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Journal articles on the topic 'Model of asset and liability management'

Author: Grafiati

Published: 28 May 2022

Last updated: 30 July 2025

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1

Izadbakhshe, Hamid Reza, Zadeh Ahmad Soleiman, Ardakani Hamed Davari, and Masouleh Marzieh Zarinbal. "Asset and Liability Management in Pension Funds with a Systemic Approach in a Fuzzy Environment." Quarterly Journal of Economic Modeling Research 8, no. 29 (2017): 201–39. https://doi.org/10.5281/zenodo.14002214.

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Since pension funds are among the important and influential institutions affecting the economic and social conditions of society, a thorough study and examination of the issues they face seems inevitable. Asset and liability management is a useful and effective tool for analyzing and understanding pension funds and their stakeholders. This paper aims to identify the key factors influencing asset and liability management in pension funds and analyze them using system dynamics.  Subsequently, using a fuzzy inference system, the significant risks affecting asset and liability management are

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2

Kusy, M. I., and W. T. Ziemba. "A Bank Asset and Liability Management Model." Operations Research 34, no. 3 (1986): 356–76. http://dx.doi.org/10.1287/opre.34.3.356.

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Ma, Hui-qiang, Meng Wu, and Nan-jing Huang. "Time Consistent Strategies for Mean-Variance Asset-Liability Management Problems." Mathematical Problems in Engineering 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/709129.

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This paper studies the optimal time consistent investment strategies in multiperiod asset-liability management problems under mean-variance criterion. By applying time consistent model of Chen et al. (2013) and employing dynamic programming technique, we derive two-time consistent policies for asset-liability management problems in a market with and without a riskless asset, respectively. We show that the presence of liability does affect the optimal strategy. More specifically, liability leads a parallel shift of optimal time-consistent investment policy. Moreover, for an arbitrarily risk ave

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4

Dempster, M. A. H., and E. A. Medova. "Asset liability management for individual households." British Actuarial Journal 16, no. 2 (2011): 405–39. http://dx.doi.org/10.1017/s135732171100016x.

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AbstractPersonal finance is a challenging topic which can benefit from a scientific approach to individual financial planning. This paper presents an individual asset liability management (iALM) model for life cycle planning which uses the methodology of dynamic stochastic optimisation and incorporates ideas from both classical and behavioural finance. Its implementation is in the form of a decision support tool for use by financial advisers or wealth managers. The investment universe is given by a set of indices for major asset classes and their returns are simulated forward over the lifetime

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5

Kramer, Bert, and Ton van Welie. "An asset liability management model for housing associations." Journal of Property Investment & Finance 19, no. 6 (2001): 453–71. http://dx.doi.org/10.1108/eum0000000006186.

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6

Satria, Indra. "PENGARUH MANAJEMEN LIKUIDITAS, MANAJEMEN ASET DAN MANAJEMEN UTANG TERHADAP LABA." Jurnal Economia 12, no. 1 (2016): 32. http://dx.doi.org/10.21831/economia.v12i1.9523.

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Abstrak: Pengaruh Manajemen Likuiditas, Manajemen Aset dan Manajemen Utang Terhadap Laba. Penelitian ini bertujuan untuk mengemukakan model regresi linier berganda yang dapat digunakan sebagai model penaksir terhadap laba. Penelitian dilakukan terhadap perusahaan porselin, keramik dan gelas yang listing di BEI pada periode 2009-2015, memunyai laporan keuangan auditan dan memeroleh laba selama periode tersebut. Variabel independen dalam penelitian ini adalah Current Ratio (CR), Total Assets Turnover Ratio (TATO), dan Debt Ratio (DR). Ketiga variabel ini masing-masing digunakan sebagai proksi ma

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7

Li, Shuang, Yu Yang, Yanli Zhou, Yonghong Wu, and Xiangyu Ge. "The Study of Mean-Variance Risky Asset Management with State-Dependent Risk Aversion under Regime Switching Market." Journal of Function Spaces 2021 (November 20, 2021): 1–15. http://dx.doi.org/10.1155/2021/5476781.

