Quarterly Review of Economics and Finance最新文献_第2页

Oil price shocks and stock market bubble-risk indicators 油价冲击与股市泡沫风险指标

IF 3.4 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-07-01 Epub Date: 2026-06-24 DOI: 10.1016/j.qref.2026.102178

Elie Bouri, Ufuk Can, Oguzhan Cepni, Rangan Gupta

{"title":"Oil price shocks and stock market bubble-risk indicators","authors":"Elie Bouri, Ufuk Can, Oguzhan Cepni, Rangan Gupta","doi":"10.1016/j.qref.2026.102178","DOIUrl":"10.1016/j.qref.2026.102178","url":null,"abstract":"<div><div>This paper examines whether structural oil price shocks (forward-looking demand, current demand, and supply) help explain variation in daily US stock market positive and negative LPPLS bubble-confidence indicators across short-, medium-, and long-term horizons from June 2007 to January 2025. Unlike standard analyses of returns, volatility, or downside risk, our approach studies whether oil shocks affect confidence that the price-dividend ratio is entering a nonlinear positive or negative LPPLS regime. The results from local projection models show strong and asymmetric effects that depend on the structural source of the oil shock. Current demand shocks tend to increase medium- and long-horizon positive-bubble confidence while reducing negative-bubble confidence, consistent with a pro-cyclical mechanism in which stronger real activity supports optimistic valuation dynamics. Oil supply shocks, by contrast, reduce positive-bubble confidence and increase negative-bubble confidence, consistent with a stagflationary mechanism in which cost, inflation, and discount-rate pressures reinforce negative LPPLS valuation-risk signals. Forward-looking demand shocks generate mixed responses: they tend to reduce positive-bubble confidence at short and medium horizons and raise short- and medium-horizon negative-bubble confidence, while reducing longer-horizon negative-bubble confidence when interpreted as favorable news about future activity. These findings show that the structural origin of oil-price movements helps explain variation in stock-market bubble-risk indicators, beyond what is captured by ordinary equity returns, volatility, or downside-risk measures.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"108 ","pages":"Article 102178"},"PeriodicalIF":3.4,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148542557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The impact of wildfires on US insurance firms: Evidence for the costliest wildfire in California 野火对美国保险公司的影响：加州最昂贵野火的证据

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-06-01 Epub Date: 2026-05-23 DOI: 10.1016/j.qref.2026.102160

António Miguel Martins , Bruno Albuquerque , Luís Sardinha , Nuno Moutinho

引用次数: 0

Revisions of peer firms’ analyst forecasts and corporate investment 修正同行公司的分析师预测和企业投资

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-03-01 Epub Date: 2026-01-22 DOI: 10.1016/j.qref.2026.102124

Huiqi Gan

引用次数: 0

Luck “duels” among factors in China 在中国，运气是各种因素中的“决斗”

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-03-01 Epub Date: 2026-01-22 DOI: 10.1016/j.qref.2026.102125

Ming-Long Wang , Huai-Long Shi , Yu-Lei Wan , Jing-Jin Wang

{"title":"Luck “duels” among factors in China","authors":"Ming-Long Wang , Huai-Long Shi , Yu-Lei Wan , Jing-Jin Wang","doi":"10.1016/j.qref.2026.102125","DOIUrl":"10.1016/j.qref.2026.102125","url":null,"abstract":"<div><div>We investigate the cross-sectional pricing power of factors in the Chinese A-share market under a rigorous multiple-testing framework. We construct 139 characteristic-managed portfolios and 30 principal components (PCs) derived from instrumented PCA (IPCA), risk-premium PCA (RPPCA), and traditional PCA. Using individual stocks as test assets and a bootstrap-based panel regression approach, we evaluate these candidates’ incremental explanatory power while addressing data mining and <span><math><mi>p</mi></math></span>-hacking concerns. We find that latent factors constructed via IPCA and RPPCA – notably IPC9 and RPPC1 – exhibit significant pricing power, whereas traditional PCs fail to provide incremental information. Among characteristic-based portfolios, three-year capital expenditure (CAPEX) growth, debt growth, and eight-quarter earnings consistency stand out by outperforming PCA-derived factors. Beyond statistical robustness, we provide new economic insights by linking factor efficacy to China-specific market frictions. Specifically, we show that IPC9 proxies for retail-driven noise trader risk and RPPC1 captures a flight-to-quality premium in large-cap stocks, yet the pricing power of both factors is strictly confined to market segments accessible to arbitrage capital. Furthermore, we document a structural migration in the CAPEX factor’s efficacy from state-owned to private enterprises, mirroring the secular evolution of China’s industrial policy. Further analysis under value-weighted schemes, small-cap exclusions, and sectoral filters underscores market heterogeneity: large-cap investors prioritize profitability and liquidity, mid-caps exhibit sensitivity to institutional trading dynamics, and non-financial stocks reward long-term investment efficiency. These findings contribute to a better understanding of conventional “factor zoo” paradigms and advocate for hybrid models that integrate standalone characteristics with synthetic risk proxies.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"106 ","pages":"Article 102125"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Harnessing incentives for sustainability: The impact of eco−compensation reform on green innovation in China 可持续发展激励机制：生态补偿改革对中国绿色创新的影响

