Regression-based Monte Carlo methods for stochastic control models: Variable annuities with lifelong guarantees
نویسندگان
چکیده
We present the regression-based Monte Carlo simulation algorithms for solving the stochastic control models associated with pricing and hedging of the Guaranteed Lifelong Withdrawal Benefit (GLWB) in variable annuities, where the dynamics of the underlying fund value is assumed to evolve according to the stochastic volatility model. The GLWB offers a lifelong withdrawal benefit even when the policy account value becomes zero while the policyholder remains alive. Upon death, the remaining account value will be paid to the beneficiary as a death benefit. The bang-bang control strategy analyzed under the assumption of maximization of the policyholder’s expected cash flow reduces the strategy space of optimal withdrawal policies to three choices: zero withdrawal, withdrawal at the contractual amount or complete surrender. The impact on the GLWB value under various withdrawal behaviors of the policyholder is examined. We also analyze the pricing properties of GLWB subject to different model parameter values and structural features. JEL classification: G22, C50
منابع مشابه
Gas Storage and Supply Guarantees: An Optimal Switching Approach
We consider the valuation of gas storage on finite horizon. Focusing on the timing optionality of storage we construct a stochastic control model that reduces to solving an optimal switching problem with inventory. Extending the methodology from Carmona and Ludkovski (2005), we then construct a robust numerical scheme based on Monte Carlo regressions. The idea is to simultaneously approximate t...
متن کاملStochastic Assessment of Voltage Sags in Distribution Networks
This paper compares fault position and Monte Carlo methods as the most common methods in stochastic assessment of voltage sags. To compare their abilities, symmetrical and unsymmetrical faults with different probability distribution of fault positions along the lines are applied in a test system. The voltage sag magnitude in different nodes of test system is calculated. The problem with the...
متن کاملA Spatial Interpolation Framework for Efficient Valuation of Large Portfolios of Variable Annuities
Variable Annuity (VA) products expose insurance companies to considerable risk because of the guarantees they provide to buyers of these products. Managing and hedging these risks requires insurers to find the value of key risk metrics for a large portfolio of VA products. In practice, many companies rely on nested Monte Carlo (MC) simulations to find key risk metrics. MC simulations are comput...
متن کاملA Monte Carlo-Based Search Strategy for Dimensionality Reduction in Performance Tuning Parameters
Redundant and irrelevant features in high dimensional data increase the complexity in underlying mathematical models. It is necessary to conduct pre-processing steps that search for the most relevant features in order to reduce the dimensionality of the data. This study made use of a meta-heuristic search approach which uses lightweight random simulations to balance between the exploitation of ...
متن کاملVariance Reduction in Stochastic Gradient Langevin Dynamics
Stochastic gradient-based Monte Carlo methods such as stochastic gradient Langevin dynamics are useful tools for posterior inference on large scale datasets in many machine learning applications. These methods scale to large datasets by using noisy gradients calculated using a mini-batch or subset of the dataset. However, the high variance inherent in these noisy gradients degrades performance ...
متن کامل