scholarly journals Insurance Contracts for Hedging Wind Power Uncertainty

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1376
Author(s):  
Guglielmo D’Amico ◽  
Fulvio Gismondi ◽  
Filippo Petroni
Keyword(s):  
Wind Power ◽  
Real Data ◽  
Markovian Process ◽  
Insurance Contract ◽  
Generation Process ◽  
Insurance Company ◽  
Electricity Prices ◽  
Insurance Contracts ◽  
Price Process ◽  
Data Application

This paper presents an insurance contract that the supplier of wind power may subscribe to with an insurance company in order to immunize his/her revenue against the volatility of wind power and prices. Based on empirical evidence, we found that wind power and electricity prices are correlated. Then, we adopted a joint stochastic process to model both time series, which is based on indexed semi-Markov chains for the wind power generation process and on a general Markovian process for the electricity price process. Using a joint stochastic model allows the insurance company to compute the fair premium that the wind power producer has to pay in order to hedge the risk against inadequate revenues. Recursive type equations are obtained for the prospective mathematical reserves of the insurance contract. The model and the validity of the results are illustrated through a real data application.

scholarly journals Dynamic decision problems in an insurance company

1968 ◽  
Vol 5 (1) ◽  
pp. 118-131 ◽  
Author(s):  
Karl Borch
Keyword(s):  
Insurance Contract ◽  
Decision Problems ◽  
Insurance Company ◽  
The Public ◽  
Insurance Contracts ◽  
Preceding Paragraph ◽  
Frame Work ◽  
The Right ◽  
Made In ◽  
Total Payment

1.1. — In this paper we shall consider some of the decisions which have to be made in the normal course of business in an insurance company. We shall see that the “right” decisions can be found only when the problems are analysed in their proper dynamic context.As examples of the decision problems which we shall study, we can mention the following:(i) What premium rates should be quoted on the insurance contracts, which the company offers to the public?(ii) How much should the company spend to promote the sale of its policies?(iii) When should the company refuse to underwrite a proposed insurance contract?(iv) How shall the company reinsure its portfolio of insurance contracts?(v) What reserve funds should an insurance company keep?(vi) How shall the company's funds be invested?Any actuary will be familiar with such problems, and he will probably feel that these problems cannot be satisfactorily solved with the methods offered by the classical actuarial theory.1.2. — In some earlier papers [I] and [2] it has been argued that such problems can best be solved in the frame work of utility theory. As an illustration we shall take Problem (iii) in the preceding paragraph, and consider an insurance company in the following situation:(i) The company has a capital S.(ii) The company holds a portfolio of insurance contracts which will lead to a total payment of x to settle claims. F1(x) is the distribution of the variate x.

Cláusulas de franquicia o deducible en seguros de responsabilidad civil en el Derecho español: Naturaleza y efectos respecto de terceros perjudicados

2018 ◽  
pp. 101
Author(s):  
Rafael Lara González
Keyword(s):  
Civil Liability ◽  
Third Parties ◽  
Insurance Contract ◽  
Third Party ◽  
Liability Insurance ◽  
Legal Doctrine ◽  
Insurance Contracts ◽  
Spanish Law ◽  
Palabras Clave ◽  
Legal Nature