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-03-01 Epub Date: 2026-02-20 DOI: 10.1016/j.qref.2026.102128

Jinghan Liu , Yanhui Li , Zhaian Bian , Wei Tu , Yinghao Song

{"title":"Harnessing incentives for sustainability: The impact of eco−compensation reform on green innovation in China","authors":"Jinghan Liu , Yanhui Li , Zhaian Bian , Wei Tu , Yinghao Song","doi":"10.1016/j.qref.2026.102128","DOIUrl":"10.1016/j.qref.2026.102128","url":null,"abstract":"<div><div>Against the backdrop of mounting global pressure for ecological governance, how to effectively stimulate corporate green innovation through institutional incentives has become a common challenge faced by nations worldwide. This study investigates the effect of the Ecological Compensation Reward–Punishment Mechanism Reform on corporate green innovation by utilizing a difference−in−differences approach and a panel dataset of A−share listed firms in China spanning 2003–2023. The empirical evidence indicates that the reform plays a significant role in fostering firms’ green innovation activities. Multiple robustness tests, including placebo simulations and PSM−DID estimations, further validate the consistency and reliability of the results. Mechanism analysis indicates that the reform exerts its effect indirectly by enhancing managerial environmental awareness and promoting corporate green transformation. Heterogeneity analysis reveals that firms in non−high−tech sectors, non−polluting industries, and competitive markets are more responsive to the policy, suggesting that institutional−dependent firms have a stronger sensitivity to external green incentives. Moreover, the effect is more pronounced among firms located in central and western China compared to those in the eastern region, indicating that in less−developed, policy−driven areas, the marginal effect of institutional incentives is more substantial. This study contributes micro−level evidence on the impact of ecological compensation policies on corporate green behavior and uncovers the organizational behavior logic of environmental policy mechanisms, providing actionable insights for developing economies and global ecological governance frameworks.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"106 ","pages":"Article 102128"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Consumption, investment, life insurance, and early retirement decisions under habit-dependent living standards 习惯依赖生活标准下的消费、投资、人寿保险和提前退休决定

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-03-01 Epub Date: 2026-02-19 DOI: 10.1016/j.qref.2026.102126

Se Yung Bae , Junkee Jeon , Hyeng Keun Koo

引用次数: 0

How does digital finance influence the share of labor income? Evidence from China 数字金融如何影响劳动收入占比？来自中国的证据

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-03-01 Epub Date: 2026-01-21 DOI: 10.1016/j.qref.2026.102115

Rui Cheng , Wenzhong Yue

引用次数: 0

Mitigating downside risk: ESG integration in portfolio construction with stock preselection using machine learning and mean-CVaR optimization 降低下行风险：利用机器学习和均值cvar优化将ESG整合到投资组合构建和股票预选中

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-03-01 Epub Date: 2026-01-26 DOI: 10.1016/j.qref.2026.102118

Larry Van Wallendael , Line Vanneste , Yanyi Zhang , Alexander Stevens, Johannes De Smedt

{"title":"Mitigating downside risk: ESG integration in portfolio construction with stock preselection using machine learning and mean-CVaR optimization","authors":"Larry Van Wallendael , Line Vanneste , Yanyi Zhang , Alexander Stevens, Johannes De Smedt","doi":"10.1016/j.qref.2026.102118","DOIUrl":"10.1016/j.qref.2026.102118","url":null,"abstract":"<div><div>Recent studies indicate that Environmental, Social, and Governance (ESG) factors are valuable indicators of downside risk. However, research into how ESG integration within portfolio construction can reduce extreme investment risks is limited. This study investigates ESG integration for downside risk mitigation within a dual-phase framework comprising stock preselection and portfolio optimization. ESG scores are incorporated either linearly in actual returns or through negative screening. We utilize various machine learning techniques for stock preselection, followed by mean Conditional Value-at-Risk optimization in the portfolio phase. Our analysis includes both in-sample and out-of-sample testing across periods characterized by low and high market volatility. Results indicate that ESG-informed returns effectively mitigate portfolio downside risk, particularly during volatile periods, while ESG integration through screening proves less effective. Overall, this study contributes novel insights into the nuanced effects of ESG integration strategies on portfolio downside risk management.</div></div>","PeriodicalId":47962,"journal":{"name":"Quarterly Review of Economics and Finance","volume":"106 ","pages":"Article 102118"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The impact of perceived uncertainty on corporate financial asset allocation: Evidence from China 感知不确定性对企业金融资产配置的影响：来自中国的证据

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-03-01 Epub Date: 2026-01-21 DOI: 10.1016/j.qref.2026.102116

Yue Liu , Meng Ju , Qilong Cao

引用次数: 0

Text-implied uncertainty in 10-K filings: Do investors get the message? 10-K文件中文本隐含的不确定性：投资者明白了吗？

IF 3.1 3区经济学

Quarterly Review of Economics and Finance Pub Date : 2026-03-01 Epub Date: 2026-01-28 DOI: 10.1016/j.qref.2026.102121

Oliver Budras, Maik Dierkes, Sebastian Schroen

引用次数: 0