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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

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8

Nguyen, Duc Thinh. "FACTORS AFFECTING THE ASSET-LIABILITY MANAGEMENT AT MILITARY COMMERCIAL JOINT STOCK BANK." International Journal of Professional Business Review 9, no. 10 (2024): e04913. http://dx.doi.org/10.26668/businessreview/2024.v9i10.4913.

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Objective: The article analyzes the impact of factors affecting the asset-liability management at Military commercial joint stock bank, providing more empirical evidence on factors affecting the asset-liability management at military commercial joint stock bank. Theoretical Framework: This paper uses model factors affecting the asset-liability management at Military commercial joint stock bank Method: The research method uses a questionnaire survey of managers and employees of Military commercial joint stock bank in ALCO, Market Risk Management Department, Risk Management Division, Capital and

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9

Tandy, Marvin, and Marcus Wono Setya Budhi. "Dynamical System Modeling in Asset and Liability Management." ITM Web of Conferences 75 (2025): 02009. https://doi.org/10.1051/itmconf/20257502009.

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Insurance companies must ensure a balance between the profits generated from their investment and the liabilities they owe to policyholders. This is widely known as asset and liability management (ALM). One important element of ALM involves forecasting the long-term financial status of the company. Therefore, a discrete time dynamical system is developed to illustrate the fluctuations in the financial components of an insurance company. Subsequently, simulations are conducted based on the constructed model for cases both with and without mortality. The model takes into account varying premium

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10

Trang, Nguyen Thi Thu, Nguyen Thuy Duong, and Pham Ngoc Binh. "The Impact of Asset-Liability Management on the Profitability of Listed Commercial Banks in Vietnam." International Journal of Economics and Financial Issues 14, no. 6 (2024): 369–78. http://dx.doi.org/10.32479/ijefi.17163.

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This paper investigates the effect of asset-liability management on the profitability of listed commercial banks in Vietnam, analyzing annual data from 2013 to 2023. The study uses VIF tests, Heteroskedasticity tests, Model Specification tests, and the Generalized Least Squares (GLS) model with the Modified Wald test to examine the data. The results reveal a positive correlation between bank asset management and annual GDP growth with profitability. Conversely, liability management and the year-on-year growth rate of total assets negatively impact profitability. Specifically, factors such as l

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11

Tanwar, Jyoti, Arun Kumar Vaish, and N. V. M. Rao. "MATHEMATICAL MODELING OF ASSET LIABILITY MANAGEMENT IN BANKS USING GOAL PROGRAMMING AND AHP." Indian Journal of Finance and Banking 4, no. 4 (2020): 1–19. http://dx.doi.org/10.46281/ijfb.v4i4.899.

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Asset Liability Management has gained popularity in the banking sector. Earlier banks focused on asset allocation, but now the management of assets and liabilities is equally essential. Asset liability management targets the optimum distribution of funds in assets and managing liabilities so that banks can earn higher profits and minimize risk. In this paper, the optimization of assets and liabilities of Indian banks has been concentrated using mathematical models. Combining the Analytical Hierarchy Process (AHP) and Goal Programming (GP) model has been used to solve the optimization problem.

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12

Ma, Hui-qiang, Meng Wu, and Nan-jing Huang. "A Random Parameter Model for Continuous-Time Mean-Variance Asset-Liability Management." Mathematical Problems in Engineering 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/687428.

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We consider a continuous-time mean-variance asset-liability management problem in a market with random market parameters; that is, interest rate, appreciation rates, and volatility rates are considered to be stochastic processes. By using the theories of stochastic linear-quadratic (LQ) optimal control and backward stochastic differential equations (BSDEs), we tackle this problem and derive optimal investment strategies as well as the mean-variance efficient frontier analytically in terms of the solution of BSDEs. We find that the efficient frontier is still a parabola in a market with random

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13

Boender, Guus C. E. "A hybrid simulation/optimisation scenario model for asset/liability management." European Journal of Operational Research 99, no. 1 (1997): 126–35. http://dx.doi.org/10.1016/s0377-2217(96)00387-6.

