Mean-variance Asset-liability Management Research Articles

Mean-variance asset-liability management under CIR interest rate and the family of 4/2 stochastic volatility models with derivative trading

<p style='text-indent:20px;'>This paper investigates the effects of derivative trading on the performance of asset-liability management in the presence of stochastic interest rate and stochastic volatility under the mean-variance criterion. Specifically, the asset-liability manager can invest not only in a money market account, a zero-coupon (rollover) bond, and a stock index but also in stock derivatives. It is assumed that the interest rate follows a Cox-Ingersoll-Ross (CIR) process, and the instantaneous variance of the stock index is governed by the family of 4/2 stochastic volatility models, which embraces the Heston model and 3/2 model, as particular cases. By solving a system of three backward stochastic differential equations, closed-form expressions for the optimal strategies and optimal value functions are derived in two cases: with and without the stock derivatives. Moreover, we consider the special cases without random liabilities. Numerical examples are provided to illustrate theoretical results and explore the effects of derivative trading on efficient frontiers.</p>

Mean-field formulation for mean-variance asset-liability management with cash flow under an uncertain exit time

Abstract The asset-liability management problem with cash flow under an uncertain exit time has been investigated in this article, which is based on the fundamental framework of the mean-variance model in the multi-period version. The liability and random cash flow will affect asset optimization, while the investor may be forced to withdraw from investments with a random probability at each period in our model. The closed-form expressions for the mean-variance optimal portfolio selection and its corresponding efficient frontier are obtained by employing the mean-field formulation and dynamic programming approach. Moreover, some numerical examples are provided to illustrate the validity and accuracy of the theoretical results.

The Study of Mean-Variance Risky Asset Management with State-Dependent Risk Aversion under Regime Switching Market

How do investors require a distribution of the wealth among multiple risky assets while facing the risk of the uncontrollable payment for random liabilities? To cope with this problem, firstly, this paper explores the approach of asset-liability management under the state-dependent risk aversion with only risky assets, which has been considered under a continuous-time Markov regime-switching setting. Next, based on this realistic modelling, an extended Hamilton-Jacob-Bellman (HJB) system has been necessarily established for solving the optimization problem of asset-liability management. It has been derived closed-form analytical expressions applied in the time-inconsistent investment with optimal control theory to see that happens to the optimal value of the function. Ultimately, numerical examples presented with comparisons of the analytical results under different market conditions are exposed to analyse numerically the developed mean variance asset liability management strategy. We find that our proposed model can explain the financial phenomena more effectively and accurately.

Mean-Variance Asset-Liability Management in a Non-Markovian Regime-Switching Jump-Diffusion Market with Random Horizon

This paper investigates the problem of mean-variance asset-liability management (ALM) in a market where the dynamics of assets are non-Markovian regime-switching models driven by a Brownian motion, a Poisson random measure and a continuous time finite-state Markov chain. It is assumed that the time horizon is uncertain relying not only on asset prices and liability values, but also on other factors. The insurer aims to minimize the variance of the terminal surplus given an expected terminal surplus subject to the risk of paying out random liabilities of an extensive Cramer-Lundberg model. By further developing the solvability of a linear backward stochastic differential equation (BSDE) with two types of jumps, namely jumps modelled by a Poisson random measure and by basic martingales related to a Markov chain, closed-form expressions for both the efficient strategy and the efficient frontier are obtained and represented by unique solutions to several relevant BSDEs.

