We investigate the relationship between bank capital, competition and liquidity creation in the West African Economic and Monetary Union (WAEMU) countries, using hand-collected bank-level data for 2000–2017. We uncover new evidence to suggest that the financial fragility-crowding out hypothesis (i.e., higher bank capital has a negative effect on liquidity creation) prevails among small banks in the WAEMU. A one-standard-deviation increase in bank capital is associated with a 0.67 percentage-point decline in liquidity creation relative to the size of the banking sector. Further granular analysis yields two specific findings. First, for high levels of competition, bank capital undermines liquidity creation, whereas this negative effect is attenuated in a highly concentrated environment. Second, although banks listed on the WAEMU regional stock exchange create more liquidity than their non-listed peers, stock market access does not appear to influence the effect of bank capital on liquidity creation. Overall, the banking market structure is the main channel through which capital is associated with liquidity creation in WAEMU.
This study investigates how heightened regulatory scrutiny by the U.S. Securities and Exchange Commission (SEC), caused by the passage of the Multilateral Memorandum of Understanding (MMoU), affects excessive risk-taking by U.S. listed foreign firms. Using data from 37 countries over the 2000–2020 period, we show that the adoption of the MMoU is associated with a significant decline in excessive risk-taking. This finding remains robust under a variety of sensitivity tests. Cross-sectional analysis shows that the drop in excessive risk-taking is more pronounced in firms with greater information opacity, and those from economies with pre-existing barriers to cross-border regulatory cooperation, and with weaker institutional environments. Finally, our findings indicate that the MMoU’s excessive risk-reducing effect is associated with enhanced firm value, implying that stronger international regulatory oversight facilitates efficient resource allocation. Overall, the results underscore the integral role of cross-border regulatory cooperation in constraining value-destroying managerial behavior to foster sustainable firm performance.
By separating aggregate oil price shocks into demand and supply components, we examine their effects on firm-level financial constraints using 60,925 firm-year observations from 2002 to 2021 across 65 countries globally. Controlling for year and firm fixed effects, we find that oil demand shocks are negatively related to firms’ financial constraints. In contrast, oil supply shocks dampen firms’ ability to obtain external financing. Additional analysis reveals that the impact of oil price shocks on financial constraints is more pronounced for firms belonging to the oil industry, oil users, oil-related and non-oil substitute subsectors, and for firms in non-oil-exporting and oil-consumer countries. We further observe that competitive industries and high market liquidity exacerbate the impact of oil price shocks on financial constraints. Our mechanism tests show that profitability and investment decrease (increase), while production costs, sales volatility and cash flow volatility increase (decrease) in response to oil price supply (demand) shocks, all of which are signs of firms experiencing binding (unbinding) financial constraints. Our main findings are robust to various modelling techniques and measures of financial constraints.
I assess the systemic effects of EBA stress tests, considering all exercises from 2009 to 2025. I document that EBA announcements linked to these exercises affect systemic metrics of risk, stress, and financial uncertainty, including outside the Euro Area. Using shocks extracted from the media coverage of stress test events in major European countries and the US, I show that the further dissemination and interpretation of information on such exercises by the media significantly amplify their systemic effects. Effects are heterogeneous across exercises and events but remain prevalent at the end of the time period, meaning these exercises still convey valuable information to the markets. Yet, while the system-wide dimension of exercises is continuously valued by market participants, not all exercises have proven effective in promoting financial stability and reducing information asymmetries.
