This study examined the impact of interest rate risk on the financial performance of listed commercial banks in Kenya from 2013 to 2023. Using the Interest Rate Parity Theory, it employed a longitudinal approach and conducted a census of all 11 banks listed on the Nairobi Securities Exchange (NSE). These banks are subject to strict oversight by both the Capital Markets Authority (CMA) and the NSE, which require consistent disclosures, financial reporting, audits, and adherence to corporate governance standards. This regulatory environment fosters transparency in asset-liability management (ALM) and risk control, making these banks ideal for studying the relationship between interest rate risk and financial performance. The research utilized secondary data from annual financial statements and reports from the Central Bank of Kenya. Financial performance was measured using Return on Assets (ROA). Panel regression analysis revealed a positive association between interest rate risk management and financial performance, indicating that banks with stronger interest rate risk management tend to perform better. The findings suggest that Kenyan-listed banks have maintained consistent and effective interest rate risk management over the decade, thereby contributing to their stability amid economic uncertainty. Enhanced interest rate management further improved their resilience and financial outcomes. The study recommends that banks maintain robust hedging strategies, conduct regular interest rate stress tests, and perform scenario analyses to guard against unexpected interest rate fluctuations and promote sustainable growth.

We analyze a robust dynamic investment problem with ambiguous interest rate risk. After deriving the optimal terminal wealth and investment policy, we expand our framework into an equilibrium model, and calibrate it to data. We confirm the bond premium puzzle, i.e. in a non-robust version of our model an unreasonably high risk-aversion parameter is needed in order to match market data. Our proposed model with robust investors and a novel formulation of the representative agent provides a solution to this puzzle. As a technical contribution, which we consider to be of interest in its own right, we develop a novel formulation of robust dynamic investment problems, and we show that a robust CRRA agent exhibits features of an Uzawa-type agent with a stochastic subjective discount rate.

This study conducts a scenario analysis on the introduction of derivative instruments into Zimbabwe’s financial markets, focusing on their potential role in enhancing risk management, market depth, and financial stability. Zimbabwe’s financial system has historically been characterised by high volatility, currency instability, and limited hedging mechanisms, constraining effective risk mitigation for firms and investors. Using qualitative scenario analysis supported by secondary macroeconomic and financial market data, the study evaluates optimistic, moderate, and adverse scenarios associated with the adoption of derivatives such as futures, options, and swaps. The analysis considers institutional readiness, regulatory capacity, market liquidity, and systemic risk implications. Findings suggest that, under a well-regulated and phased implementation framework, derivatives could improve price discovery, facilitate hedging against exchange rate and interest rate risks, and attract both domestic and foreign investment. However, weak regulatory oversight and low market sophistication could amplify systemic vulnerabilities under adverse conditions. The study concludes that successful integration of derivative instruments in Zimbabwe requires robust regulation, market education, and macroeconomic stability to maximise benefits while minimising financial risks.

Interest rate risk in the U.S. banking sector

Banks like any other firms are exposed to a variety of risks including credit risk, liquidity risk, foreign exchange risk, market risk and interest rate risk. An efficient risk management is needed in time to control these risks. Managing risk is one of the basic tasks to be done, once it is identified and known. The risk and return are directly related to each other, which means that increasing one will subsequently increase the other and vice versa. Financial risks have a great impact on firms’ performance. The purpose of the study was to establish the effects of financial risks on profitability of listed banks in Nairobi securities exchange. The study was guided by the following theories: financial risk by portfolio theory. This study covered a period of five years (2020 to 2024). A longitudinal and descriptive design was used. The target population was only 11 listed banks in Nairobi exchange security in Kenya for that period of five years. Using inclusion and exclusion approach, purposive sampling technique was used to arrive at 9 listed banks which have complete records between 2020 to 2025 as the sample size. Secondary data collection form was employed to collect information from published financial statement from the year 2020 to 2024 from Nairobi security exchange. Descriptive statistics including mean and standard deviation was used to analyse the collected data. The inferential statistics was also used through correlations and regression analysis to establish the relationship between variables. Data was presented by use of tables and figures. The study concluded that Liquidity risk had a strong positive and significant relationship with profitability. Credit risk had weak negative and insignificant relationship with profitability. IRR had a moderate positive and significant relationship with profitability. Interest rate risk had a significant effect on profitability of listed banks. Capital management risk had a significant effect of profitability of listed banks. The study recommended that banks with high SD (volatility) should align their asset-liability management framework to prevent sharp swings in liquidity levels. Banks with high liquidity levels should review their investment strategies without compromising safety. Also CBK should improve on their supervisory focus on banks with less than 20% statutory requirement.

