Liquidity and volatility in the municipal bond market: Evidence from the municipal liquidity facility and other early interventions

Optimizing investment horizons: Machine learning applications in technical analysis of the WIG20 index

The rise of distributed energy resources (DERs) and sophisticated digital communication systems has led to the emergence of Peer-to-Peer (P2P) energy trading as a viable method for facilitating flexible, autonomous, and efficient energy exchange within Local Energy Communities (LECs). This paper proposes a novel market model for P2P energy trading by integrating a multi-k double auction framework with the Gale-Shapley stable matching algorithm and metaheuristic optimization. The multi-k double auction offers greater pricing flexibility compared to traditional mechanisms such as uniform, discriminatory, and pay-as-bid auctions. The trading price is computed using a weighted parameter k balancing buyer and seller preferences, where k is evaluated for static values (0, 0.5, 1) and optimized dynamically using Ant Colony Optimization (ACO). Buyer-seller matching is performed using a constraint-aware Gale-Shapley algorithm that respects buyers' budget limits and sellers' capacity constraints. The model is validated using realistic data derived from photovoltaic generation, load forecasts, and prosumer preferences based on the IEEE 13 and IEEE 37-node residential feeders. Simulations were conducted over hourly trading periods divided into bidding and power exchange intervals. In the present work, the proposed hybrid architecture achieves improved social welfare, fairness in price allocation, higher market liquidity, and enhanced satisfaction for participants. This framework establishes a scalable and adaptive decision-making process that supports stable, efficient, and equitable operations in decentralized energy markets.

This research analysed how sustainability features impacted the time-on-market of commercial rental properties in Lagos, Nigeria. A quantitative research design was utilised in the study, where 250 registered estate surveying and valuation firms were sampled to administer the structured questionnaires, of which 150 valid responses were collected and analysed. The research examined how the sustainability qualities, such as energy efficiency, water conservation, indoor environmental quality, and accessibility, impacted the leasing performance. Factor analysis was used to derive the latent dimensions of sustainability, and independent samples t-tests were used to establish significant variations in the TOM between properties that had and those that did not have sustainable features. The findings show that commercial properties with sustainability elements are rented much quicker than non-sustainable ones, which proves the existence of a tangible market benefit of a green attribute. These results support the argument that sustainability is neither an environmental nor an ethical concern but rather a performance determinant of market liquidity and an investment return. The study argued that developers, investors and policymakers should mainstream sustainability ideals in property development and urban governance to improve commercial efficiencies of the market, shorten vacancy cycles, and promote environmentally friendly growth in the emerging real estate markets.

This study examines the influence of Foreign Institutional Investors (FIIs) on the performance of the Indian stock market. FIIs play a significant role in providing capital, improving liquidity, and influencing market trends. The study is based on secondary data collected from sources such as NSE, BSE, and RBI reports. It analyzes FII inflows and outflows and their relationship with stock market indices. The findings reveal that FII investments have a strong impact on market performance, where increased inflows lead to market growth, while withdrawals result in market decline. Keywords: Foreign Institutional Investors (FIIs), Stock Market Performance, Indian Stock Market, FII Inflows and Outflows, Market Trends, Investment Patterns, Market Liquidity, Stock Indices.