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14

Langen, Dieter. "A multi-objective decision model for bank asset/liability management." Mathematical and Computer Modelling 12, no. 10-11 (1989): 1419–35. http://dx.doi.org/10.1016/0895-7177(89)90379-8.

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15

Viswanathan, P. K., M. Ranganatham, and G. Balasubramanian. "Modeling asset allocation and liability composition for Indian banks." Managerial Finance 40, no. 7 (2014): 700–723. http://dx.doi.org/10.1108/mf-10-2013-0276.

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Purpose – Asset liability management is a multi-dimensional set of activities. Against this backdrop, the purpose of this paper is to build a goal programming model for optimally determining the asset allocation and liability composition for Indian Banks. Design/methodology/approach – The conceptual model framework has been developed and then tested for four banks that typically represent the Indian banking sector. Published balance sheet data were used for the model that span over 1995-2009. The veracity of the model has been tested in terms of its ability to project the optimum asset allocat

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16

Dash, Gordon, and Nina Kajiji. "A Nonlinear Goal Programming Model for Efficient Asset-Liability Management of Property-Liability Insurers." INFOR: Information Systems and Operational Research 43, no. 2 (2005): 135–56. http://dx.doi.org/10.1080/03155986.2005.11732722.

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17

Wijayanti, Hagni, Sudradjat Supian, Diah Chaerani, and Adibah Shuib. "Financial optimization modeling on asset liability management with weighted goal programming." Decision Science Letters 13, no. 4 (2024): 951–66. http://dx.doi.org/10.5267/j.dsl.2024.7.004.

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Asset Liability Management (ALM) can be overseen using financial ratios derived from financial statements. These statements provide a comprehensive picture of a company's status and necessitate analysis to evaluate performance. This research aims to analyze financial ratios to describe the financial condition, measure business development over time, and evaluate the achievement of the company's objectives. An optimization analysis of financial ratios is performed using the Weighted Goal Programming (WGP) model, which addresses multiple objectives by applying weights based on their priorities.

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18

AKINSELURE, Oluwafemi Philip, Tajudeen John AYOOLA, and Olateju Dolapo AREGBESOLA. "Moderating Effect of Board Characteristics on the Association between Asset Liability Management and Financial Performance of Commercial Banks in Nigeria." Theoretical and Practical Research in Economic Fields 15, no. 3 (2024): 589. http://dx.doi.org/10.14505/tpref.v15.3(31).07.

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Asset liability management and consistent improvement in financial performance are the responsibility of the Board of Directors of commercial banks, yet studies on the impact of asset liability management on the financial performance of commercial banks in Sub-Saharan Africa have excluded board characteristics variable from their statistical model. This study examines the moderating effect of board characteristics and asset liability management on the financial performance of commercial banks in Nigeria. Commercial banks. It was based on secondary data, obtained from annual reports of commerci

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19

OLAIYA, Kehinde Isiaq. "IMPACT OF UNDERWRITING AND FINANCIAL RATIOS ON PROFITABILITY: AN EMPIRICAL ANALYSIS OF INSURANCE FIRMS." Modern Management Review 30, no. 2 (2025): 113–27. https://doi.org/10.7862/rz.2025.mmr.12.

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This study examines factors influencing profitability in the insurance sector, focusing on financial indicators such as Return on Assets (ROA), Return on Equity (ROE), Asset Liability Ratio (ALR), Claims Ratio (CR), Expense Ratio (ER), Leverage (LEV), and Total Premium Earned (TPE). Using correlation analysis, unit root tests, and regression models, it evaluates their impact on financial performance. The results show that TPE positively affects ROA and ROE, highlighting the importance of premium growth. In contrast, CR, ER, and LEV negatively influence profitability, emphasizing the need for c

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20

Yudih, Sudirman, and Asyraf Mustamin. "The Influence of Asset and Liability Management on Dividend Policy and Firm Value of Listed Banking Companies in the Indonesia Stock Exchange." Jurnal Ilmiah Akuntansi Peradaban 10, no. 1 (2024): 110–28. http://dx.doi.org/10.24252/jiap.v10i1.44853.