Purpose: This study investigates the behaviour and predictability of Nigeria’s prime lending rates from 1990 to 2026. The research identifies structural shifts, volatility patterns, and the effectiveness of autoregressive components in forecasting interest rate movements within the Nigerian financial ecosystem. Methodology: Adopting an ex post facto research design, the study utilizes monthly time-series data from the Central Bank of Nigeria. In this univariate framework, the prime lending rate serves as the dependent variable, while its own lagged values (AR) and stochastic shocks (MA) function as the independent variables. The analysis involves unit root testing, heteroscedasticity evaluations, and lag identification via ACF and PACF to fit an optimal ARIMA model. Results & conclusion: Findings reveal the PLR is integrated into order one, I(1), with a significant structural shift in January 1990. ARIMA (2,1,2) emerged as the most robust model for capturing mean fluctuations. However, residual diagnostics indicate significant volatility clustering and non-normality, suggesting that while the model effectively predicts price direction, it does not fully account for variance shocks over time. Implication of findings: Precise forecasting is essential for managing interest rate risk and credit pricing. The research recommends that the Central Bank of Nigeria and financial institutions integrate GARCH-type models with ARIMA frameworks to account for volatility clustering. Such evidence-based modelling is critical for developing resilient monetary policies and mitigating systemic financial instability.

This research analyzes the distinction between risk and uncertainty within the Romanian banking system, utilizing recent data from 2024. The study examines key prudential indicators, specifically the Non-Performing Loan (NPL) ratio, interest rate risk, and liquidity metrics (Liquidity Coverage Ratio—LCR and Net Stable Funding Ratio—NSFR). The results indicate that while consumer and SME segments show higher vulnerability to interest rate fluctuations, the corporate sector remains stable. Furthermore, the system maintains robust liquidity positions, consistently exceeding regulatory thresholds. It is concluded that aggregate risks remain manageable, though flexible management strategies are essential to navigate future economic volatility.

Type of the article: Research ArticleAbstractThailand’s green bond market is expanding but remains less developed than in advanced economies, raising questions about issuance patterns and whether return–risk conditions support broader market growth. This study aims to analyze issuance dynamics in Thailand’s green bond market, evaluate return and risk performance, assess the relationship between return, risk, and issuance volume, and classify green bonds based on their risk characteristics. The sample included 62 green bonds registered with the Thai Bond Market Association (ThaiBMA) during 2019–2025. Descriptive statistics are used to summarize issuance and performance indicators; return measures include current yield, yield to maturity, holding period return, and annual percentage rate; risk is assessed using seven variables capturing default, liquidity, interest rate, inflation, and reinvestment risks, and hierarchical clustering is applied to classify bonds by risk level. Results show that private-sector issuers dominate the market, accounting for 79% of outstanding green bond value (103.216 billion baht), followed by state-owned enterprises (12%) and foreign issuers (9%). Current yield ranges from 1.62% to 5.55% (mean 3.40%), while yield to maturity ranges from 1.75% to 8.86% (mean 3.20%). Credit spreads range from 0.41% to 3.49% (mean 1.46%), and duration ranges from 0.019 to 10.07 years (mean 3.35), indicating generally moderate risk conditions. SEM analysis further reveals a significant positive relationship between risk and return, while issuance volume is not significantly related to either factor. Cluster analysis identifies four distinct risk groups – low, medium, high, and highest – offering a practical risk classification for investors and policymakers to support sustainable finance development in Thailand.