ResumenPese a su ubicuidad en la práctica contractual, las cláusulas de franquicia han recibido tratamiento incidental en la doctrina. La discusión sobre ellas se ha enfocado en los contratos de seguros de responsabilidad civil, y en la interpretación del artículo 76 de la Ley española de Contrato de Seguro. En este contexto se ha tratado de establecer si el asegurador puede o no oponer la cláusula de franquicia al tercero perjudicado. El presente trabajo analiza la cláusula de franquicia en la obligación principal del asegurador, su naturaleza jurídica, y examina su relación con los terceros perjudicados. La consideración principal a este respecto estará en si nos encontramos ante un seguro obligatorio o ante un seguro voluntario de responsabilidad civil. Palabras clave: Contrato de seguro; Cláusula de franquicia; Terceroperjudicado; Responsabilidad civil.AbstractDespite their ubiquity in contractual praxis, deductible clauses have received only incidental treatment in legal doctrine. Discussion on them has focused on civil liability insurance contracts, and the interpretation of article 76 of the Spanish Law of Insurance Contracts. In this context it has been attempted to establish whether the insurer can invoke the clause to oppose the injured third party's claim. This article examines the deductible clause included in the insurer's main obligation, its legal nature, and its relation to injured third parties. The main consideration in this regard will be whether the insurance contract is of a mandatory or voluntary nature.Keywords: Insurance contract; Deductible clause; Injured third party; Civil liability.

scholarly journals The IFRS 17 contractual service margin: a life insurance perspective

2021 ◽  
Vol 26 ◽  
Author(s):  
W. Yousuf ◽  
J. Stansfield ◽  
K. Malde ◽  
N. Mirin ◽  
R. Walton ◽  
...  
Keyword(s):  
Life Insurance ◽  
Market Value ◽  
Financial Statements ◽  
Insurance Contract ◽  
Accounting Standard ◽  
Insurance Contracts ◽  
Ifrs 4 ◽  
Insurance Perspective ◽  
To Come

Abstract IFRS 17 Insurance Contracts is a new accounting standard currently expected to come into force on 1 January 2023. It supersedes IFRS 4 Insurance Contracts. IFRS 17 establishes key principles that entities must apply in all aspects of the accounting of insurance contracts. In doing so, the Standard aims to increase the usefulness, comparability, transparency and quality of financial statements. A fundamental concept introduced by IFRS 17 is the contractual service margin (CSM). This represents the unearned profit that an entity expects to earn as it provides services. However, as a principles-based standard, IFRS 17 results in entities having to apply significant judgement when determining the inputs, assumptions and techniques it uses to determine the CSM at each reporting period. In general, the Standard resolves broad categories of mismatches which arise under IFRS 4. Notable examples include mismatches between assets recorded at current market value and liabilities calculated using fixed discount rates as well as inconsistencies in the timing of profit recognition over the duration of an insurance contract. However, there are requirements of IFRS 17 that may create economic or accounting mismatches of its own. For example, new mismatches could arise between the measurement of underlying contracts and the corresponding reinsurance held. Additionally, mismatches can still arise between the measurement of liabilities and the assets that support the liabilities. This paper explores the technical, operational and commercial issues that arise across these and other areas focusing on the CSM. As a standard that is still very much in its infancy, and for which wider consensus on topics is yet to be achieved, this paper aims to provide readers with a deeper understanding of the issues and opportunities that accompany it.

scholarly journals PERHITUNGAN PREMI ASURANSI JOINT LIFE DENGAN MODEL VASICEK DAN CIR

2019 ◽  
Vol 8 (3) ◽  
pp. 246
Author(s):  
I MADE WAHYU WIGUNA ◽  
KETUT JAYANEGARA ◽  
I NYOMAN WIDANA
Keyword(s):  
Stochastic Process ◽  
Interest Rates ◽  
Life Insurance ◽  
Insurance Premium ◽  
Insurance Contract ◽  
Insurance Company ◽  
Vasicek Model ◽  
Cir Model ◽  
Premium Payment ◽  
Premium Price

Premium is a sum of money that must be paid by insurance participants to insurance company, based on  insurance contract. Premium payment are affected by interest rates. The interest rates change according to stochastic process. The purpose of this work is to calculate the price of joint life insurance premiums with Vasicek and CIR models. The price of a joint life insurance premium with Vasicek and CIR models, at the age of the insured 35 and 30 years has increased until the last year of the contract. The price of a joint life insurance premium with Vasicek model is more expensive than the premium price using CIR model.

scholarly journals Revitalising the wind power induced merit order effect to reduce wholesale and retail electricity prices in Australia