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This study aims to examine the effect of asset and liability management on dividend policy and Firm value of listed banking companies in the Indonesia Stock Exchange. This study used panel data from banking statistics reports and annual IDX statistics. This research used Structural Equation Model as the data analysis. The results of the study found that, asset management has a positive and significant effect on dividend policy and firm value. Meanwhile, liability management has a negative and insignificant effect on dividend policy. and company value.

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21

Pan, Jian, Shengzhou Hu, and Xiangying Zhou. "Optimal investment strategy for asset-liability management under the Heston model." Optimization 68, no. 5 (2019): 895–920. http://dx.doi.org/10.1080/02331934.2018.1561691.

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22

SBARAGLIA, S., M. PAPI, M. BRIANI, M. BERNASCHI, and F. GOZZI. "A MODEL FOR THE OPTIMAL ASSET-LIABILITY MANAGEMENT FOR INSURANCE COMPANIES." International Journal of Theoretical and Applied Finance 06, no. 03 (2003): 277–99. http://dx.doi.org/10.1142/s0219024903001906.

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This paper is devoted to the formulation of a model for the optimal asset-liability management for insurance companies. We focus on a typical guaranteed investment contract, by which the holder has the right to receive after T years a return that cannot be lower than a minimum predefined rate rg. We take account of the rules that usually are imposed to insurance companies in the management of this funds as reserves and solvency margin. We formulate the problem as a stochastic optimization problem in a discrete time setting comparing this approach with the so-called hedging approach. The utilit

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23

Broeders, Dirk W. G. A., Kristy A. E. Jansen, and Bas J. M. Werker. "Pension fund's illiquid assets allocation under liquidity and capital requirements." Journal of Pension Economics and Finance 20, no. 1 (2020): 102–24. http://dx.doi.org/10.1017/s1474747219000398.

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AbstractDefined benefit pension funds invest in illiquid asset classes for return, diversification or liability hedging reasons. So far, little is known about factors influencing how much they invest in illiquid assets. We conjecture that liquidity and capital requirements are pivotal in this decision. Short-term pension payments and margining on derivative contracts generate liquidity requirements, while regulations impose capital requirements. Consistent with our model we empirically find that these requirements create a hump-shaped impact of liability duration on the fraction of risky asset

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24

Liu, Wei, Youfa Sun, and Xu Chen. "Mean-field formulation for mean-variance asset-liability management with cash flow under an uncertain exit time." Open Mathematics 20, no. 1 (2022): 24–37. http://dx.doi.org/10.1515/math-2022-0007.

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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 p

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25

Kosmidou, Kyriaki, and Constantin Zopounidis. "Combining Goal Programming Model With Simulation Analysis For Bank Asset Liability Management." INFOR: Information Systems and Operational Research 42, no. 3 (2004): 175–87. http://dx.doi.org/10.1080/03155986.2004.11732701.

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Peykani, Pejman, Mostafa Sargolzaei, Mohammad Hashem Botshekan, Camelia Oprean-Stan, and Amir Takaloo. "Optimization of Asset and Liability Management of Banks with Minimum Possible Changes." Mathematics 11, no. 12 (2023): 2761. http://dx.doi.org/10.3390/math11122761.

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Asset-Liability Management (ALM) of banks is defined as simultaneous planning of all bank assets and liabilities under different conditions and its purpose is to maximize profits and minimize the risks in banks by optimizing the parameters in the balance sheet. Most of the studies `and proposed models in the ALM field are based on an objective function that maximizes bank profit. It is not easy to apply changes in these models in order to reach the optimal values of the parameters in the balance sheet. In this article, an attempt has been made to propose a linear model using constraints to ach

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27

Tanwar, Jyoti, Arun Kumar Vaish, and NVM Rao. "OPTIMIZING BALANCE SHEET FOR BANKS IN INDIA USING GOAL PROGRAMMING." International Journal of Accounting & Finance Review 6, no. 2 (2021): 81–101. http://dx.doi.org/10.46281/ijafr.v6i2.1082.

