Asset Liability Management Research Articles

Robust Goal Programming as a Novelty Asset Liability Management Modeling in Non-Financial Companies: A Systematic Literature Review

Robust Goal Programming as a Novelty Asset Liability Management Modeling in Non-Financial Companies: A Systematic Literature Review

The Impact of Asset-Liability Management on the Profitability of Listed Commercial Banks in Vietnam

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 loans and advances, investments in securities on the asset side, and deposits and borrowings from other credit institutions, along with customer deposits on the liability side, are significant. Lending activities, in particular, are identified as key drivers of financial performance in the Vietnamese banking sector. However, the minimal impact of investment securities on profitability raises questions, given their traditionally significant role in banking profitability strategies globally. The study also highlights the negative effects of certain liabilities on bank profitability, stressing the need for careful liability management for banks in Vietnam. While GDP growth is generally linked with economic prosperity and financial sector growth, its impact on bank profitability in Vietnam appears limited, suggesting that other factors might play a more significant role.

Determinants of bank deposit in a small economy’s banking sector: a study of Fiji

Purpose Deposits, a liability component of banks’ balance sheet, are an important source of funding for commercial and retail banks. In this study, the authors consider deposits as dependent variable and examine factors (bank-specific, macrofinance and structural) that could plausibly explain deposits. Subsequently, the findings are expected to support analysts, bank managers and regulators, especially in small economies such as Fiji, for asset–liability management. Design/methodology/approach This study uses a balanced panel of six commercial banks and two credit institutions over the period 2000–2022. To control for bank heterogeneity, a fixed-effect regression method is used. Findings Bank-specific variables such as bank size, profitability, loan-to-deposit ratio and bank stability are positively associated with bank deposits, whereas the capital adequacy ratio is negatively associated with bank deposits. Macroeconomic variables such as remittances and gross domestic product per capita are positively associated with bank deposits. Moreover, institutional variables such as control of corruption, political stability and regulatory quality are positively associated with bank deposits. However, tail events such as the global financial crisis of 2007–09 and the COVID-19 pandemic negatively influence bank deposits. Structural breaks for 2007 and 2011 of two banks (Bank of the Baroda and Bank of the South Pacific, respectively) are positively associated with bank deposits. Originality/value Previous studies have considered profitability, competition, nonperforming loans and stability of banks in Fiji. To the best of the authors’ knowledge, this study is the first to consider the determinants of bank deposits, an important source of funds for banks in many small countries including Fiji. In addition, this study examines the impact of structural breaks, tail events such as the recent pandemic (COVID-19) and institutional variables.

Moderating Effect of Board Characteristics on the Association between Asset Liability Management and Financial Performance of Commercial Banks in Nigeria

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 commercial banks in Nigeria, the study covered the period starting from 2012 to 2021 and it purposively selected eleven (11) commercial banks out of fourteen (14) commercial banks in Nigeria. The statistical analysis was done using LASSO (Least Absolute Shrinkage Selection Operator). The findings of the study revealed that the moderating effect of board characteristics and asset liability management had a statistically significant impact on the financial performance of commercial banks in Nigeria because the p-values (0.04;0.03,0.02,0.01, and 0.005) obtained using LASSO were less than the 5% statistical threshold used in this study. The study concluded that the board of directors of commercial banks in Nigeria should ensure that they appoint board members who have expertise and experience in the establishment of asset liability management since its interaction with board characteristics showed a statistically significant impact on the financial performance of the bank.

Risk Assessment of Banks When Interest Rate Hikes

Interest rates play a crucial role in the risk management of banks. When central banks raise interest rates to curb inflation or an overheated economy, the risk profile of banks can alter significantly. This paper explores the risks banks face and their assessment methods in a rising interest rate environment, focusing on SVB and Credit Suisse as case studies. It identifies key risks such as liquidity risk, credit risk, market risk, and systemic risk by examining the impact of increasing interest rates on banks' balance sheets, earnings, and capital positions. The research concludes that Asset-Liability Management (ALM) modeling, stress testing, and hedging strategies are effective tools for banks to manage these risks. A thorough literature review underscores the importance of these strategies in ensuring banks' stability and performance amidst rising interest rates. The paper highlights that proper risk management practices are essential for banks to navigate the challenges posed by changing interest rates and to maintain their financial health and operational stability in such an environment.