This paper examines investors’ herding and overconfidence in cryptocurrency markets, with particular attention to their segmented nature with respect to capitalisation, market conditions, and external factors. Using a large sample of 1008 cryptocurrencies, we find no unconditional herding. However, herding emerges in larger cryptocurrencies during periods of high volatility and market downturns. In contrast, overconfidence affects smaller cryptocurrencies during market upturns and high-liquidity periods. External markets, such as stocks, options, and commodities, primarily drive overconfidence in smaller cryptocurrencies. The uncertainty shock following the outbreak of the Russia-Ukraine war in 2022 eliminates herding in larger cryptocurrencies and induces overconfidence in trading smaller cryptocurrencies, while removing the influence of external markets on trading in small cryptocurrencies. Compared with continuous measures of uncertainty, the war outbreak represents a distinct shock with unique behavioural effects. These findings support more granular, asset-size-specific regulatory responses, particularly during geopolitical upheavals. Incorporating event-driven behavioural dynamics into monitoring frameworks may strengthen early warning systems and mitigate systemic vulnerabilities in digital asset markets.
This study is the first to examine the determinants of commonality in liquidity resiliency (CLR). We use a high-frequency dataset from the MTS sovereign bond markets focusing on the euro area sovereign debt crisis period. Our findings are consistent with the predictions of supply-side explanations related to funding liquidity constraints, particularly in the context of financially distressed peripheral countries during the crisis period. We further demonstrate that the results of earlier studies using conventional spread and depth liquidity measures also apply to resiliency, suggesting that CLR is, on average, influenced by the same demand- and supply-side factors. Our findings offer valuable insights for policymakers, regulators, and investors, aiding them in more effectively monitoring financial stability and making informed investment decisions.
We examine the association between surname culture and earnings management using Chinese A-share firms from 2007 to 2023. Firms whose boards exhibit stronger surname culture, measured by the presence or proportion of directors sharing the chair’s surname, engage in significantly less accrual-based earnings management. The association remains qualitatively similar across alternative proxy constructions and a range of robustness and identification checks, including propensity score matching and instrumental-variable estimation. Mechanism analyses are consistent with surname culture operating through reduced financing constraints and stronger ESG performance, which lower incentives for opportunistic reporting. Surname culture is also associated with reduced income-increasing accrual manipulation, even in firm-years with strong benchmark incentives around small positive profits, and with smaller income-decreasing accruals, so that accrual discretion is compressed in both directions. Cross-sectional results indicate stronger effects when the chair’s surname is rarer and where the chair does not also serve as CEO. The association holds in both state-owned and privately controlled firms and at both higher and lower levels of provincial marketisation, and is not detectable among the small subsample of firms cross-listed on the Hong Kong Stock Exchange. Overall, board-level surname culture operates as an informal constraint on accrual manipulation where formal investor protection is still developing, with implications for other economies in which family names signal descent.
We compared monetary policy communications of the ECB and the Fed during Nov 2019-Jul 2024. Combining dictionary-based measures, bigram analysis, and Latent Dirichlet Allocation (LDA) topic modeling, we documented how both institutions allocate narrative attention during the pandemic, the subsequent inflation surge, and heightened geopolitical tensions. Dictionary-based evidence shows that inflation-related language is relatively more prominent in ECB communications, whereas employment-related terminology is comparatively more prominent in FOMC communications. Topic model results reinforce this structural difference, revealing a more concentrated thematic structure in ECB minutes and a broader thematic dispersion in FOMC communications, particularly with respect to labor market and financial conditions. These patterns persist in an expanded corpus including policy statements and press conferences. The findings suggest that institutional mandates and crisis dynamics systematically shape the emphasis and framing of central bank communication.
We present global evidence on the effect of climate change exposure (CCE) on mergers and acquisitions. We find that firms facing higher CCE exhibit a reduced propensity to engage in M&A, and experience a decrease in deal numbers and value. We adopt several identification strategies to mitigate endogeneity concerns. Our results indicate that the cost of financing and cash holdings explain this negative relationship. The effect is more concentrated within Anglo-Saxon nations, especially those characterized by advanced economic development and market-oriented institutional frameworks. We also find that firms proactively engage in sustainable practices to mitigate such adverse impacts of CCE. Finally, firms with higher climate change exposure also take longer to complete deals, earn insignificant announcement returns, and exhibit poor operating performance. Overall, our study highlights the importance of considering climate change in M&A decision-making.
