. Ensuring FAS in the course of insurance is one of the effective ways to improve the level of fire safety in the residential sector. The relevance of the study lies in the development of a support model for fire risk management in the residential sector in the course of individual insurance of residential real estate in the Russian Federation. Goals and objectives. The purpose of the article is the devel

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Ettore D’Ortona, Nicolino, and Maria Sole Staffa. "The theoretical surrender value in life insurance." Insurance Markets and Companies 7, no. 1 (November 18, 2016): 31–44. http://dx.doi.org/10.21511/imc.7(1).2016.04.

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In the context of the stochastic models for the management of life insurance portfolio, the authors explore, with simulation approach, the effects induced by the application of a particular method of calculation of the surrender value. In the life insurance, the policyholder position is, at any moment, quantified by the mathematical reserve. In case the reserve amount results are positive, the insurance company can allow the contract surrender, consisting in an amount payment, called surrender value, commensurate with the mathematical reserve. Generally, the insurance company enforces some res

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Khare, S., A. Bonazzi, C. Mitas, and S. Jewson. "A framework for modeling clustering in natural hazard catastrophe risk management and the implications for re/insurance loss perspectives." Natural Hazards and Earth System Sciences Discussions 2, no. 8 (August 20, 2014): 5247–85. http://dx.doi.org/10.5194/nhessd-2-5247-2014.

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Abstract. In this paper, we present a novel framework for modelling clustering in natural hazard risk models. The framework we present is founded on physical principles where large-scale oscillations in the physical system is the source of non-Poissonian (clustered) frequency behaviour. We focus on a particular mathematical implementation of the "Super-Cluster" methodology that we introduce. This mathematical framework has a number of advantages including tunability to the problem at hand, as well as the ability to model cross-event correlation. Using European windstorm data as an example, we

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Embrechts, Paul, and Hanspeter Schmidli. "Ruin estimation for a general insurance risk model." Advances in Applied Probability 26, no. 02 (June 1994): 404–22. http://dx.doi.org/10.1017/s0001867800026264.

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Butuzov, S. Yu, A. V. Kryuchkov, and E. B. Tyutikova. "Safety management of tourist services based on insurance risk assessment." Technology of technosphere safety 90 (2020): 102–15. http://dx.doi.org/10.25257/tts.2020.4.90.102-115.

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Introduction. Employees of Emercom of Russia often participate in extreme tourism during their vacations, which helps to maintain their professional physical fitness. They are also attracted to help tourist groups that find themselves in a difficult situation in nature in a particular destination. Participation in extreme tourism is associated with the risk of injury. A general approach to the assessment of the impact of the management of the safety of tourist services in the instances associated with extreme tourism on insurance risks is presented. The purpose of the article is to create mode

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Ghosh, Indranil, and Filipe J. Marques. "Tail Conditional Expectations Based on Kumaraswamy Dispersion Models." Mathematics 9, no. 13 (June 24, 2021): 1478. http://dx.doi.org/10.3390/math9131478.

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Recently, there seems to be an increasing amount of interest in the use of the tail conditional expectation (TCE) as a useful measure of risk associated with a production process, for example, in the measurement of risk associated with stock returns corresponding to the manufacturing industry, such as the production of electric bulbs, investment in housing development, and financial institutions offering loans to small-scale industries. Companies typically face three types of risk (and associated losses from each of these sources): strategic (S); operational (O); and financial (F) (insurance c

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19

Ōsawa, Hideo. "Reversibility of Markov chains with applications to storage models." Journal of Applied Probability 22, no. 1 (March 1985): 123–37. http://dx.doi.org/10.2307/3213752.

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This paper studies the reversibility conditions of stationary Markov chains (discrete-time Markov processes) with general state space. In particular, we investigate the Markov chains having atomic points in the state space. Such processes are often seen in storage models, for example waiting time in a queue, insurance risk reserve, dam content and so on. The necessary and sufficient conditions for reversibility of these processes are obtained. Further, we apply these conditions to some storage models and present some interesting results for single-server queues and a finite insurance risk mode

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Mare, Codruţa, Daniela Manaţe, Gabriela-Mihaela Mureşan, Simona Laura Dragoş, Cristian Mihai Dragoş, and Alexandra-Anca Purcel. "Machine Learning Models for Predicting Romanian Farmers’ Purchase of Crop Insurance." Mathematics 10, no. 19 (October 3, 2022): 3625. http://dx.doi.org/10.3390/math10193625.