Understanding how quickly trading liquidity recovers after volatility shocks is central to evaluating market resilience and trading costs in financial markets. The purpose of this study is to examine how quickly trading liquidity recovers after volatility-based stress shocks in an emerging equity market and to evaluate whether recovery horizons vary systematically across shock severity, market fear, downside-risk conditions, and sectors. Using a balanced panel of NIFTY-50 firms over 2018–2024, comprising 91,350 firm-day observations, the analysis employs a non-parametric event-time framework, combined with bootstrap inference and episode-level regression diagnostics, to trace the adjustment in market liquidity following episodes of elevated volatility. Liquidity conditions are measured using the Amihud illiquidity indicator, while stress episodes are identified through firm-specific volatility shocks derived from a standardised realised-volatility measure. The framework introduces duration-based recovery metrics—liquidity half-life and time-to-normalisation—to quantify the persistence of post-shock trading frictions relative to firm-specific pre-stress baselines. Across 602 declustered stress episodes, liquidity deteriorates sharply on the stress day and recovers only gradually thereafter. The estimated mean recovery half-life is slightly above five trading days, while nearly one-third of episodes do not fully normalise within twenty trading days, indicating economically meaningful persistence in post-shock illiquidity. Recovery dynamics also vary systematically across stress severity, market-wide fear conditions (India VIX), downside-risk regimes, and sectors, highlighting that market resilience is state-dependent rather than uniform. The findings provide new evidence on the temporal structure of liquidity adjustment in emerging equity markets and introduce operational recovery-horizon metrics that can inform liquidity risk management, trading execution strategies, and market surveillance during periods of elevated volatility. These recovery-horizon measures have direct practical relevance for portfolio managers and institutional traders because they provide an operational basis for planning execution strategies when market liquidity remains impaired after volatility shocks. They are also useful for exchanges and regulators seeking to complement volatility monitoring with post-shock liquidity surveillance, thereby improving the assessment of market functioning during periods of elevated stress.

This study aims to analyze the effect of market risk and liquidity risk on stock returns in companies listed on the IDX30 index on the Indonesia Stock Exchange during the 2020–2024 period. The independent variables in this study are market risk, proxied by stock beta, and liquidity risk, proxied by the turnover ratio, while the dependent variable is stock returns. This study uses a causal quantitative approach with secondary data obtained from financial statements, stock price data, and stock trading volume. The research sample was determined using a purposive sampling technique and obtained 150 observational data. The analytical method used is multiple linear regression analysis with the help of SPSS. Prior to conducting the regression analysis, classical assumption tests were conducted, including normality, multicollinearity, heteroscedasticity, and autocorrelation tests to ensure model feasibility. The results show that market risk partially has a positive and significant effect on stock returns, while liquidity risk has no significant effect on stock returns. Simultaneously, market risk and liquidity risk have a significant effect on stock returns. The coefficient of determination indicates that the independent variables' ability to explain stock returns is relatively small, suggesting that other factors outside the model may still influence stock returns. Based on the study's findings, it is recommended that future researchers add other variables, such as macroeconomic factors and company performance, to provide more comprehensive results.

ABSTRACT This study examines how the structure of underwriting syndicates affects the issuance spread, pricing efficiency, and secondary market liquidity of municipal bonds. Based on empirical evidence from local government bonds issued in China’s interbank bond market between 2015 and 2023, we find that a higher proportion of commercial banks in the underwriting syndicate is associated with a wider issuance spread. Specifically, commercial bank underwriters enhance their bargaining power by leveraging tacit cooperation among syndicate members, their dominant market positions, and weaker local ties – resulting in wider issuance spreads. The results also indicate that a higher proportion of commercial banks in the syndicate improves secondary-market liquidity for local government bonds over both short- and long-term horizons. This study provides new insights into enhancing the pricing efficiency and liquidity of local government bonds through the optimized formation of underwriting syndicates.

This study aims to analyze the effect of Trading Volume, Profitability, Earnings Volatility, and Book-to-Market Ratio on stock price volatility of technology sector companies listed on the Indonesia Stock Exchange during the 2022–2024 period. This research is motivated by the high level of stock price fluctuations in the rapidly growing technology sector, which is accompanied by considerable market uncertainty. This study employs a quantitative explanatory approach using secondary data obtained from financial statements and stock trading records. The sample was selected using a purposive sampling method based on data availability and consistency throughout the observation period. Panel data regression analysis was applied to examine the impact of the independent variables on stock price volatility. The results indicate that trading volume has a significant negative effect on stock price volatility, suggesting that higher market liquidity contributes to price stability. Profitability does not have a significant effect on stock price volatility, indicating that earnings information is largely anticipated by investors and does not trigger substantial market reactions. Earnings volatility has a significant positive effect on stock price volatility, implying that unstable earnings increase perceived risk and market uncertainty. Furthermore, the book-to-market ratio has a significant positive effect on stock price volatility, reflecting that firms with higher fundamental risk tend to experience greater price fluctuations.

