Journal of Futures Markets最新文献

{"title":"The Impact of Derivative Use on Default Probability Among Nonfinancial Firms: Evidence From European Firms","authors":"Amrit Judge,&nbsp;Khai Le,&nbsp;Kim Ly","doi":"10.1002/fut.70071","DOIUrl":"https://doi.org/10.1002/fut.70071","url":null,"abstract":"<p>This paper examines how institutional environments shape the effectiveness of derivative hedging in reducing corporate default risk. Using hand-collected data from non-financial firms across nine European countries and various econometric methods to control for endogeneity, we provide novel evidence that the risk-reducing benefits of derivative usage are significantly enhanced in stronger creditor rights settings. Additionally, we document that the default risk-reducing effect of derivatives diminishes in countries with lower economic risk. We also find that for firms in severe financial distress, hedging does not reduce default likelihood. Regarding types of derivatives, we show that interest rate derivatives have a stronger default risk-reducing effect than foreign exchange and commodity derivatives.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 3","pages":"562-581"},"PeriodicalIF":2.3,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146139767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Signature Decomposition Method Applying to Pair Trading","authors":"Zihao Guo,&nbsp;Hanqing Jin,&nbsp;Jiaqi Kuang,&nbsp;Zhongmin Qian,&nbsp;Jinghan Wang","doi":"10.1002/fut.70075","DOIUrl":"https://doi.org/10.1002/fut.70075","url":null,"abstract":"<div>\u0000 \u0000 <p>High-frequency quantitative trading strategies have long been of significant interest in futures market. While advanced statistical arbitrage and deep learning enhance high-frequency data processing, they diminish opportunities for traditional methods and yield less interpretable, unstable strategies. Consequently, developing stable, interpretable quantitative strategies remains a priority in futures markets. In this study, we propose a novel pair trading strategy by leveraging the mathematical concept of path signature which serves as a feature representation of time series. Specifically, the path signature is decomposed into two new indicators: the path interactivity indicator segmented signature and the directional indicator covariation of increments, which serve as double filters in strategy design. Empirical experiments using minute-level futures data show our strategy significantly outperforms traditional pair trading, delivering higher returns, lower maximum drawdown, and higher Sharpe ratio. The proposed method enhances interpretability and robustness while maintaining strong returns, demonstrating the potential of path signatures in financial trading.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 3","pages":"582-603"},"PeriodicalIF":2.3,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146139766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Dynamics for the Underlying Asset and Its Implied Volatility Surface: A New Methodology for Option Risk Management","authors":"Pascal François,&nbsp;Rémi Galarneau-Vincent,&nbsp;Geneviève Gauthier,&nbsp;Frédéric Godin","doi":"10.1002/fut.70068","DOIUrl":"https://doi.org/10.1002/fut.70068","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper develops a dynamic joint model of the implied volatility (IV) surface and its underlying asset which is tractable and seamless to estimate. The model combines an asymptotically well-behaved, parametric IV surface representation with a two-component variance, and non-Gaussian asymmetric GARCH specification for the underlying asset returns. Estimated on S&amp;P 500 index return and option data for the 1996–2020 period, the model captures the IV surface movements well and uses them to obtain an improved fit on index returns. It also proves to be an effective risk management tool, producing reliable Value-at-Risk estimates for straddle and strangle positions, and accurate forecasts of the VIX distribution.