Mean-variance equilibrium asset-liability management strategy with cointegrated assets

This paper investigates asset-liability management problems in a continuous-time economy. When the financial market consists of cointegrated risky assets, institutional investors attempt to make profit from the cointegration feature on the one hand, while on the other hand they need to maintain a stable surplus level, that is, the company’s wealth less its liability. Challenges occur when the liability is random and cannot be fully financed or hedged through the financial market. For mean–variance investors, an additional concern is the rational time-consistency issue, which ensures that a decision made in the future will not be restricted by the current surplus level. By putting all these factors together, this paper derives a closed-form feedback equilibrium control for time-consistent mean–variance asset-liability management problems with cointegrated risky assets. The solution is built upon the Hamilton–Jacobi–Bellman framework addressing time inconsistency. doi: 10.1017/S1446181120000164

Open-loop equilibrium strategy for mean-variance asset-liability management with margin requirements

This paper considers a mean-variance asset-liability management problem in which short-selling is allowed, but accompanied by margin requirements. This is a mean-variance problem with a non linear state process. We derive a sufficient condition and a necessary condition for the time-consistent equilibrium strategy by using a system of forward backward stochastic differential equations. By decoupling this system, we obtain the unique equilibrium strategy. As a byproduct, we also get the equilibrium strategy for the mean-variance asset-liability management problem under short-selling prohibition.

Better than optimal mean–variance portfolio policy in multi-period asset–liability management problem

When the wealth is larger than some threshold in multi-period mean–variance asset–liability management, the pre-committed policy is no longer mean–variance efficient policy for the remaining investment horizon. To revise the policy, by relaxing self-financing constraint and allowing to withdraw some wealth, we derive a new dominating policy, which is better than the pre-committed policy. The revised policy can achieve the same mean–variance pairs attained by the pre-committed policy, and yields a nonnegative free cash flow stream over the investment horizon.

Mean-variance asset-liability management with inside information

This paper studies an asset-liability management (ALM) problem under mean-variance criterion with inside information. The asset-liability manager is allowed to invest in a financial market composed of a bond and a stock. The stock price process is governed by a diffusion process with random parameters. The uncontrolled liability process is described by a general diffusion process with hedgeable risks and unhedgeable risks. We model the inside information by a general random variable related to the future values of financial assets and liabilities. By using the Donsker Delta functional technique and the BSDE method, we derive the analytic expressions of efficient strategy and efficient frontier. To illustrate the general result, an example is provided in which the efficient strategy and efficient frontier are obtained in closed form. The comparison of efficient frontiers with and without inside information demonstrates that taking advantage of inside information can improve the efficient frontier.

Open-loop equilibrium strategy for mean–variance asset–liability management portfolio selection problem with debt ratio

In this study, we consider a time-consistent mean–variance asset–liability management portfolio selection problem in which the liability is controllable. The objective is to find an equilibrium investment strategy and an equilibrium debt ratio in the financial market consisting of one risk-free asset and one risky asset. By using forward backward stochastic differential equations (FBSDEs), we derive a sufficient condition and a necessary condition for the open-loop equilibrium strategies. The uniqueness of the strategies is also provided. Furthermore, to illustrate our results, we provide numerical examples to show how the parameters impact on the equilibrium strategies and the corresponding efficient frontier.

Mean-variance asset–liability management with partial information and uncertain time horizon

ABSTRACT This paper studies a mean-variance asset–liability management (ALM) problem with uncertain time horizon and partial information. The ALM can invest in an incomplete financial market consisting of one riskless asset and n risky stocks. The stocks price process is described by a multidimensional diffusion process with random coefficients. The uncontrollable liability process is modelled by a general diffusion process with hedgeable risks and unhedgeable risks. The uncertainty of the time horizon is assumed to come from randomness of financial assets and the liability and some other stochastic factors. The ALM may get only partial information about the liability. We derive efficient strategies and efficient frontiers in terms of the solutions of two BSDEs under complete and partial information. The closed-form expressions of efficient strategies and efficient frontiers are obtained under some special cases.