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In earlier years, there was abundance of funds in banks in the form of demand and savings deposits. Hence, the focus of banks was mainly on asset management. But intense competition and volatility of interest rate due to banking reforms reduced the availability of low-cost funds and therefore, banks focused on liability management as well. These pressures call for structured and comprehensive measures and not just ad hoc action. This is how banks started to concentrate more on the management of both sides of the balance sheet. As a result, the concept of asset-liability management originated i

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AlArjani, Ali, and Teg Alam. "Lexicographic Goal Programming Model for Bank’s Performance Management." Journal of Applied Mathematics 2021 (November 12, 2021): 1–7. http://dx.doi.org/10.1155/2021/8011578.

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Any bank’s financial management is essential to preparing the assets and liabilities for multiple goals. In this paper, we develop an optimal bank model for the financial management department in the Kingdom of Saudi Arabia. The lexicographic goal programming model was used to formulate the banks’ performance management. In this study, the six goals of one of the leading banks in Saudi Arabia, namely, maximize asset, minimize liability, maximize equity, maximize operating income, maximize net income, and maximizing total goal achievements in the financial statement, were studied. To illustrate

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29

Hibiki, Norio, and Tadaaki Fukukawa. "Goal Programming Model Approach for Risk Management on Banking Based on Asset Liability Management (ALM)." Journal of the Operations Research Society of Japan 35, no. 4 (1992): 319–44. http://dx.doi.org/10.15807/jorsj.35.319.

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30

Kouwenberg, Roy. "Scenario generation and stochastic programming models for asset liability management." European Journal of Operational Research 134, no. 2 (2001): 279–92. http://dx.doi.org/10.1016/s0377-2217(00)00261-7.

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31

Klaassen, Pieter. "Financial Asset-Pricing Theory and Stochastic Programming Models for Asset/Liability Management: A Synthesis." Management Science 44, no. 1 (1998): 31–48. http://dx.doi.org/10.1287/mnsc.44.1.31.

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32

Chen, Ping, and Hailiang Yang. "Markowitz's Mean-Variance Asset–Liability Management with Regime Switching: A Multi-Period Model." Applied Mathematical Finance 18, no. 1 (2011): 29–50. http://dx.doi.org/10.1080/13504861003703633.

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Chen, Ping, Hailiang Yang, and George Yin. "Markowitz’s mean-variance asset-liability management with regime switching: A continuous-time model." Insurance: Mathematics and Economics 43, no. 3 (2008): 456–65. http://dx.doi.org/10.1016/j.insmatheco.2008.09.001.

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34

Hilli, Petri, Matti Koivu, Teemu Pennanen, and Antero Ranne. "A stochastic programming model for asset liability management of a Finnish pension company." Annals of Operations Research 152, no. 1 (2006): 115–39. http://dx.doi.org/10.1007/s10479-006-0135-3.

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35

Joshi, Mrs Snehal P., and Dr Reeta V. Sontakay. "Comparative Analysis of Asset Liability and Risk Management of Selected Urban Cooperative Banks in Nagpur Region using CAMEL Model." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (2018): 2029–36. http://dx.doi.org/10.31142/ijtsrd11590.

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Mukalazi, Herbert, ‪Torbjörn Larsson, Kasozi Juma, and Mayambala Fred. "Asset Liability Management for the Parliamentary Pension Scheme of Uganda by Stochastic Programming." Afrika Statistika 16, no. 2 (2021): 2689–715. http://dx.doi.org/10.16929/as/2021.2689.179.