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 3","pages":"545-561"},"PeriodicalIF":2.3,"publicationDate":"2025-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146148053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When the Tail Wags the Dog: A Time-Varying FCVAR Analysis of Bitcoin Market","authors":"Filippo di Pietro,&nbsp;Antonio A. Golpe,&nbsp;Jose Carlos Vides","doi":"10.1002/fut.70069","DOIUrl":"https://doi.org/10.1002/fut.70069","url":null,"abstract":"<p>This paper examines how the relationship between Bitcoin spot and futures markets has evolved using a time-varying Fractionally Cointegrated Vector Autoregressive (FCVAR) model. We are the first to apply this methodology dynamically to cryptocurrency markets, allowing us to simultaneously analyze long-run equilibrium, pricing patterns, market efficiency, and price discovery as they change over time. We document three main results. Bitcoin futures dominate price discovery, driving 80% of permanent price movements and highlighting how regulated derivative markets lead information flow. The adjustment between spot and futures prices occurs slowly and persistently, showing long-memory effects that suggest only partial market efficiency. Finally, while these markets typically maintain parity, we frequently observe contango during periods of high volatility, market optimism, or speculative activity. Our approach offers a comprehensive framework for understanding how digital asset prices form, providing valuable insights for market participants and regulators about the role of institutional infrastructure in cryptocurrency markets.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 3","pages":"529-544"},"PeriodicalIF":2.3,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146154829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Journal of Futures Markets: Volume 46, Number 1, January 2026","authors":"","doi":"10.1002/fut.70073","DOIUrl":"https://doi.org/10.1002/fut.70073","url":null,"abstract":"","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 1","pages":"1-2"},"PeriodicalIF":2.3,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145706530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crash Risk Matters: An Option-Implied Approach to the Expected Market Return","authors":"Qiang Chen,&nbsp;Xinyi Song","doi":"10.1002/fut.70070","DOIUrl":"https://doi.org/10.1002/fut.70070","url":null,"abstract":"<div>\u0000 \u0000 <p>This study introduces a lower bound that integrates the market's simple return risk-neutral variance (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <mi>SVI</mi>\u0000 \u0000 <msubsup>\u0000 <mi>X</mi>\u0000 \u0000 <mi>t</mi>\u0000 \u0000 <mn>2</mn>\u0000 </msubsup>\u0000 </mrow>\u0000 </mrow>\u0000 </semantics></math>) and a combination of log-return moments (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <mi>VI</mi>\u0000 \u0000 <msubsup>\u0000 <mi>X</mi>\u0000 \u0000 <mi>t</mi>\u0000 \u0000 <mn>2</mn>\u0000 </msubsup>\u0000 </mrow>\u0000 </mrow>\u0000 </semantics></math>) to predict market log returns. A distinctive feature of the model is that the ratio of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <mi>VI</mi>\u0000 \u0000 <msubsup>\u0000 <mi>X</mi>\u0000 \u0000 <mi>t</mi>\u0000 \u0000 <mn>2</mn>\u0000 </msubsup>\u0000 </mrow>\u0000 </mrow>\u0000 </semantics></math> to <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <mi>SVI</mi>\u0000 \u0000 <msubsup>\u0000 <mi>X</mi>\u0000 \u0000 <mi>t</mi>\u0000 \u0000 <mn>2</mn>\u0000 </msubsup>\u0000 </mrow>\u0000 </mrow>\u0000 </semantics></math> captures crash risk, and the lower bound of log returns depends on the joint effect of crash risk and risk-neutral variance. Our in-sample analysis shows that crash risk exhibits significant predictive power for market returns, and its marginal effect differs markedly between crisis and noncrisis periods. In out-of-sample testing, we argue that crash risk outperforms several benchmarks in return prediction, while the joint effects of crash risk and variance risk achieves higher accuracy in forecasting crash events. We further demonstrate that our model delivers superior performance when the risk aversion is high, particularly during periods of crises.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 3","pages":"511-528"},"PeriodicalIF":2.3,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146139428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does Sentiment Measured Through Language Models Encompass a Broader Expanse of Information From the Options Market?","authors":"Enmao Liu,&nbsp;Cong Sui","doi":"10.1002/fut.70066","DOIUrl":"https://doi.org/10.1002/fut.70066","url":null,"abstract":"<div>\u0000 \u0000 <p>Language models have emerged as powerful tools for measuring textual sentiment. Do sentiment indices derived from language models and textual data truly capture richer informational content? Drawing on a theoretical model, this paper illustrates how market sentiment embedded in news-texts shapes investors' risk aversion and influences their inclination to speculation. This dynamic drives more frequent trading activities, ultimately exerting an impact on the options market. Using news data from <i>The Wall Street Journal</i> as the corpus, we employ language models to construct a market sentiment index. Our findings validate the predictions of the theoretical model: market sentiment exerts a significant direct effect on option prices and indirectly influences them through risk aversion as a mediating variable. Furthermore, empirical evidence reveals that uncertainty significantly moderates both the direct and mediated channels linking market sentiment to option prices. Capturing market sentiment precisely, language models are indispensable for asset pricing sentiment analysis.