Asset Liability Management Research Articles

The Role of Asset-Liability Management on Financial Stability in Malaysia

Financial stability in the Malaysian Islamic banking sector is a popular issue that should be given attention by all financial service practitioners, including bank management, regulators, and popolicymakersIn this regard, Islamic banking institutions are stable not only in terms of their ability to be resilient, but also in their financial stability when it concerns their smooth functioning as effective intermediaries. However, to achieve the goals for stability, the Islamic banking sector often faces a mismatch between assets and liabilities, which may contribute to financial instability. Based on the above-mentioned issues and problems, the objective of this study is to describe the asset and liability management practices in Malaysian Islamic banking institutions. To achieve these objectives, the study used methods of estimation on a panel data set (a combination of time series and cross-section) which contains 211 observations from 16 Islamic banks (full-fledged Islamic banks) in Malaysia from 1997 to 2016. The model estimation results showed that the profitability of Islamic banking is influenced by various factors such as asset quality, liquidity, financing, credit risk, deposit ratio, zakat, other liabilities, and capital adequacy. The study found that the asset quality ratio variable has a positive relationship with the profitability of Islamic banking, while the total asset ratio variable has a negative relationship. The liquidity ratio variable, on the other hand, has a positive relationship with the profitability of Islamic banking. The article concludes that these findings have implications for the management of assets and liabilities in Islamic banking, particularly in terms of maintaining high asset quality and liquidity while managing credit risk and capital adequacy.

The Nexus of climate crisis and asset liability management in frontier economies

Climate change is a pressing issue that is disrupting the economic systems through financial and monetary impairment. The extent is more severe in the frontiers markets and compliance with the COP26 agenda is the only recourse for low-income economies. The banks play a critical role in such countries to finance business operations and incorporating sustainability practices in asset liability management can ensure financial resilience. In this paper, we assess if climate change has any impact on the mortgage portfolio and deposit mobilization of the banking sector. Using a comprehensive sample of 175 banks across twenty-three frontier markets and employing data between 2011 and 2021, we found that climate risk is negatively associated with mortgage exposure and deposit growth. We argue that the impact on mortgages is via physical risk while for deposit mobilization the pressure emanates from transitional factors. The results remained robust even after differentiating the banks into big and small categories suggesting that climate change is bringing in risks that will impact the financial sector without any discrimination. The paper has important implications for both transitional and physical risks related to climate change.

Deep treasury management for banks.

Retail banks use Asset Liability Management (ALM) to hedge interest rate risk associated with differences in maturity and predictability of their loan and deposit portfolios. The opposing goals of profiting from maturity transformation and hedging interest rate risk while adhering to numerous regulatory constraints make ALM a challenging problem. We formulate ALM as a high-dimensional stochastic control problem in which monthly investment and financing decisions drive the evolution of the bank's balance sheet. To find strategies that maximize long-term utility in the presence of constraints and stochastic interest rates, we train neural networks that parametrize the decision process. Our experiments provide practical insights and demonstrate that the approach of Deep ALM deduces dynamic strategies that outperform static benchmarks.

Dynamic asset-liability management with frictions

This paper studies a dynamic asset-liability management problem of a company with market frictions. Specifically, the asset prices are modeled by a multivariate geometric Brownian motion with their excess returns driven by some correlated stochastic signals; and the liability process is modeled by another geometric Brownian motion correlated to the asset price dynamics. The company trades dynamically to offset the risks from its liability and each trade induces both temporary and persistent price impacts. We characterize the optimal trading strategies in terms of the solutions to the coupled matrix Riccati differential systems. Due to the price impacts, the company should adopt a target-chasing strategy in which the dynamic target portfolio is expressed in terms of the return-predicting signals and realized liability. We also derive some sufficient conditions, based on the model parameters alone, to ensure the well-posedness of the coupled Riccati systems. Our numerical results indicate that the temporary and persistent price impacts have opposite implications on the company's trading behavior. While the temporary price impact slows down the company's trading speed toward the target portfolio, the persistent price impact may encourage the company to trade more aggressively to enhance the expected returns.