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Considering the large size of the agricultural sector in Romania, increasing the crop insurance adoption rate and identifying the factors that drive adoption can present a real interest in the Romanian market. The main objective of this research was to identify the performance of machine learning (ML) models in predicting Romanian farmers’ purchase of crop insurance based on crop-level and farmer-level characteristics. The data set used contains 721 responses to a survey administered to Romanian farmers in September 2021, and includes both characteristics related to the crop as well as farmer-

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21

Taksar, Michael I. "Optimal risk and dividend distribution control models for an insurance company." Mathematical Methods of Operations Research (ZOR) 51, no. 1 (February 17, 2000): 1–42. http://dx.doi.org/10.1007/s001860050001.

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Rivas-Lopez, Maria Victoria, Roman Minguez-Salido, Mariano Matilla Garcia, and Alejandro Echeverria Rey. "Contributions from Spatial Models to Non-Life Insurance Pricing: An Empirical Application to Water Damage Risk." Mathematics 9, no. 19 (October 3, 2021): 2476. http://dx.doi.org/10.3390/math9192476.

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This paper explores the application of spatial models to non-life insurance data focused on the multi-risk home insurance branch. In the pricing modelling and rating process, spatial information should be considered by actuaries and insurance managers because frequencies and claim sizes may vary by region and the premium should be different considering this rating variable. In addition, it is relevant to examine the spatial dependence due to the fact that the frequency of claims in neighbouring regions is often expected to be more closely related than those in regions far from each other. In t

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Bäuerle, Nicole, and Rudolf Grübel. "Multivariate risk processes with interacting intensities." Advances in Applied Probability 40, no. 2 (June 2008): 578–601. http://dx.doi.org/10.1239/aap/1214950217.

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The classical models in risk theory consider a single type of claim. In the insurance business, however, several business lines with separate claim arrival processes appear naturally, and the individual claim processes may not be independent. We introduce a new class of models for such situations, where the underlying counting process is a multivariate continuous-time Markov chain of pure-birth type and the dependency of the components arises from the fact that the birth rate for a specific claim type may depend on the number of claims in the other component processes. Under certain conditions

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Yuanjiang, He, Li Xucheng, and John Zhang. "Some results of ruin probability for the classical risk process." Journal of Applied Mathematics and Decision Sciences 7, no. 3 (January 1, 2003): 133–46. http://dx.doi.org/10.1155/s1173912603000130.

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The computation of ruin probability is an important problem in the collective risk theory. It has applications in the fields of insurance, actuarial science, and economics. Many mathematical models have been introduced to simulate business activities and ruin probability is studied based on these models. Two of these models are the classical risk model and the Cox model. In the classical model, the counting process is a Poisson process and in the Cox model, the counting process is a Cox process. Thorin (1973) studied the ruin probability based on the classical model with the assumption that ra

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Atoyev, Konstantin, and Pavel Knopov. "Assessment of Environmental, Social, Governance and Technogenic Components of Investment Risks." Cybernetics and Computer Technologies, no. 3 (November 29, 2022): 37–45. http://dx.doi.org/10.34229/2707-451x.22.3.4.

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Introduction. To assess the investment attractiveness (IA) and development opportunities for investment objects (IO), non-financial factors characterizing the environmental, social, governance and technogenic (ESGT) features of objects of possible financing have been increasingly used recently. The purpose of this data analysis is to establish how the ESGT-parameters of IO may reflect their financial health and performance prospects in a rapidly changing world. Having built an ESGT risk profile with the help of mathematical models, the IA of the object of study and the strategy of practical me

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Gasparian, Mikhail Samuilovich, Irina Anatolievna Kiseleva, Valery Alexandrovich Titov, and Natalia Alekseevna Sadovnikova. "St. Petersburg paradox: adoption of decisions on the basis of data mining and development of software in the sphere of business analytics." Nexo Revista Científica 34, no. 04 (October 28, 2021): 1370–80. http://dx.doi.org/10.5377/nexo.v34i04.12676.

