We propose a mean quadratic variation (MQV) framework for portfolio selection as an alternative to the classical Markowitz mean–variance (MV) paradigm. Instead of measuring risk by terminal return variance, the MQV framework employs quadratic variation, a pathwise and time-additive measure of return fluctuations. This modification addresses two longstanding limitations of the MV framework: the sensitivity of covariance-based optimization in high-dimensional settings and the time-inconsistency of multi-period portfolio choice. The proposed model is straightforward to calibrate, as quadratic variation and quadratic covariation between assets can be directly estimated from realized return paths. Moreover, the additive structure of quadratic variation yields time-consistent optimal portfolio strategies in a discrete-time multi-period setting. We derive closed-form optimal portfolio weights, characterize the corresponding efficient frontier, and develop a quadratic variation-based capital asset pricing model. Extensive empirical backtests and simulation experiments show that MQV portfolios achieve competitive or improved out-of-sample performance relative to their MV counterparts across several asset universes. Overall, the results suggest that pathwise risk measurement provides a tractable and economically meaningful alternative to variance-based portfolio optimization.

Banks operate branch networks that span multiple geographic markets. Building on theories of economies of scale, this paper examines how overlap in banks’ branch networks across markets affects cost efficiency. Using a panel of 866 U.S. bank holding companies from 1986 to 2024, we measure branch network overlap based on the similarity of banks’ branch presence across metropolitan statistical areas (MSAs). Fixed-effects estimates show that banks with greater branch network overlap exhibit significantly higher cost efficiency. Complementary instrumental-variable and robustness analyses yield qualitatively similar results. Mechanism analyses suggest that overlapping branch networks enhance cost efficiency primarily through the exploitation of economies of scale facilitated by spatial proximity. The paper contributes to the literature by extending scale economy theories to the context of banking studies and by introducing a new multi-bank measure of branch network overlap. From a managerial and policy perspective, the results inform decisions on branch expansion, consolidation, and the assessment of geographic competition in banking markets.

This study explores the relationship between new female director appointments and managerial ability for a sample of 18,216 US firm-year observations representing 1,885 distinct publicly traded firms. Using a two-stage instrumental variable, we find that new female director appointments are associated with a decrease in managerial ability. This effect is robust to alternative measures, endogeneity corrections, and matched sample approaches. However, while the consequences of new female director appointments also include reductions in labor productivity and cash flows, firms do benefit from an increase in intangible assets. In addition, with time, experience, and support, firms can profit from the appointment of a new female director.

This study investigates the extent to which credit quality and risk aversion influence open banking adoption and data-sharing behaviours among UK consumers. Contrary to credit signalling theory, we find that credit quality plays little role in adoption decisions within the UK context, providing no support for the view that consumers strategically reveal creditworthiness through open banking participation. Risk aversion emerges as the dominant behavioural barrier to open banking adoption and to consumers’ willingness to share financial data, both with traditional financial service providers and financial technology firms. The effect of risk aversion on data-sharing intentions persists irrespective of consumers’ open banking adoption status, and operates through heightened privacy and security concerns, including apprehensions about data usage, storage, financial loss, and identity theft. We find pronounced heterogeneity across institution types, indicating that consumers’ data-sharing decisions are contingent on the perceived nature of the institutional counterparty. Risk aversion exerts a consistently negative influence across the open banking ecosystem. Additionally, we find that open banking adopters appear financially vulnerable, reporting lower financial satisfaction, reduced ability to cope with income shocks, and greater difficulty managing financial commitments, raising important questions about who open banking serves and carrying direct implications for consumer protection regulations.

Accurately identifying the determinants of oil spot prices remains a persistent challenge. This paper proposes a spillover-based approach to information-set selection, in which candidate system specifications are ranked based on their internal interconnectedness rather than via individual variable screening. Conceiving markets as dynamically evolving information networks, we implement the architecture of Total Spillover Index (TSI) to quantify the transmission of shocks across variables within candidate systems. We then construct, within a cointegration framework, alternative models representing Brent and WTI markets from both isolated and globally integrated perspectives. Spillover analysis shows that systems that incorporate global market indicators exhibit very strong interconnectedness and respond more sensitively to macroeconomic shocks, as reflected in their co-movement with the Global Economic Policy Uncertainty Index. Out-of-sample forecasts using both Fractional Cointegration Vector Autoregressive (FCVAR) models and Long Short-Term Memory networks show that a hybrid global specification consistently outperforms models that are restricted to isolated markets, particularly at medium and longer horizons. These results suggest that information coherence, capturing persistent cross-variable transmission within the system, provides a useful criterion for identifying forecasting-relevant information-sets in complex market environments such as global oil markets.

This study evaluates the performance of global, regional, and hybrid asset pricing models across 67 countries, employing the most refined regional classification to date, which captures both geographic and developmental distinctions. The results indicate that hybrid and regional models consistently outperform global models, which generate the largest pricing errors. Sub-period analyses reveal no evidence of increasing dominance of global factors, showing that full financial integration has not yet been achieved. The best-performing individual model varies by region. Regional models are more effective in segmented markets, while hybrid models perform better in partially integrated ones, indicating that model effectiveness depends on the degree of regional integration. Factor-spanning tests indicate that the market factor is the most globalized, followed by momentum, while investment remains largely regional. A novel globalization measure highlights high integration in North America, Western Europe, and developed Asia-Pacific, contrasted with persistent segmentation in MENA, Latin America, and Eastern Europe.

This study investigates the impact of climate risks on the financial stability of banks using a comprehensive panel dataset of European banks covering the period from 2006 to 2021. We find that greater exposure to climate risk significantly undermines bank stability, with transition risk exerting a particularly strong destabilizing effect. This impact is especially pronounced among larger banks and those with stakeholder-oriented governance models, and it intensifies following the adoption of the Paris Agreement. Our findings reveal a non-linear relationship whereby higher levels of climate risk exposure lead to disproportionately greater financial instability. Further analysis shows that these effects are driven by heterogeneity in bank-specific characteristics and country-level factors. We also find that stricter climate-policy regimes, particularly during advanced phases of the EU Emissions Trading System, strengthen the adverse effect of transition risk on financial stability. This study underscores the importance of integrating climate risks into prudential regulation to enhance the resilience of the banking industry to climate-related shocks.

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.

This paper explores the cross-border relationship between cryptocurrency prices and news sentiment by examining the Korean and global markets. We employ ChatGPT to assess sentiment in over half a million news articles from 1 December 2017 to 28 August 2023. Our findings reveal that changes in cryptocurrency prices largely drive news sentiment rather than the reverse in the global market, which differs from patterns in traditional assets and social media-driven sentiment studies. Furthermore, only Korean news sentiment predicts cryptocurrency returns in both the Korean and global markets, a predictive power that vanishes when trading volume in Korean won surpasses that in U.S. dollars. During such periods, arbitrage by Korean traders synchronizes prices between the global and Korean markets, eliminating the lead-lag relationship between sentiment and prices.