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Статті в журналах з теми "Bootstrap adjustment"
Rocke, David M. "Bootstrap Bartlett Adjustment in Seemingly Unrelated Regression." Journal of the American Statistical Association 84, no. 406 (June 1989): 598–601. http://dx.doi.org/10.1080/01621459.1989.10478809.
Повний текст джерелаEmbrechts, Paul, and Thomas Mikosch. "A bootstrap procedure for estimating the adjustment coefficient." Insurance: Mathematics and Economics 10, no. 3 (December 1991): 181–90. http://dx.doi.org/10.1016/0167-6687(91)90048-3.
Повний текст джерелаTrenkler, Carsten. "BOOTSTRAPPING SYSTEMS COINTEGRATION TESTS WITH A PRIOR ADJUSTMENT FOR DETERMINISTIC TERMS." Econometric Theory 25, no. 1 (February 2009): 243–69. http://dx.doi.org/10.1017/s0266466608090087.
Повний текст джерелаAcquah, Henry de-Graft. "A Bootstrap Approach to Evaluating the Power of the Houck’s Test for Asymmetry." Journal of Social and Development Sciences 4, no. 2 (February 28, 2013): 69–73. http://dx.doi.org/10.22610/jsds.v4i2.737.
Повний текст джерелаAcquah, Henry De-Graft. "Using Bootstrap Method to Evaluate the Power of Tests for Non-Linearity in Asymmetric Price Relationship." Journal of Economics and Behavioral Studies 5, no. 4 (April 30, 2013): 237–41. http://dx.doi.org/10.22610/jebs.v5i4.399.
Повний текст джерелаAcquah, Henry de-Graft. "A Comparison of Bootstrap and Monte Carlo Approaches to Testing for Symmetry in the Granger and Lee Error Correction Model." Information Management and Business Review 5, no. 5 (May 30, 2013): 240–44. http://dx.doi.org/10.22610/imbr.v5i5.1048.
Повний текст джерелаPitts, Susan M., Rudolf Grübel, and Paul Embrechts. "Confidence bounds for the adjustment coefficient." Advances in Applied Probability 28, no. 3 (September 1996): 802–27. http://dx.doi.org/10.2307/1428182.
Повний текст джерелаPitts, Susan M., Rudolf Grübel, and Paul Embrechts. "Confidence bounds for the adjustment coefficient." Advances in Applied Probability 28, no. 03 (September 1996): 802–27. http://dx.doi.org/10.1017/s0001867800046504.
Повний текст джерелаKayal, Parthajit, and S. Maheswaran. "Speed of Price Adjustment towards Market Efficiency: Evidence from Emerging Countries." Journal of Emerging Market Finance 17, no. 1_suppl (February 26, 2018): S112—S135. http://dx.doi.org/10.1177/0972652717751542.
Повний текст джерелаChen, Ze Wei, Jun Chai, and Jian Yu Ge. "The Efficacy of CPPI and VBPI Based on Stationary Bootstrap Method." Applied Mechanics and Materials 687-691 (November 2014): 4848–52. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.4848.
Повний текст джерелаДисертації з теми "Bootstrap adjustment"
Oliveira, Catarina Pereira. "On the technical aspects and practical application of the IFRS 17 risk adjustment." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/20857.
Повний текст джерелаA norma contabilística IFRS 17 foi publicada a 18 de maio de 2017 com o objetivo de aumentar a comparabilidade entre contratos de seguros por todo o mundo. O Ajustamento de Risco (AR) é introduzido no novo requisito como o elemento que reflete a compensação requerida pela entidade para suportar a incerteza associada a riscos não financeiros quanto ao montante e timing dos fluxos de caixa. Sendo "principles-based", a IFRS 17 não estabelece um método específico para calcular o AR. Este relatório de estágio explora os detalhes técnicos subjacentes ao AR e procura avaliar os possíveis métodos de computação, desde técnicas de quantis, como o "Value-at-Risk", o "Tail-Value-at-Risk" e o "Proportional Hazard Transform", bem como outras medidas de risco utilizadas presentemente, como o método do "Cost-of-Capital". A partir de exemplos ilustrativos para produtos de não-vida e vida, é possível concluir que contratos de seguro com tendências de fluxos de caixa mais voláteis tendem a gerar distribuições de probabilidades de fluxos futuros mais "largas", dada uma maior incerteza sobre os mesmos, o que resulta num maior valor de AR. Para o produto de não-vida, foi utilizado o método de Bootstrap para gerar estocasticamente a distribuição de probabilidades de fluxos futuros.