MEAN–VARIANCE EQUILIBRIUM ASSET-LIABILITY MANAGEMENT STRATEGY WITH COINTEGRATED ASSETS

AbstractThis paper investigates asset-liability management problems in a continuous-time economy. When the financial market consists of cointegrated risky assets, institutional investors attempt to make profit from the cointegration feature on the one hand, while on the other hand they need to maintain a stable surplus level, that is, the company’s wealth less its liability. Challenges occur when the liability is random and cannot be fully financed or hedged through the financial market. For mean–variance investors, an additional concern is the rational time-consistency issue, which ensures that a decision made in the future will not be restricted by the current surplus level. By putting all these factors together, this paper derives a closed-form feedback equilibrium control for time-consistent mean–variance asset-liability management problems with cointegrated risky assets. The solution is built upon the Hamilton–Jacobi–Bellman framework addressing time inconsistency.

Time-consistent strategy for a multi-period mean-variance asset-liability management problem with stochastic interest rate

<p style='text-indent:20px;'>In this paper, we investigate a multi-period mean-variance asset-liability management problem with stochastic interest rate and seek its time-consistent strategy. The financial market is assumed to be composed of one risk-free asset and multiple risky assets, and the stochastic interest rate is characterized by the discrete-time Vasicek model proposed by Yao et al. (2016a)[<xref ref-type="bibr" rid="b38">38</xref>]. We regard this problem as a non-cooperative game whose equilibrium strategy is the desired time-consistent strategy. We derive the analytical expressions of the equilibrium strategy, the equilibrium value function and the equilibrium efficient frontier by the extended Bellman equation. Some special cases of our model are discussed, and some properties of our equilibrium strategy, including a two-fund separation theorem, are proposed. Finally, a numerical example with real data is given to illustrate our theoretical results.

Mean-variance asset-liability management with affine diffusion factor process and a reinsurance option

ABSTRACTThis paper considers an optimal asset-liability management (ALM) problem for an insurer under the mean-variance criterion. It is assumed that the value of liabilities is described by a geometric Brownian motion (GBM). The insurer's surplus process is modeled by a general jump process generated by a marked point process. The financial market consists of one risk-free asset and n risky assets with the risk premium relying on an affine diffusion factor process. By transferring a proportion of insurance risk to a reinsurer and investing the surplus into the financial market, the insurer aims to maximize the expected terminal net wealth and, at the same time, minimize the corresponding variance of the terminal net wealth. By using a backward stochastic differential equation (BSDE) approach, closed-form expressions for both the efficient strategy and efficient frontier are derived. To illustrate the main results, we study an example with the Heston stochastic volatility (SV) model and numerically analyze the economic behavior of the efficient frontier. Finally, a generalization of the Mutual Fund Theorem is obtained.

Continuous-time mean-variance asset-liability management with stochastic interest rates and inflation risks

This paper investigates a continuous-time Markowitz mean-variance asset-liability management (ALM) problem under stochastic interest rates and inflation risks. We assume that the company can invest in $n + 1$ assets: one risk-free bond and $n$ risky stocks. The risky stock's price is governed by a geometric Brownian motion (GBM), and the uncontrollable liability follows a Brownian motion with drift, respectively. The correlation between the risky assets and the liability is considered. The objective is to minimize the risk (measured by variance) of the terminal wealth subject to a given expected terminal wealth level. By applying the Lagrange multiplier method and stochastic control approach, we derive the associated Hamilton-Jacobi-Bellman (HJB) equation, which can be converted into six partial differential equations (PDEs). The closed-form solutions for these six PDEs are derived by using the homogenization approach and the variable transformation technique. Then the closed-form expressions for the efficient strategy and efficient frontier are obtained. In addition, a numerical example is presented to illustrate the results.

Mean–Variance Asset–Liability Management Problem Under Non-Markovian Regime-Switching Models

In this paper, we study an asset–liability management problem under a mean–variance criterion with regime switching. Unlike previous works, the dynamics of assets and liability are described by non-Markovian regime-switching models in the sense that all the model parameters are predictable with respect to the filtration generated jointly by a Markov chain and a Brownian motion. The problem is solved with the aid of backward stochastic differential equations (BSDEs) and bounded mean oscillation martingales. An efficient strategy and an efficient frontier are obtained and represented by unique solutions to several relevant BSDEs. We show that the optimal capital structure can be achieved when the initial asset value is expressed by a linear combination of the initial liability and the expected surplus. It is further found that a mutual fund theorem holds not only for the efficient strategy, but also for the optimal capital structure.