Purpose This study scrutinizes the influence of earnings management practices on the tone of the narrative board of directors' report of the annual report. Likewise, it investigates the effect of narrative reporting tone on stock liquidity. Besides, it explores how earnings management practices could affect the relationship between narrative reporting tone and stock liquidity. Design/methodology/approach The study utilizes a sample of Egyptian firms listed on the EGX 100 index from 2010 to 2023. It develops a new Python 3.6 script to measure the narrative reporting tone in Arabic annual reports. Earnings management is estimated with the widely used modified Jones model. Stock liquidity is proxied by the standard bid–ask spread. Findings The results reveal that Egyptian firms are likely to use more positive than negative tones in their narrative board of directors' reports. Likewise, the abnormal tone of the board of directors' report is a positive consequence of earnings management practices, indicating that entities with such practices tend to provide a net positive tone in their narrative reporting. Additionally, the net positive tone directly affects stock liquidity. However, earnings management practices reduce the direct interplay between the net positive tone and liquidity of the stock. The results suggest that Egyptian entities with earnings management practices exhibit higher information asymmetry and, consequently, lower stock liquidity. Research limitations/implications While this study offers several contributions, it also faces some limitations. It focuses on Egyptian companies in the EGX 100 index, which could limit how broadly the findings generalize across settings or financial markets. Practical implications Regulators may consider implementing stricter regulations or providing more precise guidelines to mitigate the potential impact of earnings management on narrative reporting tone. Corporate investors also need to be aware of the potential bias in the tone and conduct thorough analyses to avoid being swayed solely by the positive language used in the reports. Originality/value Aside from developed economies, the study provides the first evidence of interactions between earnings management, narrative reporting tone and stock market liquidity in an emerging economy with unique institutional settings and reporting requirements (i.e. Egypt). Likewise, it advances methodological approaches for assessing the tone of narrative reporting of Arabic-written texts.

At a critical juncture where global carbon neutrality goals continue to advance and carbon trading markets pursue high-quality development, traditional carbon trading systems face growing challenges including information opacity, insufficient asset liquidity, low transaction efficiency, cross-border circulation barriers, and dual billing risks. Real World Assets (RWA), leveraging blockchain's decentralized, traceable, immutable, programmable, and divisible technical characteristics, offers a novel approach to addressing carbon market dilemmas and unlocking carbon asset value. This study examines the current state of carbon trading markets and the core mechanisms of RWA technology, systematically analyzing the intrinsic logic, core value, and operational models of their integration. It explores practical applications of carbon trading-RWA convergence in carbon asset ownership confirmation, transaction circulation, regulatory accounting, and risk management scenarios. The research thoroughly assesses real-world challenges including legal compliance, technological security, market regulation, standardization, and talent shortages during integration. Targeted optimization strategies are proposed, encompassing institutional system improvements, technological breakthroughs, unified industry standards, enhanced regulatory frameworks, and professional talent cultivation. These efforts aim to deepen the synergy between carbon trading and RWA technology, enhance market efficiency and liquidity, support carbon peak and neutrality objectives, while providing theoretical foundations and practical references for green finance and digital technology integration.

The dynamics of the capital market in the post-pandemic era have become increasingly complex, influenced by both macroeconomic conditions and market activity. In Indonesia, fluctuations in the Composite Stock Price Index (IHSG)reflect changes in market liquidity and price stability, making it essential to understand the role of key economic indicators. This study aims to analyze the effect of stock trading volume, inflation, the Rupiah exchange rate, and interest rates on the movement of the Composite Stock Price Index (IHSG) during the period January 2022 to December 2024. This research employs a quantitative approach using monthly secondary data consisting of 36 observations obtained from the Indonesia Stock Exchange, Bank Indonesia, and the Central Statistics Agency. Data analysis was conducted using multiple linear regression, supported by classical assumption tests to ensure the validity of the model. The results of the study indicate that stock trading volume has a positive and significant impact on the Composite Stock Price Index (IHSG). Conversely, inflation has a negative and significant impact on the index. However, the Rupiah exchange rate and interest rates did not show a significant partial impact on the movement of the Composite Stock Price Index (IHSG) during the study period. In conclusion, the movement of the Indonesian stock market in the post-pandemic period is primarily influenced by liquidity and inflation stability. These findings highlight the importance of maintaining stable economic conditions and active market participation to support sustainable capital market growth.