Ukrainian domestic government bonds account for more than 85% of stock market turnover, yet institutional investors lack formalized frameworks for incorporating macroeconomic forecasts into portfolio decisions. War-induced volatility amplifies interest rate and currency risks. Existing Ukrainian research addresses these issues fragmentarily: either correlating macro factors with yields without portfolio optimization or optimizing portfolios using current yields without forecasting macro-driven changes. No prior work integrates the complete chain from scenarios to optimal weights. This study addresses how macroeconomic forecasts of the National Bank of Ukraine can substitute for unstable VAR models in yield prediction, what is the monetary transmission coefficient under structural breaks, and how currency diversification between hryvnia and dollar bonds should be optimized when exchange rate scenarios diverge while accounting for repricing effects. Methodologically, the framework implements two-stage approach. First stage models National Bank of Ukraine key rate as function of inflation and unemployment using central bank forecasts. Second stage links policy rate to domestic government bonds yields via parsimonious regression with crisis interaction. Portfolio optimization maximizes Sharpe ratio incorporating repricing through modified duration. Covariance matrix applies shrinkage to stabilize parameters. Key contribution is the first systematic mechanism for Ukrainian domestic government bonds market that operationalizes macro forecasts into rebalancing decisions. Unlike fragmented approaches, it delivers endto-end algorithm: from quarterly NBU forecasts through monetary transmission to optimal weights with explicit currency exposure and duration management. For institutional investors facing regulatory diversification requirements, this provides formal alternative to discretionary or naive strategies. Framework demonstrates how forward-looking macro information can be systematically incorporated into portfolio management in volatile emerging markets.

Guaranteed annuity options (GAOs) allow policyholders to convert accumulated funds into life annuities at maturity at a guaranteed minimum rate. Thus, insurers are exposed to both investment and longevity risks. Accurate valuation of these long-term, survival-contingent contracts is essential for solvency assessment and risk management. Many existing approaches assume independence between interest rate and mortality risks. This paper develops a computationally efficient pricing framework for GAOs that jointly models interest and mortality rates as correlated stochastic processes with regime-switching dynamics governed by a finite-state continuous-time Markov chain. Model parameters are estimated using U.S. interest rates and cohort mortality data via quasi-maximum likelihood estimation. A semi-analytic valuation formula is derived based on the joint distribution of the underlying processes. Numerical results show that incorporating correlation and regime-switching materially increases GAO prices relative to conventional one-state models. The proposed semi-analytic approach delivers substantial computational advantages over standard Monte Carlo simulations. Sensitivity analysis further identifies the parameters most relevant for long-horizon pricing and solvency considerations. This highlights the practical relevance of the framework for managing longevity-linked guarantees under economic and demographic uncertainty.

Mergers and acquisitions are noteworthy corporate strategic measure that assists the merged entity in external growth and afford it competitive advantage. The study tries to evaluate methodically the consequence of merger of United Western Bank along with Industrial Development Bank of India in 2006 and subsequent merger of IDBI bank with LIC of India in 2019 on their financial performance in terms of different financial parameters for the period from 2004-05 to 2024-25 dividing the entire period into two phases. Most of the financial indicators of Industrial Development Bank of India (IDBI) after undergoing merger with United Western Bank (UWB) in 2006 and LIC of India in 2019 exhibit noteworthy progress in their outfitted performance during post-merger period. Post-merger regression analysis suggests that impact of management quality, capital adequacy and sensitivity to interest rate risk on profitability (ROA) parameter have improved much in comparison with entire study period’s regression analysis (both pre- and post-merger taken together) in both mergers. It can be inferred from the regression analysis that merger of these above two banks and subsequently with LIC has significant impact on earning capabilities of the Bidder Bank (IDBI) in terms of creating synergy through augmented managerial efficiency and subsequently by capital adequacy and non-interest income related sensitivity.© The Author(s) 2026. Published by RITHA Publishing. This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited maintaining attribution to the author(s) and the title of the work, journal citation and URL DOI.Article’s history: Received 22nd of December, 2025; Revised 17th of January, 2026; Accepted for publication 27th of January, 2026; Available online: 2nd of February, 2026; Published as article in Volume II, Issue 1(3), 2026.

Interest rate risk supervision and bank capital management: What can the new prudential standards tell us?