This paper examines how liquidity connectedness in the foreign exchange (FX) market varies across the conditional distribution of liquidity. Using a quantile-based connectedness framework, we analyze nine major currency markets under both normal and extreme liquidity conditions. We find that liquidity connectedness is state-dependent and follows a U-shaped pattern across the distribution. Connectedness is stronger in both the lower and upper tails of the conditional distribution of liquidity, corresponding to highly liquid and severely illiquid states. These findings suggest that mean-based measures may not fully capture regime variations in liquidity transmission. Quotation- and trade-based liquidity measures exhibit heterogeneous dynamics across states, which are linked to market risk, funding conditions, and intermediary balance sheet constraints.
To protect minority shareholders, China introduced the China Securities Investor Services Center Co., Ltd. (CSISC), which has become a quasi-regulatory minority shareholder in listed companies. This regulatory innovation offers a unique opportunity to investigate a novel approach that regulators worldwide can adopt to protect minority shareholders’ interests. We find that the CSISC protects the interests of minority shareholders during particularly vulnerable periods, such as mergers and acquisitions (M&As). Specifically, excess goodwill, a proxy for overpayment in M&As, is lower when CSISC activism is present. This decrease is economically significant, showing a 33.86% reduction in excess goodwill in M&As involving CSISC activism. Moreover, this effect is more pronounced in firms with greater mispricing, poorer information environments, and fewer political connections. Our findings suggest that the CSISC is an effective protection mechanism for minority shareholders.
This paper develops an asymptotically unbiased estimator for extreme Expected Shortfall (ES) and evaluates its performance for tail risk forecasting across eight major international financial markets. The proposed estimator builds on a bias-corrected Value-at-Risk (VaR) estimator and the first-order asymptotic relation between ES and VaR, with asymptotic normality established under certain regularity conditions. Monte Carlo simulations show that the new estimator performs well in terms of bias and efficiency relative to standard extreme value theory benchmarks. To validate its practical relevance for international finance, we apply the proposed estimator to forecast extreme ES and compare its out-of-sample performance with various parametric and semi-parametric benchmarks. When combined with an AR-TGARCH filter-denoted as the conditional bias-corrected approach (C-UGH)-our approach exhibits superior out-of-sample predictive performance relative to competing methods, particularly in lower-tail ES forecasting. Notably, the proposed method demonstrates high tolerance for truncation level variations, alleviating the well-documented challenge of optimal truncation level selection in EVT-based approaches. Intriguingly, it outperforms the conditional Weissman (C-W) and conditional Peaks-Over-Threshold (C-POT) models across all eight international financial markets, even when using a randomly selected truncation level. These findings provide useful insights for extreme ES estimation and have practical implications for tail risk management and regulatory capital calculation in global financial markets.
In this paper, I empirically analyze trading patterns and investor behavior in a market for tokenized financial assets. Although investors can trade the tokenized assets around the clock, trading activity is substantially higher when the primary listing exchange is open, in particular during the regular trading session. Likewise, price differences between tokenized and underlying assets are wider during the extended trading hours than during the regular trading session. The majority of trades result from fractional order sizes but orders still cluster at round sizes, values, and prices, indicating that investors use relatively simple heuristics when setting quantities and prices. Additionally, a disproportionate number of trades, especially buy trades, use the minimum permissible order size, suggesting the presence of retail traders interested in owning an asset for purposes other than financial gain.
We study the effects of fintech acquisitions by traditional banks, a strategic response to rising digital competition in financial services. Using a panel of 69 banks in advanced economies that acquired at least one fintech firm between 2013 and 2021, we examine, in a DiD framework, how these transactions affect deposit growth, credit growth, asset allocation, and the risk profiles of acquiring banks relative to non-acquiring banks. Following a fintech acquisition, deposit growth accelerates and lending expands, although lending grows less than deposits; securities and other interest-earning assets also increase. Non-performing loans rise relative to total lending: the NPL ratio increases, while the Z-score decreases, indicating higher risk. Crucially, analogous M&As with non-fintech financial firms do not increase NPLs or reduce Z-scores, showing that these risk effects are specific to fintech acquisitions. Our findings highlight both the benefits and the unintended consequences of fintech integration. They suggest that, while these acquisitions may enhance digital capabilities and market reach, they can also amplify risk exposure.