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This article is devoted to analysis of models of St. Petersburg paradox, as well as development of software in the sphere of business analysis. This work is based on mathematical models using theories of probability and games as well as expert survey method. It is demonstrated that the St. Petersburg paradox is a mathematical problem of probability theory with artificial conditions. The influence of this problem on economical theory is exemplified by such provisions as the principle of diminishing marginal utility, the use of expected utility as criterion of decision adoption in uncertain envi

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Li, Jingwei, Guoxin Liu, and Jinyan Zhao. "Optimal Dividend-Penalty Strategies for Insurance Risk Models with Surplus-Dependent Premiums." Acta Mathematica Scientia 40, no. 1 (December 17, 2019): 170–98. http://dx.doi.org/10.1007/s10473-020-0112-1.

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Wang, Shijie, and Wensheng Wang. "Precise Large Deviations for Sums of Random Variables with Consistently Varying Tails in Multi-Risk Models." Journal of Applied Probability 44, no. 4 (December 2007): 889–900. http://dx.doi.org/10.1239/jap/1197908812.

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Assume that there are k types of insurance contracts in an insurance company. The ith related claims are denoted by {Xij, j ≥ 1}, i = 1,…,k. In this paper we investigate large deviations for both partial sums S(k; n1,…,nk) = ∑i=1k ∑j=1niXij and random sums S(k; t) = ∑i=1k ∑j=1Ni (t)Xij, where Ni(t), i = 1,…,k, are counting processes for the claim number. The obtained results extend some related classical results.

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Lee, Jen-Chieh, and Tyrone T. Lin. "Decision Analysis on Sustainable Value: Comparison of the London and Taiwan Markets for Product Integration of Family Security Services and Residential Fire Insurance." Journal of Risk and Financial Management 13, no. 11 (October 30, 2020): 266. http://dx.doi.org/10.3390/jrfm13110266.

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This paper explores a decision analysis on product integration of family security services and residential fire insurance in the London and Taiwan markets by using the proposed mathematical models for counting sustainable value. This paper shows the five main different results between London and Taiwan markets with ten different parameters of the family security market, to find out the optimal number of family security integrated services for each security company in London. The improvement of the risk aversion effect based on risk and financial management will enhance the market share of the

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Lefèvre, Claude, and Matthieu Simon. "Ruin problems for epidemic insurance." Advances in Applied Probability 53, no. 2 (June 2021): 484–509. http://dx.doi.org/10.1017/apr.2020.66.

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AbstractThe paper discusses the risk of ruin in insurance coverage of an epidemic in a closed population. The model studied is an extended susceptible–infective–removed (SIR) epidemic model built by Lefèvre and Simon (Methodology Comput. Appl. Prob.22, 2020) as a block-structured Markov process. A fluid component is then introduced to describe the premium amounts received and the care costs reimbursed by the insurance. Our interest is in the risk of collapse of the corresponding reserves of the company. The use of matrix-analytic methods allows us to determine the distribution of ruin time, th

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Badescu, Andrei L., Eric C. K. Cheung, and David Landriault. "Dependent Risk Models with Bivariate Phase-Type Distributions." Journal of Applied Probability 46, no. 1 (March 2009): 113–31. http://dx.doi.org/10.1239/jap/1238592120.

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In this paper we consider an extension of the Sparre Andersen insurance risk model by relaxing one of its independence assumptions. The newly proposed dependence structure is introduced through the premise that the joint distribution of the interclaim time and the subsequent claim size is bivariate phase-type (see, e.g. Assaf et al. (1984) and Kulkarni (1989)). Relying on the existing connection between risk processes and fluid flows (see, e.g. Badescu et al. (2005), Badescu, Drekic and Landriault (2007), Ramaswami (2006), and Ahn, Badescu and Ramaswami (2007)), we construct an analytically tr

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Levenchuk, Liudmyla. "The Bayesian approach to analysis of financial operational risk." ScienceRise, no. 2 (April 30, 2022): 11–20. http://dx.doi.org/10.21303/2313-8416.2022.002377.

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The article provides a short overview of methods for constructing mathematical models in the form of Bayesian Networks for modeling operational risks under conditions of uncertainty. Let’s provide the sequence of actions necessary for creating a model in the form of the network, methods for computing a probabilistic output in BN, and give examples of using the tool to solve practical problems of operational financial risk estimation. The study results can be used by financial institutions as a tool for resolving specific practical issues of risk estimation. The object of research: method

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Michna, Zbigniew. "Self-similar processes in collective risk theory." Journal of Applied Mathematics and Stochastic Analysis 11, no. 4 (January 1, 1998): 429–48. http://dx.doi.org/10.1155/s1048953398000367.

