Asset Liability Management in Insurance Companies and Banks: Quantitative Models

2010 ◽  
Author(s):  
Rossano Giandomenico
Keyword(s):  
Insurance Companies ◽  
Asset Liability Management ◽  
Quantitative Models ◽  
Liability Management

OPTIMAL PORTFOLIOS OF CORPORATE BONDS AND HOLD TO MATURITY STRATEGIES

2015 ◽  
Vol 10 (02) ◽  
pp. 1550010
Author(s):  
YAACOV KOPELIOVICH
Keyword(s):  
Corporate Bond ◽  
Insurance Companies ◽  
Asset Liability Management ◽  
Optimal Portfolios ◽  
Optimal Weights ◽  
Liability Management ◽  
Simulation Based ◽  
Copula Approach ◽  
Bond Portfolios ◽  
Bond Indices

In this paper, we initiate a research on optimal bond portfolios, that are held to their maturity. We solve the problem analytically for log utility investor in the case of one risky corporate asset. We compare the behavior of these portfolios to equally weighted and portfolios with randomly selected weights. We apply simulation based on Vasicek’s copula approach to derive optimal weights for a corresponding problem involving more than one corporate bond. Further we discover that these portfolios outperform naive investment in constant maturity (CCM) bond indices with a similar maturity horizon. We explain possible application of our findings to boost asset liability management (ALM) strategies for pensions and insurance companies.

GPU parallel implementation for asset-liability management in insurance companies

2018 ◽  
Vol 24 ◽  
pp. 232-254 ◽  
Author(s):  
José L. Fernández ◽  
Ana M. Ferreiro-Ferreiro ◽  
José A. García-Rodríguez ◽  
Carlos Vázquez
Keyword(s):  
Parallel Implementation ◽  
Insurance Companies ◽  
Asset Liability Management ◽  
Liability Management

scholarly journals Between ℙ and ℚ: The ℙℚ Measure for Pricing in Asset Liability Management

2018 ◽  
Vol 11 (4) ◽  
pp. 67 ◽  
Author(s):  
Marcel van Dijk ◽  
Cornelis de Graaf ◽  
Cornelis Oosterlee
Keyword(s):  
Option Pricing ◽  
Real World ◽  
Implied Volatility ◽  
Insurance Companies ◽  
Asset Liability Management ◽  
Pricing Models ◽  
Liability Management ◽  
Market Variables ◽  
Implied Volatility Surfaces ◽  
The Impact

Insurance companies issue guarantees that need to be valued according to the market expectations. By calibrating option pricing models to the available implied volatility surfaces, one deals with the so-called risk-neutral measure Q , which can be used to generate market consistent values for these guarantees. For asset liability management, insurers also need future values of these guarantees. Next to that, new regulations require insurance companies to value their positions on a one-year horizon. As the option prices at t = 1 are unknown, it is common practice to assume that the parameters of these option pricing models are constant, i.e., the calibrated parameters from time t = 0 are also used to value the guarantees at t = 1 . However, it is well-known that the parameters are not constant and may depend on the state of the market which evolves under the real-world measure P . In this paper, we propose improved regression models that, given a set of market variables such as the VIX index and risk-free interest rates, estimate the calibrated parameters. When the market variables are included in a real-world simulation, one is able to assess the calibrated parameters (and consequently the implied volatility surface) in line with the simulated state of the market. By performing a regression, we are able to predict out-of-sample implied volatility surfaces accurately. Moreover, the impact on the Solvency Capital Requirement has been evaluated for different points in time. The impact depends on the initial state of the market and may vary between −46% and +52%.

Long‐Term Economic and Market Trends and Their Implications for Asset/Liability Management of Insurance Companies

2003 ◽  
Vol 4 (2) ◽  
pp. 5-18 ◽  
Author(s):  
CHRISTIAN GILLES ◽  
LARRY RUBIN ◽  
JOHN RYDING ◽  
LEO M. TILMAN ◽  
AJAY RAJADHYAKSHA
Keyword(s):  
Insurance Companies ◽  
Asset Liability Management ◽  
Liability Management ◽  
Market Trends
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