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>

Optimal investment strategies for asset-liability management with affine diffusion factor processes and HARA preferences

<p style='text-indent:20px;'>This paper investigates an optimal asset-liability management problem within the expected utility maximization framework. The general hyperbolic absolute risk aversion (HARA) utility is adopted to describe the risk preference of the asset-liability manager. The financial market comprises a risk-free asset and a risky asset. The market price of risk depends on an affine diffusion factor process, which includes, but is not limited to, the constant elasticity of variance (CEV), Stein-Stein, Schöbel and Zhu, Heston, 3/2, 4/2 models, and some non-Markovian models, as exceptional examples. The accumulative liability process is featured by a generalized drifted Brownian motion with possibly unbounded and non-Markovian drift and diffusion coefficients. Due to the sophisticated structure of HARA utility and the non-Markovian framework of the incomplete financial market, a backward stochastic differential equation (BSDE) approach is adopted. By solving a recursively coupled BSDE system, closed-form expressions for both the optimal investment strategy and optimal value function are derived. Moreover, explicit solutions to some particular cases of our model are provided. Finally, numerical examples are presented to illustrate the effect of model parameters on the optimal investment strategies in several particular cases.</p>

A framework for treating model uncertainty in the asset liability management problem

The problem of asset liability management (ALM) is a classic problem of the financial mathematics and of great interest for the banking institutions and insurance companies. Several formulations of this problem under various model settings have been studied under the Mean-Variance (MV) principle perspective. In this paper, the ALM problem is revisited under the context of model uncertainty in the one-stage framework. In practice, uncertainty issues appear to several aspects of the problem, e.g. liability process characteristics, market conditions, inflation rates, inside information effects, etc. A framework relying on the notion of the Wasserstein barycenter is presented which is able to treat robustly this type of ambiguities by appropriate handling the various information sources (models) and appropriately reformulating the relevant decision making problem. The proposed framework can be applied to a number of different model settings leading to the selection of investment portfolios that remain robust to the various uncertainties appearing in the market. The paper is concluded with a numerical experiment for a static version of the ALM problem, employing standard modelling approaches, illustrating the capabilities of the proposed method with very satisfactory results in retrieving the true optimal strategy even in high noise cases.

Dynamics of Asset Liability Management in Indian Public Sector Banks: A Comprehensive Analysis of Deposit and Lending Practices

This research investigate into the complexity of Asset Liability Management (ALM) in the context of Indian Public Sector Banks (PSBs), with a focus on deposit and lending practices. The selected banks for deposit and lending analysis?SBI, Bank of Baroda (BOB), Canara Bank, Bank of India (BOI), and Punjab National Bank (PNB)?offer a diverse perspective due to variations in operations, size, government influence, risk management, innovation, market trends, and regulatory compliance. The research design outlines the objective, scope, methodology, variables, and significance of the study, spanning the years 2011-12 to 2019-20. The techniques employed include the crucial Loan-to-Deposit Ratio (LDR) analysis, providing a metric to assess liquidity and potential risks. Additionally, correlation analysis explores the relationship between deposit and lending growth. The data analysis section offers a detailed examination of the selected banks' performance, highlighting deposit and lending trends, CAGR, and LDR growth. Notably, the study identifies high correlations between deposits and loans, underscoring the banks' reliance on deposits for lending activities. The overall analysis indicates positive growth in deposits and advances for the chosen period, with State Bank of India and Canara Bank emerging as top performers. However, the slow LDR growth suggests cautious lending strategies, possibly influenced by concerns about asset quality and capital adequacy. The research concludes by acknowledging the challenges faced by Indian public sector banks but highlights their progress and essential role in the nation's economy. The findings have implications for policymakers, banking professionals, and researchers in the financial sector, contributing to a deeper understanding of deposit and lending practices in major public sector banks.

A bi-level optimization model for the asset-liability management of insurance companies

<p style='text-indent:20px;'>Different from traditional asset-liability management where only investment allocation is considered, this paper introduces policy product allocation into asset-liability management of insurance companies. In order to balance product allocation and investment allocation, a bi-level optimization model is employed. Since the decision-making environment of the two allocation processes is full of indeterminacy, the imprecise information of the model is measured by uncertain variables in order to deal with the lack of enough historical data. To solve this bi-level Optimization problem containing uncertain variables, an uncertain bilevel programming model is used. Furthermore, we simulate a scenario to compare the bi-level optimization approach with other approaches by virtue of hybrid intelligent algorithms.</p>

Finding the Blind Spots Before It's Too Late: A (Reverse) Stress Testing Approach for Asset Liability Management

Finding the Blind Spots Before It's Too Late: A (Reverse) Stress Testing Approach for Asset Liability Management

Stochastic maximum principle for weighted mean-field system

We study the optimal control problem for a weighted mean-field system. A new feature of the control problem is that the coefficients depend on the state process as well as its weighted measure and the control variable. By applying variational technique, we establish a stochastic maximum principle. Also, we establish a sufficient condition of optimality. As an application, we investigate the optimal premium policy of an insurance firm for asset–liability management problem.

