Scenario Selection with Lasso Regression for the Valuation of Variable Annuity Portfolios PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Scenario Selection with Lasso Regression for the Valuation of Variable Annuity Portfolios PDF full book. Access full book title Scenario Selection with Lasso Regression for the Valuation of Variable Annuity Portfolios by Hang Nguyen. Download full books in PDF and EPUB format.
Author: Hang Nguyen
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Variable annuities (VAs) are increasingly becoming popular insurance products in many developed countries which provide guaranteed forms of income depending on the performance of the equity market. Insurance companies often hold large VA portfolios and the associated valuation of such portfolios for hedging purposes is a very time-consuming task. There have been several studies focusing on inventing techniques aimed at reducing the computational time including the selection of representative VA contracts and the use of a metamodel to estimate the values of all contracts in the portfolio. In addition to the selection of representative contracts, this paper proposes using LASSO regression to select a set of representative scenarios, which in turn allows for the set of representative contracts to expand without significant increase in computational load. The proposed approach leads to a remarkable improvement in the computational efficiency and accuracy of the metamodel.
Author: Hang Nguyen
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Variable annuities (VAs) are increasingly becoming popular insurance products in many developed countries which provide guaranteed forms of income depending on the performance of the equity market. Insurance companies often hold large VA portfolios and the associated valuation of such portfolios for hedging purposes is a very time-consuming task. There have been several studies focusing on inventing techniques aimed at reducing the computational time including the selection of representative VA contracts and the use of a metamodel to estimate the values of all contracts in the portfolio. In addition to the selection of representative contracts, this paper proposes using LASSO regression to select a set of representative scenarios, which in turn allows for the set of representative contracts to expand without significant increase in computational load. The proposed approach leads to a remarkable improvement in the computational efficiency and accuracy of the metamodel.
Author: Guojun Gan
Publisher: CRC Press
ISBN: 1000651010
Category : Mathematics
Languages : en
Pages : 196
Get Book Here
Book Description
This book is devoted to the mathematical methods of metamodeling that can be used to speed up the valuation of large portfolios of variable annuities. It is suitable for advanced undergraduate students, graduate students, and practitioners. It is the goal of this book to describe the computational problems and present the metamodeling approaches in a way that can be accessible to advanced undergraduate students and practitioners. To that end, the book will not only describe the theory of these mathematical approaches, but also present the implementations.
Author: Shuai Yang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Variable annuities (VAs) are equity-linked annuities with embedded investment guarantees. Their long-term security and tax deferred features have made them one of the major insurance products in the world. Nowadays, many insurance companies are managing large VA portfolios that contain hundreds of thousands policies. Since most of the VA contributions are invested in the equity market, the insurance companies are exposed to significant market risks and risk managing the VA liabilities has become the central task. In practice, the stochastic-on-stochastic nested simulation is commonly used for VA portfolio valuation and risk management. The path-dependency of the embedded guarantees and the non-homogeneity of the VA policies make the nested simulation algorithm extremely complex and time-consuming to run. As a result, timely managing the portfolio risks becomes a major challenge to the insurance companies. The complexity of the nested simulation algorithm depends directly on three components: the number of policies, the number of outer-loop simulation, and the number of inner-loop simulation. In this thesis, we incorporate the idea of surrogate modelling to the nested simulation algorithm such that all of the input dimensions are reduced. The surrogate models act as proxies to approximate the input/output relationships. Since only a few input points are needed in order to identify the surrogate models, the simulation time could be shortened significantly. The key feature of the proposed algorithm is that the methodologies for selecting the inputs are theoretically justifiable from the statistical properties of the surrogate models. As a result, a robust performance can be ensured for the proposed algorithm in different context. Specifically, we introduce a model-assisted estimation framework with balanced sampling to reduce the number of policies, and a spline regression framework with scenario clustering to reduce the number of outer-/inner-loops. The proposed algorithm is applied to perform various valuations for large synthetic VA portfolios such as calculating the predictive liability distribution, the portfolio Greeks, and the regulatory capital requirement with dynamic hedging. The efficiency and the robustness of the algorithm are demonstrated through numerical studies on a number of uniform/non-uniform large synthetic VA portfolios and economics models.
Author: Ruihong Jiang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
A computationally appealing methodology for the valuation of large variable annuities portfolios is a metamodelling framework that evaluates a small set of representative contracts, fits a predictive model based on these computed values, and then extrapolates the model to estimate the values of the remaining contracts. This paper proposes a new two-phase procedure for selecting representative contracts. The representatives from the first phase are determined using contract attributes as in existing metamodelling approaches, but those in the second phase are chosen by utilizing the information contained in the values of the representatives from the first phase. Two numerical studies confirm that our two-phase selection procedure improvesupon conventional approaches from the existing literature.
Author: Guojun Gan
Publisher: CRC Press
ISBN: 1351166581
Category : Mathematics
Languages : en
Pages : 169
Get Book Here
Book Description
This book is devoted to the mathematical methods of metamodeling that can be used to speed up the valuation of large portfolios of variable annuities. It is suitable for advanced undergraduate students, graduate students, and practitioners. It is the goal of this book to describe the computational problems and present the metamodeling approaches in a way that can be accessible to advanced undergraduate students and practitioners. To that end, the book will not only describe the theory of these mathematical approaches, but also present the implementations.