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Collective risk theory is concerned with random fluctuations of the total assets and the risk reserve of an insurance company. In this paper we consider self-similar, continuous processes with stationary increments for the renewal model in risk theory. We construct a risk model which shows a mechanism of long range dependence of claims. We approximate the risk process by a self similar process with drift. The ruin probability within finite time is estimated for fractional Brownian motion with drift. A similar model is applicable in queueing systems, describing long range dependence in on/off p

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Alanzi, Ayed R. A., M. Qaisar Rafique, M. H. Tahir, Waqas Sami, and Farrukh Jamal. "A New Modified Kumaraswamy Distribution: Actuarial Measures and Applications." Journal of Mathematics 2022 (December 31, 2022): 1–18. http://dx.doi.org/10.1155/2022/4288286.

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In this paper, a new modified Kumaraswamy distribution is proposed, and some of its basic properties are presented, such as the mathematical expressions for the moments, probability weighted moments, order statistics, quantile function, reliability, and entropy measures. The parameter estimation is done via the maximum likelihood estimation method. In order to show the usefulness of the proposed model, some well-established actuarial measures such as value-at-risk, expected-shortfall, tail-value-at-risk, tail-variance, and tail-variance-premium are obtained. A simulation study is carried out t

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Kalfin, Kalfin, Sukono Sukono, Sudradjat Supian, and Mustafa Mamat. "Insurance Premium Determination Model and Innovation for Economic Recovery Due to Natural Disasters in Indonesia." Computation 10, no. 10 (September 28, 2022): 174. http://dx.doi.org/10.3390/computation10100174.

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Climate change that occurs causes the risk of natural disasters to continue to increase throughout the world. Economic losses are unavoidable, leading to the need for continuous innovation in post-disaster economic recovery efforts. Insurance is one of the offers in providing funding for the economic recovery that occurs. This study aimed to develop innovations and models for determining natural disaster insurance premiums with a subsidy and tax system. In addition, the developed model considers the disaster risk index in the form of the level of risk distribution, the frequency of events, and

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Albrecher, Hansjörg, Sem C. Borst, Onno J. Boxma, and Jacques Resing. "Ruin excursions, the G/G/∞ queue, and tax payments in renewal risk models." Journal of Applied Probability 48, A (August 2011): 3–14. http://dx.doi.org/10.1017/s0021900200099083.

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In this paper we investigate the number and maximum severity of the ruin excursion of the insurance portfolio reserve process in the Cramér–Lundberg model with and without tax payments. We also provide a relation of the Cramér–Lundberg risk model with the G/G/∞ queue and use it to derive some explicit ruin probability formulae. Finally, the renewal risk model with tax is considered, and an asymptotic identity is derived that in some sense extends the tax identity of the Cramér– Lundberg risk model.

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Ryan, Gearóid. "Hedging your bets in a volatile world: an introduction to the use and pricing of European call options." Boolean: Snapshots of Doctoral Research at University College Cork, no. 2011 (January 1, 2011): 207–10. http://dx.doi.org/10.33178/boolean.2011.43.

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In recent years, our economy and livelihoods have been affected by the volatility of financial markets. We have seen how banks and investors have failed to control and understand their risks. In this article, I outline one of the fundamental tools used to control exposure to risk in financial markets. In doing so, I explore some of the underlying assumptions of mathematical models used in the financial industry today and show how my research attempts to make these assumptions more realistic while keeping the model simple. As well as the trading of stocks and shares, many of the transactions in

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Krah, Anne-Sophie, Zoran Nikolić, and Ralf Korn. "Least-Squares Monte Carlo for Proxy Modeling in Life Insurance: Neural Networks." Risks 8, no. 4 (November 4, 2020): 116. http://dx.doi.org/10.3390/risks8040116.

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Abstract (sommario):

The least-squares Monte Carlo method has proved to be a suitable approximation technique for the calculation of a life insurer’s solvency capital requirements. We suggest to enhance it by the use of a neural network based approach to construct the proxy function that models the insurer’s loss with respect to the risk factors the insurance business is exposed to. After giving a mathematical introduction to feed forward neural networks and describing the involved hyperparameters, we apply this popular form of neural networks to a slightly disguised data set from a German life insurer. Thereby, w

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39

Donnelly, Catherine, and Paul Embrechts. "The Devil is in the Tails: Actuarial Mathematics and the Subprime Mortgage Crisis." ASTIN Bulletin 40, no. 1 (May 2010): 1–33. http://dx.doi.org/10.2143/ast.40.1.2049222.