GAP Ratio, Posisi Devisa Neto, Biaya Operasional Pendapatan Operasional dan Profitabilitas pada Perbankan di Indonesia

This research intends to examine the factors that influence the profitability of the banking industry since, as a sector that influences economic circumstances, the banking industry has witnessed fluctuations in profitability over the previous decade. This form of study employs quantitative secondary data sources. The population of this research consisted of all state-owned banks from 2010 to 2021. Multiple linear regression test and also hypothesis testing are employed in this study. Using descriptive quantitative statistics, the technique of analysis explains the relationship between the dependent and independent variables. The study's findings give empirical proof that gap ratio and BOPO have a negative impact on ROA. Meanwhile, PDN has no impact on ROA. This study also demonstrates the validity of the theory of asset-liability management (ALMA); maximizing earnings via risk-managing the structure of the business's financial situation and the anticipated income theory; increasing bank liquidity and optimize bank earnings by offering efficient long-term lending.
 Keywords: Gap Ratio; Net Open Position (NOP); Operating Cost of Operating Income (BOPO); Profitability (ROA)

Effect of Asset-Liability Management on Bank Profitability: Evidence from Afghanistan Banking Sector

Much research has been carried out in various nations to examine the effect of ALM (Asset-liability Management) on Bank profitability. In developing nations, this issue of banks' profitability has attained relatively little attention. Existing literature, in the context of the Afghan commercial bank industry, has only related banks' endogenous factors and exogenous factors to banks' profitability and has not explicitly generated a clear relationship between balance-sheet both sides components (ALM) and the value of the bank. This paper attempted to find out the impact of Asset- liabilities components (AML), and macroeconomic factors on the banks' profitability, in the Afghanistan banking sector's context keeping control variables in place. The research was empirical in nature and the study period was between 2011 and 2021. The research population in Afghanistan consists of twelve commercial banks. The annual audited balance sheet, income statements of the commercial banks, national statistics, and World Bank dataset served as the source of secondary data. Random effect and fixed effect regression analysis was employed to analyze the data. The research accepts that there is a link between the majority of the categories of assets and liabilities, macroeconomics as their coefficients are confirmed to be statistically significant.

Effect of Asset-Liability Management on Bank Profitability: Evidence from Afghanistan Banking Sector

Much research has been carried out in various nations to examine the effect of ALM (Asset-liability Management) on Bank profitability. In developing nations, this issue of banks' profitability has attained relatively little attention. Existing literature, in the context of the Afghan commercial bank industry, has only related banks' endogenous factors and exogenous factors to banks' profitability and has not explicitly generated a clear relationship between balance-sheet both sides components (ALM) and the value of the bank. This paper attempted to find out the impact of Asset- liabilities components (AML), and macroeconomic factors on the banks' profitability, in the Afghanistan banking sector's context keeping control variables in place. The research was empirical in nature and the study period was between 2011 and 2021. The research population in Afghanistan consists of twelve commercial banks. The annual audited balance sheet, income statements of the commercial banks, national statistics, and World Bank dataset served as the source of secondary data. Random effect and fixed effect regression analysis was employed to analyze the data. The research accepts that there is a link between the majority of the categories of assets and liabilities, macroeconomics as their coefficients are confirmed to be statistically significant.

THE ROLE OF SERVICE QUALITY ON PERFORMANCE

The South Sudan banking has seen momentous changes in the post-independence era. It has witnessed introduction of a remarkable shift in its operating environment during the last decade. Various reform measures, both qualitative and quantitative, were introduced with an objective to revitalize Indian banking sector and to meet the future challenges(Carlson, 2010). Every aspect of the functioning of the South Sudan banking industry, be it a customer service, resource mobilization, credit management, asset-liability management, investments, human resource development, and forex management are undergoing dramatic changes with the reforms gathering the momentum and speed. Several innovative IT-based services such as Automated Teller Machines (ATMs), electronic fund transfer (EFT), anywhere-anytime banking, internet banking etc. are being introduced in the South Sudan banking customers(Kassim & Abdullah, 2010).