Optimal dynamic mean-variance asset-liability management under the Heston model

This paper studies a continuous-time mean-variance asset-liability management problem under the Heston model. Specifically, an asset-liability manager is allowed to invest in a risk-free asset and a risky asset whose price process is governed by the Heston model. By applying the Lagrange duality theorem and stochastic control theory, we derive the closed-form expressions of the efficient investment strategy and the efficient frontier. Moreover, we provide numerical experiments to analyze the sensitivity of the efficient frontier with respect to the relevant parameters in the Heston model.

Dynamic derivative-based investment strategy for mean–variance asset–liability management with stochastic volatility

This paper considers the derivative-based optimal investment strategies for an asset–liability management (ALM) problem under the mean–variance criterion in the presence of stochastic volatility. Specifically, an asset–liability manager is allowed to invest not only in a risk-free bond and a stock, but also in a derivative, whose price depends on the underlying price of the stock and its volatility. By solving a system of two backward stochastic differential equations, we derive the explicit expressions of the efficient strategies and the corresponding efficient frontiers in two cases, with and without the derivative asset. Moreover, we consider the special case of an optimal investment problem with no liability commitment, which is also not studied in the literature. We also provide some numerical examples to illustrate our results and find that the efficient frontier of the case with the derivative is always better than that of the case without the derivative. Moreover, under the same variance, the expectation of the case with the derivative can reach up to as twice as that of the case without the derivative in some situations.

Time-consistent mean–variance asset–liability management with random coefficients

In this paper, we aim to find a time-consistent open-loop equilibrium strategy for the asset–liability management problem under mean–variance criterion. The financial market consists of a bank account and m stocks whose prices are modeled by geometric Brownian motions. The liability of the investor is uncontrollable and modeled by another geometric Brownian motion which is correlated to the stock prices. First, we provide a sufficient condition for the equilibrium strategy, which involves a system of FBSDEs. Second, by solving these FBSDEs, we obtain an equilibrium strategy in a linear feedback form of the surplus and the liability. Finally, we consider a Markovian case where the interest rate is given by the Vasiček model.

Mean-Variance Asset Liability Management with State-Dependent Risk Aversion

ABSTRACTThis article investigates the asset liability management problem with state-dependent risk aversion under the mean-variance criterion. The investor allocates the wealth among multiple assets including a risk-free asset and multiple risky assets governed by a system of geometric Brownian motion stochastic differential equations, and the investor faces the risk of paying uncontrollable random liabilities. The state-dependent risk aversion is taken into account in our model, linking the risk aversion to the current wealth held by the investor. An extended Hamilton-Jacobi-Bellman system is established for the optimization of asset liability management, and by solving the extended Hamilton-Jacobi-Bellman system, the analytical closed-form expressions for the time-inconsistent optimal investment strategies and the optimal value function are derived. Finally, numerical examples are presented to illustrate our results.

Mean–variance asset–liability management under constant elasticity of variance process

This paper investigates a mean–variance asset–liability management (ALM) problem under the constant elasticity of variance (CEV) process. The company can invest in n+1 assets: one risk-free bond and n risky stocks. The uncontrollable liability process is modelled by a geometric Brownian motion. The feasibility is studied and potential optimal portfolio is proven to be admissible. We derive the efficient frontier and efficient feedback portfolio in terms of the solutions of two backward stochastic differential equations (BSDEs), which do not admit analytical solutions in general. The closed form solutions are obtained under some special cases. Applying the Monte Carlo simulation, we provide several numerical examples to demonstrate how the efficient frontier is influenced by the relevant parameters.