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We develop a model for asset liability management of pension funds, which is solved by stochastic programming techniques. Using data provided by the Parliamentary Pension Scheme of Uganda, we obtain the optimal investment policies.Randomly sampled scenario trees using the mean, and covariance structure of the return distribution are used for generating the coefficients of the stochastic program. Liabilities are modelled by remaining years of life expectancy and guaranteed period for monthly pension.We obtain the funding situation of the scheme at each stage under three different asset investme

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Chaudhury, Rahul, and Sahidul Islam. "A Multi-Objective Risk Return Trade off Models for Banks: Fuzzy Programming Approach." Mathematical Modelling of Engineering Problems 8, no. 2 (2021): 179–88. http://dx.doi.org/10.18280/mmep.080203.

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The main focus of banking sector is on the risk management. Asset liability management (ALM) is one of the key processes to manage the risks. The objective of this paper is to develop a multi-objective asset liability optimization model for banks with the maximization of market value of equity and minimization of duration gap as the objective function. Several liquidity ratios, concept of duration and convexity are considered to manage the risk properly. Interest rate risk and liquidity risk are two major considerations in both the regulation and management of a bank. As we know that, with the

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Dutta, Goutam, Harish V. Rao, Sankarshan Basu, and Manoj Kr Tiwari. "Asset liability management model with decision support system for life insurance companies: Computational results." Computers & Industrial Engineering 128 (February 2019): 985–98. http://dx.doi.org/10.1016/j.cie.2018.06.033.

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Yang, Wen-ze, Xiao-ming Xu, and Yun-ze Cai. "Segmented dynamic optimization model for asset-liability management of commercial banks and its applications." Journal of Shanghai Jiaotong University (Science) 17, no. 1 (2012): 114–20. http://dx.doi.org/10.1007/s12204-012-1237-5.

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Chen, Fei. "THE IMPACT MODEL OF INTEREST RATE LIBERALIZATION REFORM ON THE PROFITABILITY OF STATE-OWNED COMMERCIAL BANKS: A CASE STUDY OF BANK C OF CHINA." EUrASEANs: journal on global socio-economic dynamics, no. 3(46) (May 13, 2024): 7–18. http://dx.doi.org/10.35678/2539-5645.3(46).2024.7-18.

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This paper explores the definition and development of interest rate marketization in China and its impact on the profitability of state-owned commercial banks. The reform, characterized by the People's Bank of China's gradual easing of interest rate controls and expansion of the benchmark interest rate's floating range, enhanced financial market flexibility and efficiency but challenged traditional banking profit models based on interest margins. Through qualitative case studies and thematic analysis of the Bank C (China), the study finds that Bank C effectively mitigated these challenges by o

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MARTELLINI, LIONEL, and VINCENT MILHAU. "Dynamic allocation decisions in the presence of funding ratio constraints." Journal of Pension Economics and Finance 11, no. 4 (2012): 549–80. http://dx.doi.org/10.1017/s1474747212000194.

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AbstractThis paper introduces a continuous-time allocation model for an investor facing stochastic liability commitments indexed with respect to inflation. In the presence of funding ratio constraints, the optimal policy is shown to involve dynamic allocation strategies that are reminiscent of portfolio insurance strategies, extended to an asset–liability management (ALM) context. Empirical tests suggest that their benefits are relatively robust with respect to changes in the objective function and the introduction of various forms of market incompleteness. We also show that the introduction o

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Dinarjito, Agung. "Penyertaan Modal Negara Pertumbuhan Aset Dan Kinerja Badan Usaha Milik Negara." E-Jurnal Akuntansi 28, no. 2 (2019): 1323. http://dx.doi.org/10.24843/eja.2019.v28.i02.p20.

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This study aims to examine whether State capital participation (PMN) and asset growth will affect the financial performance of State-Owned Enterprises (SOEs) in the year the addition of State capital participation. In addition, this study also examines whether PMN influences asset growth to see whether additional PMN provided by the Central Government is used to increase fixed assets in order to increase SOEs revenues. This research is a quantitative study using SOEs data in the form of a limited liability company (PT) that received PMN from 2014 to 2017. Research shows that PMN and asset grow

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Mishu, Tripathi. "A CRITICAL ASSESSMENT OF SELECTED PRIVATE AND PUBLIC SECTOR BANKS THROUGH ASSET LIABILITY MANAGEMENT." Anvesak 51, no. 2 (2021): 107–17. https://doi.org/10.5281/zenodo.10579118.