An Analysis of Maturity Patterns and Interest Rate Risk in Public and Private Banks in India: an Asset Liability Management Approach

An Analysis of Maturity Patterns and Interest Rate Risk in Public and Private Banks in India: an Asset Liability Management Approach

The Relationship Between Asset-Liability Management and Governance Quality in the Banking Industry

This study investigates whether governance quality is associated with asset-liability management (ALM) within the US banking industry. Based on stewardship theory, we hypothesize that there ought to be a significant, positive association between bank governance quality and a strong balance sheet due to inherent fiduciary responsibility and internal controls associated with an ALM governance process. Due to endogeneity concerns, we employ two-stage least squares regression and examine the relationship between 10 ALM metrics and governance risk scores (a component of ESG quality scores) for a cross-sectional sample of 251 US publicly traded banks in 2022. The results suggest that corporate governance influences ALM, not vice-versa. However, contrary to our hypothesized direction, favorable governance quality is associated with weaker ALM metrics as the results indicate that there is an inverse relationship between governance quality and ALM. Even so, the results provide evidence that bank governance quality is associated with balance sheet management. The results should be of interest to bank executives, regulators, investors, and other stakeholders in the banking industry.

Bank liquidity risk management through stable and volatile markets: The role of the asset-liability committee and lessons learned for the balance sheet governance operating model

This study examines the balance sheet management governance operating model of selected failed banks from 2007, 2008, 2009 and 2023, with emphasis on the corporate governance structure in place and the position of the asset-liability committee (ALCO), and draws conclusions and recommendations for future policy. All failed sample banks exhibited near-identical governance frameworks for management and oversight of balance sheet risk: namely an ALCO that reported to the senior executive management committee, and was at least two levels, if not three levels, below board level. It is inferred that, as the ultimate responsible and accountable forum for ensuring balance sheet viability and continuing going concern of the bank, the board would benefit from being closer to the balance sheet risk management process. This implies changing the governance structure such that the ALCO is closer to the board itself, and able to provide direct comfort to the board that the bank's capital and liquidity risks are being managed appropriately. The following bank governance measures are recommended, to be imposed by regulatory fiat if necessary: •Direct delegated authority of the ALCO to manage the balance sheet, from a long-term robustness and viability perspective, directly on behalf of the board. •The ALCO to report directly to the board, rather than via the executive management committee (or as an alternative approach, changed to become a sub-committee of the board). This recognises that the asset-liability management (ALM) discipline is at least as important as, if not more important than, the ‘audit’ oversight function undertaken by the board audit committee. •Technical expertise at ALCO and board level that is capable of discerning the genuine capital and liquidity risk exposure position of the bank, on a medium-term forward-looking basis, at all times.

Optimal investment for asset–liability management with delay and partial information under Ornstein–Uhlenbeck process

In this paper, we investigate the optimal investment strategy of asset liability management (ALM) with bounded memory and partial information. Suppose that investors invest their assets in a financial market consisting of a risk-free bond and a risk-free stock, while also taking on liabilities, in which the value of liabilities and the price of risky assets satisfy the Ornstein–Uhlenbeck (O–U) processes whose drift terms are unobserved. By constructing a dynamic portfolio of risk-free bonds, risky stocks and liabilities, a stochastic delay differential equation is obtained to depict the surplus process of investor. The ALM problem is formulated as finding the best strategy to maximize the terminal utility of the sum of terminal surplus and some historical wealth under partial information, and the corresponding full information case is also studied as a supplement. For both cases of partial information and full information, we apply the dynamic programming method to derive HJB equations, verification theorems, and closed-form solutions of optimal strategies and value functions. Moreover the relationship between optimal strategy and value function under full information and partial information is also given. Finally, numerical examples are carried out to illustrate the influence of some important parameters on the obtained results.

Worst-case Conditional Value at Risk for asset liability management: A framework for general loss functions

Asset–liability management (ALM) is a challenging task faced by pension funds due to the uncertain nature of future asset returns, employees’ wages, and interest rates. To address this challenge, this paper presents a new mathematical model that uses a Worst-case Conditional Value-at-Risk (WCVaR) constraint to ensure that, with high probability, the funding ratio remains above a regulator-mandated threshold under the worst-case density function that plausibly explains historical sample data. A tractable reformulation of this WCVaR constraint is developed based on the definition of the Worst-case Lower Partial Moment (WLPM) for a general loss function. Additionally, a data-driven moment-based ambiguity set is constructed to capture uncertainty in the moments of the density functions of random variables in the ALM problem. The proposed approach is evaluated using real-world data from the Canada Pension Plan (CPP) and is shown to outperform classical ALM models, based on either CVaR or WCVaR with fixed moments, on out-of-sample data. The proposed framework for handling correlated uncertainty using WCVaR with nonlinear loss functions can be used in other application areas.