ABSTRACT We show that a U‐shaped monetary rate path increases banking crisis risk, via credit and asset price cycles, analyzing 17 countries over 150 years. Rate hikes (raw or instrumented) increase crisis risk, but only if preceded by prolonged cuts. These patterns are unique to banking crises, unlike noncrisis recessions. Regarding the mechanism, prolonged cuts raise the likelihood of large credit and asset price booms, consistent with higher credit supply and risk‐taking. Subsequent hikes strongly reduce credit and asset prices, and increase banks' realized credit risk, rather than interest rate risk. We find consistent results in administrative loan‐level data for Spain.

Liquidity risk poses a significant threat to the stability of the banking sector, as highlighted by the recent bank run happened with Silicon Valley Bank (SVB). This paper examines the causes of liquidity risk through a case study and literature review of Silicon Valley Bank, focusing on its concentrated business model, reliance on uninsured deposits, asset-liability management practices, and internal risk governance. The analysis reveals that SVBs liquidity crisis was driven by its business focus and high dependence on uninsured deposits, compounded by inadequate management of interest rate risk and weaknesses in its internal risk controls. Although external supervision by the Federal Reserve was in place, its conservative approach failed to prevent the crisis. This study contributes to the literature by providing a comprehensive analysis of liquidity risk and internal governance in the context of a high-profile banking failure. It recommends that banks diversify their business models and improve the risk management for the financial investment strategies. Additionally, regulators should enhance oversight of regional and large foreign banking organizations to ensure financial stability.

In this paper, we develop a theoretical framework called ‘financialised valuation dynamics’, situated within debates on the power of finance, drawing on the conceptual and empirical contributions of early financialisation studies on firm competition in stock markets and the conjunctural nature of valuations. We analyse the 2023 U.S. banking crisis using our theoretical framework to demonstrate that the regulators’ ex-post explanation of the crisis as interest rate risk mismanagement and the concentration of uninsured deposits at the three failed banks ignores fundamental sources of financial instability that central banks have contributed to through monetary policy. We argue, through empirical analysis, that financialised valuation dynamics exercise taxonomic power and narrativise the business models of the three failed banks, which had led them to outperform other U.S. banks in stock market valuation before their failure. Financialised valuation dynamics depicted the three failed banks as ‘niche’ banks serving disruptive technology firms, which were conjuncturally regarded as the future growth engines of capitalism following the COVID-19 pandemic.

Demand deposit balance prediction models under the interest rate risk in the banking book guidelines: an empirical analysis integrating time-series models and machine learning predictions in Mexican banks

This study uses the numerical changes of the systematic skewness factors to reflect investors' preferences for the systematic skewness of stocks. As systematic skewness describes the correlation between individual stock returns and market volatility, stocks with positive systematic skewness can obtain positive returns during periods of market volatility. Thus, investors' preferences for the systematic skewness of stocks can reflect their hedging demands. By examining the predictive power of systematic skewness factors on future interest rates, we found that systematic skewness factors have a significant predictive power on future interest rates. This indicates that investors' hedging demands influence adjustments to interest rates by China's monetary authorities. Moreover, for both short‑term and long‑term interest rates, prediction errors based on systematic skewness factors are consistently lower than those from an AR model and the extended Taylor‑rule model proposed by Ma et al. (2025). Systematic skewness can serve as an asymmetric pricing signal in the market for extreme interest rate risks. Its increase often indicates a rise in investors' anxiety over liquidity tightening, thereby providing central banks with a forward-looking sentiment monitoring window independent of traditional economic indicators.