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<em>Asset-Liability Management (ALM) is a risk management technique used by banks and</em> <em>financial institutions to earn profits return while maintaining an appropriate balance between assets and</em> <em>liabilities. The major types of risks faced by banks are interest rate risk, liquidity risk, credit risk and</em> <em>market risk. The main aim of this study is to analyse the selected 2 public and 2 private commercial</em> <em>banks using Maturity Gap Analysis Model. The analysis shows the highest mismatch ratio is 4.66 of</em> <em>Axis Bank for the maturity bucket of over 3 years and u

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Chiu, Mei Choi, and Hoi Ying Wong. "Optimal Investment for Insurers with the Extended CIR Interest Rate Model." Abstract and Applied Analysis 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/129474.

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A fundamental challenge for insurance companies (insurers) is to strike the best balance between optimal investment and risk management of paying insurance liabilities, especially in a low interest rate environment. The stochastic interest rate becomes a critical factor in this asset-liability management (ALM) problem. This paper derives the closed-form solution to the optimal investment problem for an insurer subject to the insurance liability of compound Poisson process and the stochastic interest rate following the extended CIR model. Therefore, the insurer’s wealth follows a jump-diffusion

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Waring, M. Barton, and Duane Whitney. "An Asset–Liability Version of the Capital Asset Pricing Model with a Multi-Period Two-Fund Theorem." Journal of Portfolio Management 35, no. 4 (2009): 111–30. http://dx.doi.org/10.3905/jpm.2009.35.4.111.

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Ibrahim, Haslindar, and Mohammed Aljaloudi. "Sovereign Asset and Liability Management (SALM) and Efficient Debt Management: An Empirical Study for Jordan." International Journal of Analysis and Applications 22 (August 12, 2024): 132. http://dx.doi.org/10.28924/2291-8639-22-2024-132.

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Abstract:

This research is about the effect of Sovereign Asset and Liability Management (SALM) on efficient debt management in Jordan using quarterly data from 2005 to 2023. The paper applies time series analysis methods, such as the Autoregressive Distributed Lag (ARDL) and Nonlinear Autoregressive Distributed Lag (NARDL) models to study the links between SALM components (cash reserves, foreign reserves, equity in state-owned enterprises, future revenues, government debt, fiscal expenditures and contingent liabilities) and Jordan's debt-to-GDP ratio. The results show that these variables have a signifi

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Chen, Xiaowei, Fuzhe Huang, and Xiufang Li. "Robust asset-liability management under CRRA utility criterion with regime switching: a continuous-time model." Stochastic Models 38, no. 2 (2021): 167–89. http://dx.doi.org/10.1080/15326349.2021.1985520.

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Oliveira, Alan Delgado de, Tiago Pascoal Filomena, and Marcelo Brutti Righi. "PERFORMANCE COMPARISON OF SCENARIO-GENERATION METHODS APPLIED TO A STOCHASTIC OPTIMIZATION ASSET-LIABILITY MANAGEMENT MODEL." Pesquisa Operacional 38, no. 1 (2018): 53–72. http://dx.doi.org/10.1590/0101-7438.2018.038.01.0053.

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Luo, Xueping, and Qing Zhou. "Stochastic differential games on robust optimal asset-liability management with delay under the CEV model." Journal of Industrial and Management Optimization 21, no. 3 (2025): 1771–96. https://doi.org/10.3934/jimo.2024148.

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Shen, Yang, Jiaqin Wei, and Qian Zhao. "Mean–Variance Asset–Liability Management Problem Under Non-Markovian Regime-Switching Models." Applied Mathematics & Optimization 81, no. 3 (2018): 859–97. http://dx.doi.org/10.1007/s00245-018-9523-8.

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