THE IMPACT MODEL OF INTEREST RATE LIBERALIZATION REFORM ON THE PROFITABILITY OF STATE-OWNED COMMERCIAL BANKS: A CASE STUDY OF BANK C OF CHINA

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 optimizing asset-liability management, adjusting asset and liability structures, and employing proactive risk management. These measures improved its investment returns and profitability. Additionally, Bank C’s adoption of countercyclical strategies and advancements in digital transformation and process automation helped sustain its profit model. The research concludes that Bank C's strategic adjustments enhanced its profitability and competitive edge, offering insights for other banks in similar market conditions and aiding predictions of financial market trends.

ALM for insurers with multiple underwriting lines and portfolio constraints: a Lagrangian duality approach

We investigate how an insurance firm can optimally allocate its assets to back up liabilities from multiple non-life business lines. The insurance risks are modeled by a multidimensional jump-diffusion process that accounts for simultaneous claims in different insurance lines with policy limits. We use Lagrangian convex duality techniques to derive optimal investment-underwriting strategies that maximize the expected utility from dividends and final wealth over a finite horizon. We examine how risk aversion, prudence, portfolio constraints, and multivariate insurance risk affect the firm’s earnings retention. We obtain explicit solutions for optimal strategies under constant relative risk aversion preferences. Finally, we illustrate our results with numerical examples and show the impact of co-integration for asset-liability management with multiple sources of insurance risk.

Asset–Liability Management of Life Insurers in the Negative Interest Rate Environment

This study investigates the asset–liability management (ALM) of life insurers in markets with negative interest rates. Using a sample of Japanese life insurers between 2000 and 2020, we provide initial evidence that the negative interest rate environment produces a much more serious consequence on insurers than the positive interest rate environment. Given that duration and convexity are two common measures widely used by insurers to manage their assets and liabilities, we highlight that the assumption of a flat yield curve underlying the traditional measures (e.g., the Macaulay and modified durations and convexities) is problematic when interest rates turn negative. To address this issue, we propose an ALM framework using the duration and convexity based on the Vasicek stochastic model. Results show that the strategy based on the Vasicek model outperforms the strategy using the modified duration and convexity in the negative interest rate environment.

Robust asset-liability management games for n players under multivariate stochastic covariance models

This paper investigates a non-zero-sum stochastic differential game among n competitive CARA asset-liability managers, who are concerned about the potential model ambiguity and aim to seek the robust investment strategies. The ambiguity-averse managers are subject to uncontrollable and idiosyncratic random liabilities driven by generalized drifted Brownian motions and have access to an incomplete financial market consisting of a risk-free asset, a market index and a stock under a multivariate stochastic covariance model. The market dynamics permit not only stochastic correlation between the risky assets but also path-dependent and time-varying risk premium and volatility, depending on two affine-diffusion factor processes. The objective of each manager is to maximize the expected exponential utility of his terminal surplus relative to the average among his competitors under the worst-case scenario of the alternative measures. We manage to solve this robust non-Markovian stochastic differential game by using a backward stochastic differential equation approach. Explicit expressions for the robust Nash equilibrium investment policies, the density generator processes under the well-defined worst-case probability measures and the corresponding value functions are derived. Conditions for the admissibility of the robust equilibrium strategies are provided. Finally, we perform some numerical examples to illustrate the influence of model parameters on the equilibrium investment strategies and draw some economic interpretations from these results.

Risk assessment for synthetic GICs: a quantitative framework for asset–liability management

AbstractThis study addresses a research gap in quantitative modeling framework and scenario analysis for the risk management of stable value fund wraps, a crucial segment of the U.S. financial market with over USD $400 billion in assets. In this paper, we present an asset–liability model that encompasses an innovative approach to modeling the assets of fixed-income funds coupled with a liability model backed by empirical analysis on a unique data set covering 80% of the stand-alone plan sponsor market, contrasting with models based solely on regular deterministic cash flows and interest rate differences. Our model identifies and analyzes two critical risk scenarios from the insurer’s perspective: inflationary and yield spike. Our approach demonstrates that the tail risk of wraps, used as an economic capital measure, is sensitive to characteristic parameters of the fund, such as the duration, portfolio composition and credit quality of assets. This finding significantly differs from U.S. regulatory approaches like the NAIC’s, which often result in a zero capital requirement. These findings reveal limitations in current actuarial risk and profitability metrics for U.S. insurers and argue that a more sophisticated risk model reproducing the two critical scenarios is necessary.