2017 ◽  
Vol 67 ◽  
pp. 224-241 ◽  
Author(s):  
William Paul Bell ◽  
Phillip Wild ◽  
John Foster ◽  
Michael Hewson
Keyword(s):  
Wind Power ◽  
Order Effect ◽  
Electricity Prices

scholarly journals Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2164
Author(s):  
Héctor J. Gómez ◽  
Diego I. Gallardo ◽  
Karol I. Santoro
Keyword(s):  
Expectation Maximization Algorithm ◽  
Likelihood Estimation ◽  
Real Data ◽  
Simulation Studies ◽  
R Software ◽  
Data Application ◽  
The Em Algorithm ◽  
Kurtosis Parameter ◽  
Computational Implementation ◽  
Moments Method

In this paper, we present an extension of the truncated positive normal (TPN) distribution to model positive data with a high kurtosis. The new model is defined as the quotient between two random variables: the TPN distribution (numerator) and the power of a standard uniform distribution (denominator). The resulting model has greater kurtosis than the TPN distribution. We studied some properties of the distribution, such as moments, asymmetry, and kurtosis. Parameter estimation is based on the moments method, and maximum likelihood estimation uses the expectation-maximization algorithm. We performed some simulation studies to assess the recovery parameters and illustrate the model with a real data application related to body weight. The computational implementation of this work was included in the tpn package of the R software.

27. Insurance

2017 ◽  
Author(s):  
MA Clarke ◽  
RJA Hooley ◽  
RJC Munday ◽  
LS Sealy ◽  
AM Tettenborn ◽  
...  
Keyword(s):  
Insurance Contract ◽  
Marine Insurance ◽  
Insurance Claims ◽  
Insurance Law ◽  
Insurable Interest ◽  
Insurance Contracts

This chapter deals with insurance and the principles of insurance law. Contracts of insurance may be subdivided into two categories: indemnity insurance and contingency insurance. Under a contract of insurance, the event insured against is interpreted to be uncertain, either in the sense that it may or may not occur, or that the time of the occurrence is uncertain. This chapter first explains how insurance works, with a particular focus on insurable interest, the statutes that govern insurance contracts, and the power of the Financial Conduct Authority to authorise persons wishing to conduct business as insurers. It then considers how an insurance contract is formed and goes on to describe the content and interpretation of the contract. It also discusses the liability and rights of the insurer before concluding with an analysis of marine insurance and insurance claims.

scholarly journals Causal variance decompositions for institutional comparisons in healthcare

2019 ◽  
Vol 29 (7) ◽  
pp. 1972-1986
Author(s):  
Bo Chen ◽  
Keith A Lawson ◽  
Antonio Finelli ◽  
Olli Saarela
Keyword(s):  
Random Effect ◽  
Real Data ◽  
Hospital Performance ◽  
Case Mix ◽  
Link Functions ◽  
Variation In Care ◽  
Residual Variation ◽  
Data Application ◽  
Variance Decompositions ◽  
Random Effect Models

There is increasing interest in comparing institutions delivering healthcare in terms of disease-specific quality indicators (QIs) that capture processes or outcomes showing variations in the care provided. Such comparisons can be framed in terms of causal models, where adjusting for patient case-mix is analogous to controlling for confounding, and exposure is being treated in a given hospital, for instance. Our goal here is to help identify good QIs rather than comparing hospitals in terms of an already chosen QI, and so we focus on the presence and magnitude of overall variation in care between the hospitals rather than the pairwise differences between any two hospitals. We consider how the observed variation in care received at patient level can be decomposed into that causally explained by the hospital performance adjusting for the case-mix, the case-mix itself, and residual variation. For this purpose, we derive a three-way variance decomposition, with particular attention to its causal interpretation in terms of potential outcome variables. We propose model-based estimators for the decomposition, accommodating different link functions and either fixed or random effect models. We evaluate their performance in a simulation study and demonstrate their use in a real data application.

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