Author: Guojun Gan
Publisher:
ISBN:
Category :
Languages : en
Pages : 28
Get Book Here
Book Description
Metamodeling techniques have recently been proposed to address the computational issues related to the valuation of large portfolios of variable annuity contracts. However, it is extremely difficult, if not impossible, for researchers to obtain real datasets from insurance companies in order to test their metamodeling techniques on such real datasets and publish the results in academic journals. Even if a researcher can obtain real datasets from insurance companies, it is difficult for the re- searcher to share the datasets with the public at large. To facilitate the development and dissemination of research related to the efficient valuation of large variable annuity portfolios, this paper creates a large synthetic portfolio of variable annuity contracts based on the properties of real portfolios of variable annuities and implements a Monte Carlo simulation engine for valuing the synthetic portfolio. In addition, this paper develops benchmark datasets of fair market values and Greeks, which are important quantities for managing the financial risks associated with variable annuities. The resulting datasets provide researchers with a common basis for testing and comparing the performance of various metamodeling techniques.
Author: Guojun Gan
Publisher:
ISBN:
Category :
Languages : en
Pages : 19
Get Book Here
Book Description
Variable annuities contain complex guarantees, whose fair market value cannot be calculated in closed form. To value the guarantees, insurance companies rely heavily on Monte Carlo simulation, which is extremely computationally demanding for large portfolios of variable annuity policies. Metamodeling approaches have been proposed to address these computational issues. An important step of metamodeling approaches is the experimental design that selects a small number of representative variable annuity policies for building metamodels. In this paper, we compare empirically several multivariate experimental design methods for the GB2 regression model, which has been recently discovered to be an attractive model to estimate the fair market value of variable annuity guarantees. Among the experimental design methods examined, we found that the data clustering method and the conditional Latin hypercube sampling method produce the most accurate results.
Author: Thorsten Moenig
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
The valuation of variable annuity (VA) portfolios presents major challenges for life insurers. Recent studies propose approximation methods based on selecting a few representative guarantees. In contrast, I present a "bottom-up" valuation approach using recursive dynamic programming (RDP). An in-depth numerical analysis shows that the RDP estimation is able to value a large VA portfolio with a high degree of accuracy and within a few seconds--even under stochastic interest rates and volatility--since the heavy computational burden can be fully front-loaded (in a one-time effort at the guarantee's pricing stage). The RDP approach outperforms competing methods in both speed and accuracy and is thus ideally suited for various VA-related applications, including the computation of GAAP reserves, statutory reserves and capital requirements, as well as to determine the insurer's hedging position. Moreover, RDP can naturally incorporate optimal policyholder behavior into the insurer's valuation.
Author: Guojun Gan
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
Get Book Here
Book Description
Metamodels, which simplify the simulation models used in the valuation of large variable annuity portfolios, have recently increased in popularity. The ordinary kriging and the GB2 regression models are examples of metamodels used to predict fair market values of variable annuity guarantees. It is well known that the distribution of fair market values is highly skewed. Ordinary kriging does not fit well skewed data but it depends only on a few parameters that can be estimated straightforwardly. GB2 regression can handle skewed data but its parameter estimation can be quite challenging. In this paper, we explore the rank order kriging method, which can handle highly skewed data and depends only on a single parameter, for the valuation of large variable annuity portfolios. Our numerical results demonstrate that the rank order kriging method performs remarkably well in terms of fitting the skewed distribution and producing accurate estimates of fair market values at the portfolio level.
Author: Wenchu Li
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
This dissertation provides a comprehensive and practical analysis of basis risk in the U.S. variable annuity market and examines effective fund mapping strategies to mitigate the level of basis risk while controlling for the associated transaction costs. Variable annuities are personal savings and investment products with long-term guarantees that expose life insurers to extensive financial risks. Liabilities associated with VA guarantees are the largest liability component faced by U.S. life insurers and have raised concerns to VA providers and regulators. And the hedging performance of these guarantee liabilities is impeded by the existence of basis risk. I look into 1,892 registered VA-underlying mutual funds and two VA separate accounts to estimate the basis risk faced by U.S. VA providers at the individual fund level and the separate account level. To evaluate the degree to which basis risk can be mitigated, I consider various proxy instrument sets and assess different variable selection models. The LASSO regression is shown to be most effective at identifying the most suitable (combination of) mapping instruments that minimize basis risk, compared to other test-based and screening-based models. I supplement it with the Sure Independence Screening (SIS) procedure to further limit the number of instruments requested in the hedging strategies, and modify it by introducing the diff LASSO regression to restrict the changes in instrument allocations across rebalancing periods and, therefore, control for transaction costs. I show that VA providers can reduce their exposure to basis risk by applying data analytic techniques in their mapping process, by hedging with ETFs instead of futures contracts, and through diversification at the separate account level. Combining the traditional fund mapping method with the machine learning algorithm, the proposed portfolio mapping strategy is efficient at reducing basis risk in VA separate accounts while controlling for the tractability and transaction costs of the mapping and hedging procedure, and is practical to incorporate newly-developed VA funds, as well as the varying compositions of separate accounts. Overall, this study presents that U.S. VA providers have the ability to mitigate basis risk to a greater extent than the limited literature on this topic has suggested.