Asset-liability management with state-dependent utility in the regime-switching market

This paper considers a state-dependent optimal asset-liability management problem in continuous-time settings. The investor maximizes the expected state-dependent utility of the terminal asset-liability ratio in a regime-switching market to better describe insurance companies’ needs for asset-liability matching and regulation with background risk. We apply the stochastic dynamic programming method to get closed-form results. We find that the optimal strategy in the state-dependent utility case is the same, and the optimal value function differs from the state-independent utility case. Finally, we study how the parameters impact the optimal investment strategy and corresponding value functions through numerical examples.

Robust optimal asset–liability management with delay and ambiguity aversion in a jump-diffusion market

In this paper, we consider a robust optimal asset–liability management problem with delay for an ambiguity-averse investor (AAI), who does not hold a firm belief towards not only the drift parameters but also the jump intensity in the wealth process. The objective of AAI is to maximise the robust value involving the expected utility of a weighted sum of terminal wealth and a penalisation of model uncertainty. In addition, the wealth process is modelled by a stochastic delay equation with jump via introducing the performance-related capital inflow/outflow. Applying the technique of robust optimal theory and Hamilton–Jacobi–Bellman equation, we derive the optimal results and the proof of verification theorem for the general utility functions and liability processes. In the case of the exponential utility function and a positive liability process, we prove the existence and uniqueness of the robust optimal investment strategy and find it naturally satisfies the constraint of no-short selling. Meanwhile, we adopt a special method to solve the corresponding Riccati equation and obtain the value function in explicit form. Furthermore, the results under the complete memory are discussed in detail. Finally, some numerical examples are provided to illustrate the influence of model parameters on the optimal strategy as well as the economic interpretation behind it.

Long-term stability of a life insurer’s balance sheet

In this paper, we devise a stochastic asset–liability management (ALM) model for a life insurance company and analyze its influence on the balance sheet within a low-interest rate environment. In particular, a flexible procedure for the generation of insurers’ compressed contract portfolios that respects the given biometric structure is presented, extending the existing literature on stochastic ALM modeling. The introduced balance sheet model is in line with the principles of double-entry bookkeeping as required in accounting. We further focus on the incorporation of new business, i.e. the addition of newly concluded contracts and thus of insured in each period. Efficient simulations are obtained by integrating new policies into existing cohorts according to contract-related criteria. We provide new results on the consistency of the balance sheet equations. In extensive simulation studies for different scenarios regarding the business form of today’s life insurers, we utilize these to analyze the long-term behavior and the stability of the components of the balance sheet for different asset–liability approaches. Finally, we investigate the robustness of two prominent investment strategies against crashes in the capital markets, which lead to extreme liquidity shocks and thus threaten the insurer’s financial health.

The effect of asset and liability management on the financial performance of microfinance institutions: evidence from sub-Saharan African region

This study applies statistical cost accounting method to a sample of 106 sub-Saharan African microfinance institutions (MFIs) during 2014–2018 to investigate the relationship between asset-liability management and financial performance. The result shows that the composition of assets and liabilities has both positive and negative effects on the returns of the MFIs in the sample. Net loan portfolio, other current financial liabilities and MFI size are significantly and positively related to return on assets of listed MFIs. Deposits, borrowings and other liabilities, on the other hand, are significantly and negatively related to financial performance. Overall, the study suggests that adequate attention needs to be paid to asset-liability management to ensure better financial performance.

Development of a new asset liability Management model with liquidity and inflation risks based on the Lower Partial Moment

Inflation and liquidity risks are two significant risks with which pension fund managers must contend. This study develops a new multi-period Asset Liability Management model to address these challenges. The model objective function minimizes both risks simultaneously. The Lower Partial Moment measure is used to minimize investment portfolio risk and a CVaR constraint is employed to avoid loss. A hybrid ARIMA-GARCH model is developed to generate scenarios regarding a case study from Iran. To do so, four different investment cases out of seven stocks from the stock market, one bond, three foreign currencies (Dollar, Euro, and Yen) and gold are considered. Findings affirm model efficacy and the model suggests that a portfolio of all four assets is the best investment strategy.