Abstract Since the increases of policy interest rates in the years 2022-2023, a number of central banks are suffering significant losses from the materialisation of interest rate risk. These losses erode the capital buffers and raise questions about the cost-efficiency of monetary policy. This warrants a closer look at the topic of central bank profitability. What drives central bank profits? What is the problem with central bank losses exactly? And what possibilities do central banks have to influence their profits and manage public perception? In this paper we revisit these questions for central banks in general, with a particular focus on the Eurosystem and De Nederlandsche Bank. Although central bank losses can be an accepted consequence of necessary monetary policy (risks), they are regrettable as they constitute public money that could have been otherwise used for public purposes such as education and healthcare. But even low (positive) profits are undesirable. In general, central bank profits contribute to maintaining a strong balance sheet and support financial independence from the government. A central bank should preferably generate sufficient income over time to grow its capital in line with GDP (Gross Domestic Product). Here, we use the concept of “capital” in a broad sense, i.e. shareholder capital and provisions, acting as risk buffer. This risk buffer should develop in line with GDP as that is roughly proportional to the underlying latent risks of the central bank from the economy and the banking sector. Central bank profits are mainly driven by the monetary policy interest rates – which have little room for including “efficiency” considerations. However, central banks should understand the outlook of their profits under different (interest rate) scenarios. This is also important for Eurosystem national central banks and the ECB which are exposed to the financial consequences of the ECB’s monetary policy decisions via income and cost sharing arrangements. Some of the balance sheet items allow for profitability considerations to be included in their management. The central bank’s own investment portfolio is the most prominent example. With the significant losses of a number of central banks, it may be wise to consider profitability more explicitly in the central bank policies. This paper attempts to offer input on that question.

This study examines the influence of financial key factors on corporate performance of the Indian Textile Industry, bridging the gap in empirical studies with respect to the risk and profitability relation. Specifically, the research looks at the liquidity risk, credit risk, operational risk, inflationary risk, and interest rate risk in terms of their impacts on the profitability of firms as measured by the return on assets (ROA) over the time period 2015-2023. Secondary financial data from 10 Indian textile listed companies provided a balanced panel of 90 firm-year observations. Using random effects panel regression with robust standard errors, the study tests the stated purposes of quantifying the single and joint effects of financial risk determinants on performance. Results show that credit risk has a significant negative effect on ROA (β = –0.086; p < .01), while operational risk (β = .114; p < .01) and inflationary risk (β = .529; p < .01) exhibit positive associations with profitability. Liquidity risk and Interest rate risk are not statistically significant. Among the control variables, the firm growth has a positive effect on ROA, but the firm age shows a negative effect. The results show that appropriate credit and operational risk management could improve performance in textile companies. The study concludes with some recommendations for the firm managers to strengthen credit controls and operational processes, and for policymakers to support risk-resilient business environments. These findings help to advance the understanding of the impacts of financial risk in emerging markets and to inform risk management practices in the strategic enterprise arena.

The relevance of the study is determined by the difficult economic situation in Ukraine caused by military aggression, which has led to a rapid increase in public debt as a key source of financing for state needs. Problem statement. The accumulation of debt obligations, changes in their currency structure and servicing conditions create significant risks for the financial stability of the state and its future economic development, which emphasises the need for a deep understanding of the peculiarities of public debt formation. Unresolved aspects of the problem. The diversity of scientific concepts regarding the interpretation of the essence of public debt emphasises the complexity and multifaceted nature of this phenomenon and points to the need for a more in-depth study of the theoretical aspects and practical tools of public debt management in conditions of geopolitical instability. Purpose of the article. The purpose of the study is to substantiate the theoretical foundations of public debt, analyse its formation in wartime and identify the main debt risks. Presentation of the main material. The object of the study is the process of forming Ukraine's public debt. The study uses a set of scientific methods, including analysis of scientific publications by domestic and foreign scientists to reveal the theoretical essence of public debt, statistical analysis to assess the dynamics and structure of Ukraine's public debt for the period 2019-2024, as well as the construction of a multivariate regression model and the average growth rate method to forecast public debt volumes for the coming years. The theoretical basis of the study was the main provisions of the theory of finance and macroeconomics. Conclusions. The results of the study demonstrate a rapid increase in Ukraine's public debt after the start of full-scale military aggression, which indicates a deterioration in the country's debt sustainability. Analysis of the structure of public debt revealed a significant increase in the share of external financing, which increases dependence on external creditors and raises currency risks. The main risks associated with the increase in public debt include refinancing risk and interest rate risk, as well as macroeconomic, fiscal, geopolitical, currency and social risks. The practical value of the study arises from deepening the understanding of current trends in the formation of Ukraine's public debt in conditions of military aggression and identifying threats to macro-financial stability. The results obtained can be used by state authorities to develop and implement effective debt policy.