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 3","pages":"489-510"},"PeriodicalIF":2.3,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146139429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investor Attention and Carbon Prices: Evidence From European Union and China","authors":"Jing Ye,&nbsp;Na Wu","doi":"10.1002/fut.70062","DOIUrl":"https://doi.org/10.1002/fut.70062","url":null,"abstract":"<div>\u0000 \u0000 <p>We investigate the impact of heterogeneous investor attention on carbon prices. Although previous research has demonstrated the influence of investor attention on asset prices, how investors attribute attention toward the carbon-market, emission, and environment issues, and their consequences on carbon prices remain unknown. Leveraging data from the European Union (EU) and Chinese (Guangdong and Hubei pilots) carbon markets, our regression results reveal that investor attention toward the carbon-market and environment issues negatively affects carbon prices in the EU Emissions Trading System, whereas attention toward the carbon-market and emission issues exhibits positive impacts in the Guangdong pilot. Interestingly, these effects are reversed in the subsequent month, implying a lasting effect of investor attention. Additional analyses suggest that the different reactions in the EU and China can be attributed to investor types and green assets diversity. Finally, we demonstrate the economic usefulness of heterogeneous investor attention in improving carbon trading investors' trading strategies.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 2","pages":"463-486"},"PeriodicalIF":2.3,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Market Returns Using Covariance Asymmetry Risk Premium","authors":"Zhenxiong Li,&nbsp;Xinfeng Ruan,&nbsp;Xingzhi Yao","doi":"10.1002/fut.70065","DOIUrl":"https://doi.org/10.1002/fut.70065","url":null,"abstract":"<div>\u0000 \u0000 <p>Implied covariance asymmetry is a market-wide measure defined as the average of the absolute difference between the downside and upside pairwise co-movements of individual stocks, estimated from options data. Its risk premium is linked to improved long-term economic conditions and significantly forecasts excess market returns from 1 month to 2 years. This predictive power persists at horizons beyond 6 months after controlling for popular financial and economic predictors in in-sample analyses. It also translates into superior out-of-sample forecasts and substantial economic gains for a mean-variance investor, particularly over medium and long horizons.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 2","pages":"435-462"},"PeriodicalIF":2.3,"publicationDate":"2025-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does Financial Stress Affect Commodity Futures Traders' Positions?","authors":"Shengwu Du,&nbsp;Travis D. Nesmith,&nbsp;Yanggen Heppe","doi":"10.1002/fut.70064","DOIUrl":"https://doi.org/10.1002/fut.70064","url":null,"abstract":"<div>\u0000 \u0000 <p>We examine trading behavior in commodity futures markets in the United States during the 2008 Global Financial Crisis (GFC) and the COVID-19 pandemic, focusing on absolute changes and relative exposure dynamics. These crises led to distinctly different trading patterns. During the 2008 GFC, speculators rapidly closed long positions while producers facilitated these trades, shifting risk from speculators to producers. In contrast, during the COVID-19 crisis—characterized by milder financial stress and an early commodity market rally—there was not meaningful risk transfer from speculators. The impact on traders' relative exposures was minimal in both crises. However, speculators generally showed greater sensitivity to changing financial conditions than hedgers throughout the study period. These findings highlight the varying impacts of financial stress on commodity futures markets and the importance of crisis-specific context in understanding trader behavior.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 2","pages":"413-434"},"PeriodicalIF":2.3,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}