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AbstractIn the aftermath of the 2007-2008 financial crisis, there has been criticism of mathematics and the mathematical models used by the finance industry. We answer these criticisms through a discussion of some of the actuarial models used in the pricing of credit derivatives. As an example, we focus in particular on the Gaussian copula model and its drawbacks. To put this discussion into its proper context, we give a synopsis of the financial crisis and a brief introduction to some of the common credit derivatives and highlight the difficulties in valuing some of them.We also take a closer

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40

Khalfallah, Mohammed El-arbi, Mohammed Lakhdar Hadji, and Josep Vives. "Pricing cumulative loss derivatives under additive models via Malliavin calculus." Boletim da Sociedade Paranaense de Matemática 41 (December 23, 2022): 1–15. http://dx.doi.org/10.5269/bspm.51549.

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We show that integration by parts formulas based on Malliavin-Skorohod calculus techniques for additive processes help us to compute quantities like ${\E}(L_T h(L_T))$ for different suitable functions $h$ and different models for the cumulative loss process $L_T$. These quantities are important in Insurance and Finance. For example they appear in computing expected shortfall risk measures or stop-loss contracts. The formulas given in the present paper, obtained by simple proofs, generalize the formulas given in a recent paper by Hillairet, Jiao and Réveillac using Malliavin calculus techniques

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41

Hürlimann, Werner. "Economic capital modelling for the MTPL man-made catastrophe risk." Annals of Actuarial Science 7, no. 1 (September 4, 2012): 46–60. http://dx.doi.org/10.1017/s1748499512000164.

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AbstractWe undertake a mathematical clarification of the QIS5 proposal for the calculation of the Motor Third Party Liability (MTPL) man-made catastrophe risk capital in terms of two more general models. The QIS5 model assumption implies that the total loss consists of a single catastrophe claim in case it occurs during the next one-year insurance time period. However, the total loss should instead be dynamically modelled by a sequence of claims of varying size that follow a compound Poisson Pareto model, which is our first alternative model. A second possibility also takes into account the ef

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42

Gajek, Lesław, and Marcin Rudź. "Finite-Horizon Ruin Probabilities in a Risk-Switching Sparre Andersen Model." Methodology and Computing in Applied Probability 22, no. 4 (March 26, 2018): 1493–506. http://dx.doi.org/10.1007/s11009-018-9627-2.

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Abstract (sommario):

AbstractAfter implementation of Solvency II, insurance companies can use internal risk models. In this paper, we show how to calculate finite-horizon ruin probabilities and prove for them new upper and lower bounds in a risk-switching Sparre Andersen model. Due to its flexibility, the model can be helpful for calculating some regulatory capital requirements. The model generalizes several discrete time- as well as continuous time risk models. A Markov chain is used as a ‘switch’ changing the amount and/or respective wait time distributions of claims while the insurer can adapt the premiums in r

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43

Ryzhkov, O. Yu, and V. V. Glinskiy. "Risk Evaluation Using the Theory of Generalized Actuarial Calculations." Voprosy statistiki 26, no. 2 (March 9, 2019): 18–26. http://dx.doi.org/10.34023/2313-6383-2019-26-2-18-26.

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Abstract (sommario):

The article is prepared based on the results of theoretical studies conducted by the authors in the field of actuarial calculations, the improvement of which is one of the development directions for statistical science.In modern economic conditions, the assessment of risks inherent in economic entities in all spheres of activity and leading to significant losses, such as credit, operational risk, liquidity risk, and so forth is of particular importance. Quantitative assessment of the level of risks is the subject of actuarial calculations. However, the existing apparatus of actuarial science i

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44

Ferreiro, Ana M., Enrico Ferri, José A. García, and Carlos Vázquez. "Global Optimization for Automatic Model Points Selection in Life Insurance Portfolios." Mathematics 9, no. 5 (February 25, 2021): 472. http://dx.doi.org/10.3390/math9050472.

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Abstract (sommario):

Starting from an original portfolio of life insurance policies, in this article we propose a methodology to select model points portfolios that reproduce the original one, preserving its market risk under a certain measure. In order to achieve this goal, we first define an appropriate risk functional that measures the market risk associated to the interest rates evolution. Although other alternative interest rate models could be considered, we have chosen the LIBOR (London Interbank Offered Rate) market model. Once we have selected the proper risk functional, the problem of finding the model p

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45

Perera, S. S. N. "Analysis of Economic Burden of Seasonal Influenza: An Actuarial Based Conceptual Model." Journal of Applied Mathematics 2017 (2017): 1–6. http://dx.doi.org/10.1155/2017/4264737.