Cryptocurrency connectedness studies often treat sentiment as a single aggregate channel, leaving unclear whether sentiment spillovers differ across information sources and what mechanisms drive cross-asset emotional transmission. We examine these issues using Thomson Reuters MarketPsych Indices news media and social media sentiment for ten major cryptocurrencies. Diebold-Yilmaz connectedness estimates show that news media sentiment exhibits stronger and more synchronized spillovers than social media sentiment. Bitcoin emerges as the dominant sentiment transmitter, and its spillover leadership is driven primarily by the return-unrelated sentiment component, supporting an amplification mechanism beyond return-linked reactions. A QVAR tail-state extension further shows that sentiment connectedness strengthens sharply in pessimistic and euphoric sentiment states, especially for social media sentiment. Finally, spillover intensity and leadership vary systematically with crypto-salient risk narratives and attention, including scams, security risk, and regulatory/legal developments. Our findings clarify how narratives and investor emotions propagate across cryptocurrencies and provide complementary insights for monitoring narrative-driven market fragility.
Firms in the aerospace and defense sector are often seen as potential beneficiaries of geopolitical tensions, but prior evidence on whether they systematically gain from geopolitical risk is limited and mixed. This paper examines the comovement between geopolitical risk and defense stock returns using daily data from 2008 to 2023 across multiple crises, and shows significant comovement asymmetries across both investment horizons and market states. Like other stocks, defense stocks are susceptible to short-term price drops in response to geopolitical risk, reflecting a flight-to-quality by investors. At longer horizons, however, they comove positively with geopolitical risk, consistent with a flight-to-arms effect as investors anticipate higher defense spending. Major spikes in geopolitical risk prolong the flight-to-quality effect before the flight-to-arms effect emerges. Easing geopolitical tensions do not lead to a short-term positive return-to-risk effect, and while a negative return-from-arms effect emerges, it does so with a delay. Our findings contribute to our understanding of industry differences in geopolitical risk exposure, and show that defense stocks are not short-term hedges but contingent long-term plays on geopolitical cycles.
Sound risk management is essential for the sustainable and high-quality development of banks. Using microdata for 220 Chinese commercial banks from 2007 to 2021 and a dynamic panel GMM framework, we examine how cross-border capital flows affect bank risk-taking and the channels through which they operate. We find that net capital inflows significantly increase bank risk-taking through two main channels: credit expansion and liquidity creation. A structural decomposition of capital movements shows that a reduction in outward investment plays the dominant role in driving this effect. We further show that the relationship depends on the regulatory environment: tighter monetary and macroprudential policies significantly mitigate the risk-inducing effect of capital flows by raising the marginal cost of risk-taking and curbing procyclicality. Additional analysis indicates that equity capital inflows are the main drivers of higher bank risk-taking, whereas net direct investment and debt capital inflows tend to reduce risk-taking. Overall, the results suggest that the volatility of short-term portfolio flows, particularly equity-related flows, is the main source of higher risk exposure in the banking sector. The study offers important insights for emerging economies seeking to balance financial liberalization with systemic stability.
This paper examines the time-series predictability of eleven currency risk factors. Using machine learning methods, I show that characteristics constructed from cross-sectional predictors of currency returns have significant out-of-sample predictive power for currency factor returns. A factor timing strategy that dynamically allocates across currency factors based on these forecasts achieves substantially higher Sharpe ratios than benchmark strategies. These results indicate that currency factor returns are predictable out-of-sample and that factor timing generates sizable economic value for investors.
