International Review of Financial Analysis最新文献

{"title":"Non-stationary financial risk factors and macroeconomic vulnerability for the UK","authors":"Katalin Varga, Tibor Szendrei","doi":"10.1016/j.irfa.2024.103866","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103866","url":null,"abstract":"Tracking the build-up of financial vulnerabilities is a key component of financial stability policy. Due to the complexity of the financial system, this task is daunting, and there have been several proposals on how to manage this goal. One popular way is through the creation of indices that act as a signal for the policy maker. While factor modelling in finance and economics has a rich history, most of the applications tend to focus on stationary factors. Nevertheless, financial stress can exhibit a high degree of inertia, which could be better captured by non-stationary factors. To this end, we advocate moving away from the stationary paradigm. In this paper we outline how to select and estimate the correct number of factors in the presence of non-stationary data. In doing so we create a financial stress index for the UK financial market, whose performance we compare to other popular financial stress indices. In a growth-at-risk and a connectedness exercise we show that the proposed method yields better performance at the short forecast horizons, which is of key interest for policy makers.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"43 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A gentle reminder: Should returns be interpreted as log differences?","authors":"David Iheke Okorie","doi":"10.1016/j.irfa.2024.103864","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103864","url":null,"abstract":"It is rather a norm for researchers to directly use the log difference of an asset price to compute returns. Just like using <mml:math altimg=\"si317.svg\"><mml:mo>ln</mml:mo><mml:mfenced close=\")\" open=\"(\"><mml:mrow><mml:mi mathvariant=\"normal\">X</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfenced></mml:math> to avoid taking the natural logarithm of zero(s). However, this log returns is but a conditional approximation of the actual returns. Nonetheless, can log difference approximations and the <mml:math altimg=\"si317.svg\"><mml:mo>ln</mml:mo><mml:mfenced close=\")\" open=\"(\"><mml:mrow><mml:mi mathvariant=\"normal\">X</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfenced></mml:math> common practices produce BLUE estimates? Using the log return as an example, this study discusses the approximation nature and conditions for using the log difference approximation both for the interest regressor and control variables. These conditions are; that both the sample average and variance of the original series tend to zero. When these conditions are not met, the log difference approximation is, in fact, not a good approximation and biases OLS causal estimators. When the conditions are met, it produces unbiased, consistent but less efficient estimators. Thereby making the estimates less precise and less accurate. Nonetheless, this is true for a log differenced interest regressor(s) and control variables, when it correlates with the interest variable(s) and explains, in part, the dependent variable, even in large samples. Similarly, the common use of <mml:math altimg=\"si317.svg\"><mml:mo>ln</mml:mo><mml:mfenced close=\")\" open=\"(\"><mml:mrow><mml:mi mathvariant=\"normal\">X</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfenced></mml:math> biases the estimation of the true causal effect, even the intercept term, except when <mml:math altimg=\"si901.svg\"><mml:mi>X</mml:mi></mml:math> tends to infinity. A robust solution of using non-zero subsamples, against <mml:math altimg=\"si317.svg\"><mml:mo>ln</mml:mo><mml:mfenced close=\")\" open=\"(\"><mml:mrow><mml:mi mathvariant=\"normal\">X</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfenced></mml:math>, produces unbiased and consistent estimators for the true causal effects under the causal assumptions. These biasedness, inconsistencies, and inefficiencies do not disappear in large samples. Finally, both ex-ante and ex-post test statistics are discussed, however, the ex-post estimation test statistic is recommended to confirm both the choice of using log difference approximation and that of using <mml:math altimg=\"si317.svg\"><mml:mo>ln</mml:mo><mml:mfenced close=\")\" open=\"(\"><mml:mrow><mml:mi mathvariant=\"normal\">X</mml:mi><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:mfenced></mml:math>, in an empirical data causal regression analysis. Ideally, researchers should ensure the conditions for using the log difference approximation are met. Otherwise, these approximation","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"10 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tail risk contagion and multiscale spillovers in the green finance index and large US technology stocks","authors":"Hongjun Zeng, Mohammad Zoynul Abedin, Brian Lucey, Shenglin Ma","doi":"10.1016/j.irfa.2024.103865","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103865","url":null,"abstract":"Our purpose is to check the dynamic asymmetric volatility connectedness among the Green Finance Index and six large US technology stocks. The QVAR connectedness framework, the quantile Granger causality test, the TVP-VAR frequency connectedness framework, and the quantile-on-quantile regression (QQR) function were employed to measure the cross-frequency and quantile risk dependencies among these indices. The findings show that: (1) the volatility connectedness effect is higher at extreme tails. In addition, the dynamic spillover between the Green