In an increasingly volatile and uncertain business environment, effective risk management has become a critical determinant of financial decision-making and organizational sustainability. This study adopts a qualitative case study approach to examine how risk management practices influence financial decision-making within a financial services firm operating in India. The case focuses on a strategic decision involving the expansion of a lending portfolio under conditions of market volatility and credit uncertainty. Drawing on multiple data sources, including organizational reports and managerial insights, the study analyzes key dimensions of financial risk, including market risk, credit risk, liquidity risk, and operational risk. The findings reveal that structured risk assessment frameworks, supported by data analytics and managerial expertise, significantly enhance the effectiveness of financial decisions. However, behavioral factors such as risk perception and cognitive biases also play a critical role in shaping decision outcomes. The study further highlights the importance of organizational context, including leadership, governance, and human capital, in strengthening risk management practices and fostering resilience. By providing in-depth case-based insights, this research bridges the gap between theoretical models and practical implementation, offering valuable implications for managers and policymakers in navigating VUCA environments.

ABSTRACT This paper examines the impact of the Judicial Auction Housing Purchase Restriction (JPR) policy on the number of bidders, auction prices, and auction failure rates, using Changsha – a mid-tier city in China – as a natural experimental setting. Based on 11,540 daily auction records from 2015 to 2022 and a micro-level Propensity Score Matching with Difference-In-Differences empirical strategy, we find the JPR significantly reduces the number of bidders and raises the auction failure rate. However, unlike findings from speculative first-tier cities, the policy exerts no significant net impact on auction prices in Changsha. This heterogeneity stems from distinct market demand structures. In rigid-demand markets, the exit of marginal bidders is counterbalanced by intensified competition among remaining high-valuation buyers, stabilizing prices but reducing market liquidity. These findings provide practical implications for policymakers to optimize judicial auction market efficiency, underscoring the necessity of context-specific policy design.

Systemic financial risk spillover has become a core concern in global financial stability and macroprudential regulation, as the interconnectedness of financial institutions and markets amplifies the transmission of extreme tail risks across the entire financial system. Traditional Value-at-Risk (VaR) only measures individual entity risk and fails to capture risk interdependence and spillover effects, while the static Conditional VaR (CoVaR) model cannot reflect the time-varying characteristics of financial risk spillovers under volatile market conditions. This paper constructs a dynamic CoVaR model integrating GARCH volatility clustering and dynamic conditional correlation (DCC) to quantify the time-varying spillover effects of systemic financial risk, with a focus on measuring the marginal risk contribution of individual financial institutions to the overall system. Using daily return data of 12 major listed financial institutions in China (covering banking, securities, and insurance sectors) from January 2018 to December 2023, this paper conducts empirical analysis, calculates dynamic ΔCoVaR to measure spillover intensity, and compares risk spillover differences across financial subsectors. Results show that large state-owned commercial banks have the strongest systemic risk spillover effects, followed by securities companies, while insurance institutions have relatively weaker spillovers; risk spillovers surge significantly during crisis periods such as market turbulence and liquidity shocks, verifying the asymmetric and time-varying nature of systemic risk transmission. The dynamic CoVaR model outperforms static models in fitting accuracy and early warning efficiency, providing a reliable quantitative tool for macroprudential supervision and risk prevention.

This study investigates the causal impact of hedge fund activism (HFA) on market liquidity. The empirical results show that HFA leads to a deterioration in stock liquidity, with the effect being more pronounced in firms characterized by greater information asymmetry and financial constraints. The decline in liquidity is also more evident in cases of high-intensity campaigns, led by funds with weaker market reputation, and that engage more frequently in activist interventions. Additional analyses reveal that price efficiency, corporate information flow, and operating complexity contribute to liquidity decline. This evidence holds using several liquidity metrics and sensitivity tests, and we rule out any potential endogeneity concern using an exogenous setting in our Difference-in-Differences regression analysis. Overall, this study underscores the disruptive influence of HFA on corporate dynamics and its wider market repercussions.