The accounting standard IFRS 17 was released on 18 May 2017 with the purpose of increasing comparability between insurance contracts globally. The Risk Adjustment (RA) is introduced by the new standard as the element reflecting the compensation required by an entity for bearing the uncertainty that arises from non-financial risk regarding the amount and timing of cash flows. Being principles-based, IFRS 17 does not prescribe a calculation method for the RA. This internship report explores the technical aspects underlying the RA and aims to assess commonly found computational methods, from quantiles measures - like the Value-at-Risk, Tail-Value-at-Risk and the Proportional Hazard Transform - to existing risk measuring techniques, such as the Cost-of-Capital approach. From illustrative examples for both non-life and life products, it is possible to conclude that insurance contracts with more volatile cash flow trends have wider probability distributions of future losses, given an increase in uncertainty, which result in higher RA estimates. For the non-life product, the Bootstrap method is also applied - prior to the risk measures - to stochastically generate a probability distribution function of losses.
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Sjöström, Magnus. "Factor Demand and Market Power." Doctoral thesis, Umeå universitet, Nationalekonomi, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-279.
Повний текст джерелаPanasco, Ana Margarida Canelhas. "Risk adjustment - metodologias de cálculo da LIC compliant com a nova Norma de Relato Financeiro IFRS 17." Master's thesis, 2020. http://hdl.handle.net/10451/48649.
Повний текст джерелаA difícil comparabilidade entre as companhias de seguros e a permissão de aplicabilidade de distintas políticas contabilísticas pelas entidades do setor segurador de acordo com o país em que inserem, fez surgir a nova norma para os contratos de seguro: IFRS 17 – Contratos de Seguro. O novo normativo, desenvolvido pelo IASB como substituto da norma interina IFRS 4, materializa-se numa enorme metamorfose na contabilização das demonstrações financeiras das companhias de seguros, revelada pelos novos requisitos, complexos e rigorosos, que são exigidos para a mensuração dos contratos de seguro. O presente estudo aborda especificamente o novo conceito do Risk Adjustment para os riscos não financeiros que surge no domínio deste novo normativo com obrigatoriedade legal a partir de janeiro de 2023. Neste sentido, são desenvolvidas várias metodologias de cálculo desta componente no contexto do modelo geral de mensuração implícito na IFRS 17. As metodologias propostas emergem de abordagens paramétricas e não paramétricas consagradas na Estatística e envolvem procedimentos de estimação de quantis de ordem 𝑝, indicadores do nível de confiança que se pretendeu vincular ao devido procedimento. Nesta sequência, é determinado o Risk Adjustment específico para a mensuração da Liability for Incurred Claims (LIC) da carteira de seguros Multirriscos Habitação da ASP Não Vida, com base em Risk Adjustment marginais determinados ao nível de cada causa de ocorrência dos sinistros e a distintos níveis de confiança que se fundamentam no princípio da prudência das estimativas dos custos face aos serviços passados da Companhia. É também efetuado o paralelismo, teórico e prático, do novo conceito de Risk Adjustment, no contexto da IFRS 17, com o conceito de Risk Margin já existente e transversalmente aplicado pelas companhias de seguros no âmbito do reporte da solvência e situação financeira pelo regime Solvência II.
The difficult comparability between insurance companies and the permission for different accounting policies that entities in the insurance sector may apply, according to the country in which they operate, led to the emergence of the new standard for insurance contracts: IFRS 17 - Insurance Contracts. The new standard, issued by the IASB as a substitute for the interim IFRS 4 standard, materializes in a huge metamorphosis in the accounting of insurance companies' financial statements, revealed by the new, complex and rigorous requirements that are mandatory for the measurement of insurance contracts. This study specifically addresses the new concept of Risk Adjustment for non-financial risks that arises in the field of this new regulation, which is legally mandatory as of January 2023. In this sense, several methodologies for calculating this component are developed in the context of the IFRS 17 general model. The proposed methodologies emerge from the existing parametric and non-parametric approaches in Statistics and involve estimation procedures for pth quantiles, which are indicators of the confidence level that was intended to be linked to the procedure. In this sequence, the specific Risk Adjustment is determined for the measurement of the company’s Liability for Incurred Claims (LIC) for Multi-risk House insurance portfolio, based on marginal Risk Adjustments determined in terms of the reason for the occurrence of claims and determined at different confidence levels, that are based on the principle of prudence in estimating costs related to past services of ASP Não Vida. The theoretical and practical parallelism of the IFRS 17’s new concept of Risk Adjustment is also carried out with the Risk Margin concept, which already exists and is transversely applied by insurance companies in terms of solvency and financial reporting under the Solvency II regime.
Книги з теми "Bootstrap adjustment"
Finding Your Bootstraps: 11 Steps to Overcoming Victim Thinking. Gerald Simmons & Associates, 2005.
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