financial index and large US technology stocks is strengthened during bullish market conditions. (2). Net risk spillover characteristics across markets show cyclicality and heterogeneity. The S&P 500 ESG index and Microsoft are the dominant sources of risk. In contrast, the S&P Green Bond Index and Apple act as net recipients of spillovers. (3). Connectedness networks across quartiles exhibit asymmetric behavior. (4). When considering all quartiles, there was a significant Granger causality between the Green Finance Index and major US technology firms. (5). The results of frequency spillovers indicate that long-term frequency spillovers predominate over short-term frequency spillover. The S&P 500 ESG Index contributed risk across frequencies, while green bonds acted as a receiver of risk across frequencies. (6) Utilising the multivariate QQR method, we find the impact of the green finance index on US technology stocks risk exhibited significant non-linear and asymmetric characteristics, demonstrating pronounced cross-quantile heterogeneity. Our empirical findings held practical significance for heterogeneous market participants concerned with the risks associated with green finance and high-tech assets across different investment horizons and market conditions.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"1 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does short-selling threat potentially influence corporate risk-taking? Evidence from equity lending supply","authors":"Ge Lan, Xin Gao, Xiaolan Zheng, Hang Zhou, Donghui Li","doi":"10.1016/j.irfa.2024.103859","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103859","url":null,"abstract":"This study examines whether the equity lending supply strengthens or weakens corporate risk-taking behaviors. The evidence shows that ex-ante short selling can unintentionally function as an external governance mechanism to discipline self-interested, risk-averse managers. This showed an increase in long-term risk-taking among U.S. firms from 2006 to 2017. The robustness of our findings is confirmed by the consistent results obtained using alternative dependent variables and varying data sampling frequencies, which was further reinforced by causality checks through external shocks and instrumental variables. Cross-sectional tests indicate that the disciplinary role played by short sellers is stronger in firms with weaker corporate governance, greater financial constraints, and less incentivized managers. After excluding alternative explanations, we find that the positive impact of short selling on corporate risk-taking is determined by investor attention drawn by short sellers, confirming the disciplinary role of the market's invisible hand. More tests confirm the positive effects of our primary findings. This study provides robust empirical evidence that short sellers have an impact on favorable long-term corporate risk-taking and offers valuable insights for fiscal policy and academic discussion.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"22 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal relation-specific investment, financing, and the supply chain capital structure under uncertainty","authors":"Hongmei Li, Zongyi Zhang, Wei Wang, Fangnan Liao","doi":"10.1016/j.irfa.2024.103854","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103854","url":null,"abstract":"Growing risks and potential disruptions in global supply chains underscore the urgent need to enhance supply resilience. This research focuses on relationship-specific investments by suppliers that target resilience enhancement through performance improvements, cost efficiency, and the establishment of trust. Using a real options framework, we construct a coopetition model between suppliers and manufacturers to investigate how supplier investments and financing decisions are influenced by market uncertainties and bargaining power in the presence of manufacturer subsidies. Our analysis reveals that compared to full equity financing, debt financing by an upstream supplier supported by subsidies from a downstream manufacturer can mitigate underinvestment to some extent. Moreover, in contrast to the existing literature, we find that the effect of leverage on investment timing is non-monotonic. Finally, we identify a U-shaped relationship between suppliers' bargaining power and the timing of relationship-specific investments.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"30 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attention to biodiversity and stock returns","authors":"Imane El Ouadghiri, Olfa Kaabia, Jonathan Peillex, Federico Platania, Celina Toscano Hernandez","doi":"10.1016/j.irfa.2024.103855","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103855","url":null,"abstract":"Our study empirically explores how public interest in biodiversity influences the financial performance of novel investment solutions that specifically promote biodiversity. We consider three distinct metrics capturing public attention to biodiversity: the daily Google Search Volume index for “biodiversity”, the daily media coverage of biodiversity, and the daily visits to the “biodiversity” page on Wikipedia. We also use the UN Biodiversity Conference (COP 15) as quasi-natural experiment. Our econometric analyses reveal a positive association between attention to biodiversity and excess stock returns on biodiversity stock indices. This suggests a growing investor preference for companies with the lowest biodiversity footprints when attention to biodiversity is particularly intense. These fresh insights offer important financial and policy implications.