ABSTRACT This study evaluates Bosnia and Herzegovina’s equity market using a country risk premium (CRP) – based valuation framework suited to structurally constrained frontier markets. In conditions of fragmented trading, negligible turnover, and weak price discovery, conventional asset-pricing models offer limited guidance. Augmenting a U.S. base equity risk premium with Bosnia’s sovereign default spread yields an implied cost of equity of approximately 17.6%. Benchmarking against regional peers shows persistent underperformance in market size, liquidity, and valuation. The analysis highlights how fragmentation and institutional constraints sustain a high required return and discusses policy pathways for gradual risk-premium compression.

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.

Research in advanced markets has identified a negative and significant relationship between stock returns and liquidity. Conversely, research on emerging markets yields conflicting findings, indicating either a positive relationship or no relationship between liquidity and stock returns. This raises questions over liquidity constraints potentially stemming from socioeconomic factors in emerging stock markets, where institutional frameworks and socioeconomic challenges may affect market dynamics. This paper studies the impact of liquidity levels on stock returns in one of the major emerging stock markets in Asia. Data at the firm level were obtained from equities listed on Bursa Malaysia. Turnover ratios were employed to assess liquidity levels, as well as other known variables associated with stock returns, including size, book-to-market equity, and momentum. This study examines several hypotheses concerning the relationship between stock returns, liquidity, and other control variables through panel data regression analyses. The findings indicate that stock returns were not explained by beta during the period of study. Stock returns appeared to be positively influenced by size and turnover ratio, but negatively affected by momentum, book-to-market ratio, and variability in liquidity. Further investigations reveal that the results were mostly robust and demonstrated a non-linear relationship between liquidity levels and stock returns, with higher liquidity exerting a much higher influence on returns. The robustness of the results was assessed in relation to the January effect, non-linearity of liquidity, and variability of liquidity – elements that may be especially pertinent in emerging markets. The study’s findings suggest that the conflicting results may be attributable to the additional socioeconomic challenges present in emerging markets, which may have impacted the outcomes.

In imperfectly competitive banking markets, the determination of loan volume and interest rates matters because even modest differences in banks’ loan-origination efficiency can alter credit availability, borrowing costs, and the transmission of financial conditions to the real economy. The existing literature richly analyzes asymmetric information, relationship lending, and credit rationing, yet it does not offer a comparably simple and tractable oligopoly framework that links heterogeneous bank-level loan-production costs directly to equilibrium loan volume and market interest rates in a unified way. The purpose of this theoretical paper is to develop such a framework and to show how differences in banking efficiency, technology, and compliance burdens propagate into observable loan-market outcomes. The paper proposes a Cournot-style model of a banking market in which banks supply loans to a common market, face a downward-sloping inverse demand for loanable funds, and differ in constant marginal loan-production costs that summarize information frictions, regulatory burden, technology adoption, and related operational constraints. The novelty of the model lies in its explicit treatment of bank-specific loan-production costs as the central microfoundation connecting imperfect competition to equilibrium liquidity and borrowing costs, thereby yielding closed-form solutions for both symmetric and asymmetric banking structures. Unlike prior approaches that emphasize credit rationing, relationship formation, or information asymmetry in isolation, the present framework embeds those frictions within a transparent quantity-competition structure that makes comparative statics on efficiency, market size, and the number of banks straightforward and policy-relevant. The model reveals a first regularity: higher average loan-production costs reduce aggregate loan supply and increase the equilibrium interest rate, implying that banking inefficiency operates in the same direction as a contractionary monetary policy. It also reveals a second regularity: improvements in technology, information processing, or other cost-reducing capabilities expand market liquidity and lower borrowing costs, so that greater bank efficiency can generate effects analogous to an expansionary monetary policy even without a direct policy-rate change. These results create a basis for future empirical testing of heterogeneous bank-cost channels and offer practical relevance for monetary authorities, prudential regulators, and bank managers evaluating how technology investment and compliance design shape credit-market performance.