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Analysing the economic burden of the seasonal influenza is highly essential due to the large number of outbreaks in recent years. Mathematical and actuarial models can be considered as management tools to understand the dynamical behavior, predict the risk, and compute it. This study is an attempt to develop conceptual model to investigate the economic burden due to seasonal influenza. The compartment SIS (susceptible-infected-susceptible) model is used to capture the dynamical behavior of influenza. Considering the current investment and future medical care expenditure as premium payment and

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46

Pfeifer, Dietmar, and Olena Ragulina. "Generating unfavourable VaR scenarios under Solvency II with patchwork copulas." Dependence Modeling 9, no. 1 (January 1, 2021): 327–46. http://dx.doi.org/10.1515/demo-2021-0115.

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Abstract (sommario):

Abstract The central idea of the paper is to present a general simple patchwork construction principle for multivariate copulas that create unfavourable VaR (i.e. Value at Risk) scenarios while maintaining given marginal distributions. This is of particular interest for the construction of Internal Models in the insurance industry under Solvency II in the European Union. Besides this, the Delegated Regulation by the European Commission requires all insurance companies under supervision to consider different risk scenarios in their risk management system for the company’s own risk assessment. S

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47

Xie, Shengkun, and Rebecca Luo. "Measuring Variable Importance in Generalized Linear Models for Modeling Size of Loss Distributions." Mathematics 10, no. 10 (May 11, 2022): 1630. http://dx.doi.org/10.3390/math10101630.

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Abstract (sommario):

Predictive modeling is a critical technique in many real-world applications, including auto insurance rate-making and the decision making of rate filings review for regulation purposes. It is also important in predicting financial and economic risk in business and economics. Unlike testing hypotheses in statistical inference, results obtained from predictive modeling serve as statistical evidence for the decision making of the underlying problem and discovering the functional relationship between the response variable and the predictors. As a result of this, the variable importance measures be

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48

Jin, Zhuo, Rebecca Stockbridge, and George Yin. "Some Recent Progress on Numerical Methods for Controlled Regime-Switching Models with Applications to Insurance and Risk Management." Computational Methods in Applied Mathematics 15, no. 3 (July 1, 2015): 331–51. http://dx.doi.org/10.1515/cmam-2015-0015.

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AbstractThis paper provides a survey on several numerical approximation schemes for stochastic control problems that arise from actuarial science and finance. The problems to be considered include dividend optimization, reinsurance game, and quantile hedging for guaranteed minimum death benefits. To better describe the complicated financial markets and their inherent uncertainty and randomness, the so-called regime-switching models are adopted. Such models are more realistic and versatile, however, far more complicated to handle. Due to the complexity of the construction, the regime-switching

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49

Lin, Peng, Martin Neil, and Norman Fenton. "Risk aggregation in the presence of discrete causally connected random variables." Annals of Actuarial Science 8, no. 2 (August 26, 2014): 298–319. http://dx.doi.org/10.1017/s1748499514000098.

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AbstractRisk aggregation is a popular method used to estimate the sum of a collection of financial assets or events, where each asset or event is modelled as a random variable. Applications include insurance, operational risk, stress testing and sensitivity analysis. In practice, the sum of a set of random variables involves the use of two well-known mathematical operations: n-fold convolution (for a fixed number n) and N-fold convolution, defined as the compound sum of a frequency distribution N and a severity distribution, where the number of constant n-fold convolutions is determined by N,

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50

Farina, Francesco, Stefania Ottone, and Ferruccio Ponzano. "On the Collective Choice among Models of Social Protection: An Experimental Study." Games 10, no. 4 (October 11, 2019): 41. http://dx.doi.org/10.3390/g10040041.

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A real-effort experiment is conducted in order to detect preferences for one out of three different models of the Welfare State characterized by different tax-and-transfer schemes. We reproduce a small society in the lab where: Subjects are grouped in three stylized classes (the rich, the middle class and the poor) on the basis of their performance in a real-effort activity; income and risk are assigned according to the class; tax revenue is spent to refund unlucky people and to provide a public good. Experimental subjects must choose (both under and without a veil of ignorance concerning thei

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