Sustainable Equity Discrimination in Asset Liability Management for Practitioners: A Practical Approach

CONTEXT: As the financial sector increasingly emphasizes responsible investment, insurance companies are actively seeking user-friendly approaches to incorporate sustainability criteria for equities into their Asset and Liability Management processes. OBJECTIVES: This paper aims to introduce a novel practitioner-centric methodology focused on seamlessly integrating publicly available Environmental, Social, and Governance (ESG) criteria. The objective is also to ensure ease of implementation for companies, emphasizing independence from ESG scoring provided by private data providers. METHODS: The proposed approach involves leveraging accessible sustainability data to construct both a sustainable equity index and a complementary index for non-included shares, utilizing clustering techniques. Subsequently, an efficient frontier is generated through the application of the Markowitz methodology. The effectiveness of the method is demonstrated through its application to a real portfolio, showcasing stability with a notable emphasis on sustainable assets, guided by the efficient reallocations suggested by the Markowitz model. RESULTS: Both constructed indices exhibit similar trends, with the ESG index outperforming, albeit with slightly higher volatility. This performance discrepancy is mirrored in the strategic asset allocation, where a preference is given to the ESG class over the non-ESG class. IMPLICATIONS AND LIMITATIONS: The findings suggest the feasibility of a financial institution successfully developing its own cohesive sustainability index using solely publicly available data. While our constructed ESG index demonstrated superior performance in this study, further research involving alternative data sources is essential to generalize this result.

Optimal investment strategy for asset-liability management with a defaultable bond under stochastic default intensity

This paper studies a continuous-time asset-liability management problem with a defaultable bond under stochastic interest rates and stochastic default intensity. Specifically, an asset-liability manager is allowed to invest in a cash, a treasury bond, a defaultable bond and a stock. Using the stochastic control scheme and partial differential equation approach, we derive closed-form expressions for optimal investment strategies and corresponding value functions under the power and exponential utility functions. In addition, we also provide numerical experiments to illustrate the impact of relevant parameters in the default process and recovery rate on the optimal asset allocation strategy.

The Effect of Alma Relationship Implementation On Sharia Bangking In Indonesia

This study aims to determine the effect of Asset Liability Management on the financial performance of Sharia Commercial Banks in 2017-2022. Asset Liability Management is the activity of optimizing the balance sheet structure of Islamic banks with various alternatives available to maximize profits while limiting risk to a minimum. The research method used in this study is quantitative, with multiple linear regression analysis using analytical methods with the help of the SPSS program, tests carried out such as regression tests and classical assumption tests with exogenous variables, namely Asset Liability Management and endogenous variables are financial performance. This research takes data from the annual financial statements of Islamic Commercial Banks, data obtained from the website of the Financial Services Authority in the financial statements for the year at Islamic commercial banks for the 2017-2022 period. In determining the sample used is purposive sampling, namely the determination of samples based on criteria, namely banking companies registered with Sharia Commercial Banks during 2017-2018. This study found that ALMA on the CAR and FDR variables had no effect on Financial Performance on the ROA variable. Meanwhile, NIM affects Financial Performance on the ROA variable. Application of ALMA to financial performance. The results of data processing show that CAR has no effect on ROA with a significant value of 0.165 and NIM has an effect on ROA with a significant value of 0.022 while FDR has no effect on ROA with a significant value of 0.135.

Manajemen Aset dan Liabilitas dalam Bank Syariah: Analisis Komprehensif Institusi Keuangan Berprinsip Syariah

The Islamic banking industry in Indonesia, since the establishment of Bank Muamalat Indonesia in 1991, has experienced rapid growth, reaching its peak in 2019. This growth is evident not only in financial aspects but also involves a broader performance assessment, including Sharia principles and organizational governance. The assets of Islamic banks have achieved remarkable milestones, strengthening Indonesia's position as a key player in the global Islamic banking arena. New approaches such as the Sharia Maqhasid Index (SMI) highlight the attainment of Sharia goals, while fund management and the phenomenon of mergers between BRIS, Mandiri Syariah, and BNI Syariah forming Bank Syariah Indonesia (BSI) underscore the urgency of assessing asset liability management in the context of sustainability in Indonesia's Islamic banking sector.

Financial optimization modeling on asset liability management with weighted goal programming

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. The Best-Worst Method (BWM) was used to determine the priority weights of deviation variables from each financial ratio target. Financial ratios were selected based on their impact on profit using factor analysis. The constructed WGP model aims to minimize deviations in Return on Assets, Operating Ratios, Operating Income Ratio, Total Assets Turnover, and Current Ratio. Computational calculations to solve the WGP model are performed using Python, with pseudocode provided. A case study on a company in the garment and textile sector was conducted and found that the Operating Ratio, Return on Assets, Operating Income Ratio, and Current Ratio still need improvement by developing strategies to achieve the targets. Sensitivity analysis was also employed to assess the resilience of the model in response to alterations in data.