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"252 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"International evidence on the relationship between fraud tolerance and stock price crash risk","authors":"Kenneth Yung, Alireza Askarzadeh","doi":"10.1016/j.irfa.2024.103853","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103853","url":null,"abstract":"Employing a sample of 16,718 firms across 38 countries from 2000 to 2022, we find that ex ante attitudes in society toward dishonest behavior, instead of fraudulent acts, are adequate to provoke firm-level stock price crash risk. Specifically, we document that fraud tolerance in society is positively related to crash risk. The result implies that fraud tolerance promotes managerial opportunistic behavior such as bad news hoarding. Robustness checks show that the result holds after we account for potential issues of endogeneity. We also find evidence implying that ineffective monitoring is a channel connecting fraud tolerance and crash risk. Additional analyses provide results suggesting that fraud tolerance is a persistent behavioral norm unaffected by national culture, including individualism, uncertainty avoidance, and long-term orientation.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"29 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model specification for volatility forecasting benchmark","authors":"Yaojie Zhang, Mengxi He, Yudong Wang, Danyan Wen","doi":"10.1016/j.irfa.2024.103850","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103850","url":null,"abstract":"The ideal model specification for asset price volatility forecasting is still an open question. From a variable transformation perspective, existing studies arbitrarily choose between the raw volatility measure, its square root form, or its natural logarithmic form. In this paper, both the in- and out-of-sample forecasting results support the effectiveness of variable transformation compared to the raw volatility variable. Notably, the logarithmic transformation shows overwhelming advantages. Our results hold across thirty global stock indices, five cryptocurrencies, a crude oil market, as well as a wide range of extensions and robustness checks. In statistics, we find the predictability sources that the logarithmic transformation can lead to more efficient regression estimators by mitigating the heteroscedasticity and serial correlation issues. Consequently, let's make a deal: the benchmark model of volatility forecasting should be based on the natural logarithmic form of the original volatility measure.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"30 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic behavior of green bond premiums","authors":"Takashi Kanamura","doi":"10.1016/j.irfa.2024.103836","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103836","url":null,"abstract":"This paper aims to examine the stochastic behavior of green bond premiums that can characterize the benefits of green bonds. We propose a novel affine model of green bond pricing with mean-reverting interest rates and green bond premiums and a new model parameter estimation method using conventional and green bond prices to capture the stochastic behavior. Then, the model parameter estimation results demonstrate mean-reverting stochastic behavior for conventional bond yield and green bond premium using the US and EU green bond indices for Corporate and three corporate bond indices for intermediate, total, and long-term periods of the Bloomberg Fixed Income Indices from November 3, 2014 to December 11, 2020. Comparative statics using simulated green bond premiums show that green bond premiums orient toward negative values in nature. Moreover, the stochastic behavior of green bond premiums demonstrates that the greenness of green bonds has a downward effect on interest rates in COVID-19 and has a mitigating impact on liquidity risk in corporate bond markets. These results confirm the benefits of green bonds. Finally, the discussions secure the validity of the green bond pricing model by conducting econometric analyses of the regime-switching model, principal component analyses, and the GARCH (1,1) model.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"200 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of inflation and macroprudential policies on bank risk: Evidence from emerging economies","authors":"Xueming Qin, Gangdong Peng, Mengxiang Zhao","doi":"10.1016/j.irfa.2024.103841","DOIUrl":"https://doi.org/10.1016/j.irfa.2024.103841","url":null,"abstract":"This study explores the relationship between macroprudential policies, inflation, and bank risk in emerging economies. Several significant findings emerge based on panel data from approximately 1400 commercial banks across 32 emerging economies over the period 2000–2018. Firstly, a positive correlation is observed between inflation rates and bank risk, suggesting that inflation increases financial instability. Contrary to their intended purpose, stringent macroprudential policies actually intensify bank risk during periods of high inflation rather than stabilizing economies. Secondly, the analysis indicates that macroprudential tools designed to moderate credit cycles significantly enhance the risk banks face from inflation. Varied impacts are observed among different macroprudential instruments: capital-related, reserve requirement, and foreign exchange-related tools counterproductively heighten bank risk during periods of high inflation. Conversely, asset-based and liquidity-focused tools effectively reduce bank risk under similar inflationary conditions.","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"50 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}