Journal of Futures Markets最新文献

{"title":"Journal of Futures Markets: Volume 45, Number 7, July 2025","authors":"","doi":"10.1002/fut.22523","DOIUrl":"https://doi.org/10.1002/fut.22523","url":null,"abstract":"","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 7","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.22523","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244254","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":"Skewness Premium for Short-Term Exposure to Squared Market Returns","authors":"Martin Wallmeier","doi":"10.1002/fut.22615","DOIUrl":"https://doi.org/10.1002/fut.22615","url":null,"abstract":"<p>Following Kraus and Litzenberger, the skewness of stock returns is often modeled as exposure to the square of the market return. We use a trading strategy in S&amp;P 500 options that creates exposure to the square of the S&amp;P 500 return without affecting other characteristics of a direct index investment. This allows us to uniquely identify the skewness premium. We find a significantly negative premium on daily returns, which amounts to a return difference of 5 percentage points per year between a put-based strategy (negative skewness) and a call-based strategy (positive skewness). Our results suggest that short-term exposure to squared market returns is important for investors, even though this exposure declines sharply when returns are aggregated over months or quarters.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 9","pages":"1091-1099"},"PeriodicalIF":2.3,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.22615","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811251","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":"The Reaction of Corn Futures Markets to US and Brazilian Crop Reports","authors":"Rodrigo Lanna Franco da Silveira,&nbsp;Renato Moraes Silva,&nbsp;Fabio L. Mattos,&nbsp;José César Cruz Júnior,&nbsp;Daniel Henrique Dario Capitani","doi":"10.1002/fut.22601","DOIUrl":"https://doi.org/10.1002/fut.22601","url":null,"abstract":"<p>The purpose of this study is to examine the impact of US (WASDE) and Brazilian (CONAB) crop reports on corn futures prices and trading volumes in both the US and Brazilian markets. Employing an intraday announcement analysis, we investigate how return volatilities and trading volumes respond to the release of these reports. Specifically, we compare prices and volume behavior on report days with the 5 days preceding and following the announcements. Using both parametric and nonparametric tests, our results indicate that WASDE report announcements significantly influence returns and trading volumes in both markets. In contrast, the effects of CONAB reports are less pronounced than those associated with WASDE releases.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 9","pages":"1298-1323"},"PeriodicalIF":2.3,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.22601","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811250","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":"Evaluating Market Downturn Connectedness Between S&P 500 Index Funds, Gold, and Oil Markets","authors":"Waheed Ullah Shah,&nbsp;Ibtissem Missaoui,&nbsp;Ijaz Younis,&nbsp;Xiyu Liu","doi":"10.1002/fut.22608","DOIUrl":"https://doi.org/10.1002/fut.22608","url":null,"abstract":"<div>\u0000 \u0000 <p>This study evaluates the market downturn connectedness between S&amp;P 500 index funds and real-time markets (gold and WTI) during the COVID-19 pandemic and the Russia-Ukraine wars. Using the TVP-VAR approach, we explored the significant connectedness among these markets during both crisis episodes. The S&amp;P 500 Index Fund (State Street S&amp;P 500 Index Fund Class N) is the net risk spillover receiver in the system, whereas S&amp;P 500 Index funds (all others) are significant volatility spillover transmitters during the COVID-19 and Russia-Ukraine wars. Furthermore, gold and WTI receive net risk spillovers in both crises. However, all S&amp;P 500 index funds are also pairwise and extensively connected with real-time markets (gold and WTI) in the COVID-19 and Russia-Ukraine wars. This study offers potential investment insights for shareholders, traders, speculators, and portfolio managers in these markets.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 9","pages":"1278-1297"},"PeriodicalIF":2.3,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811247","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":"Spillovers Into the German Electricity Market From the Gas, Coal, and CO2 Emissions Markets","authors":"Filippos Ioannidis,&nbsp;Kyriaki Kosmidou,&nbsp;Panayiotis Theodossiou","doi":"10.1002/fut.22607","DOIUrl":"https://doi.org/10.1002/fut.22607","url":null,"abstract":"<p>This paper investigates the mean, volatility, skewness, and kurtosis of price spillovers from the natural gas, coal, and CO₂ emissions markets into the German electricity market from 2010 to July 2023, segmented into three periods: pre-Russo-Ukrainian war, war-triggered price rise, and postwar adjustment. Utilizing a flexible probability model with time-varying parameters and structural dummies for different periods and days of the week and applying the Bayesian Information Criterion (BIC) for model selection, the analysis reveals: (a) significant bidirectional mean spillovers between gas and coal markets, with coal prices exerting a stronger influence on gas prices; (b) volatility spillovers from the CO₂ market into the electricity market; (c) skewness spillovers from the coal market that negatively impact electricity skewness; and (d) kurtosis spillovers from the CO₂ market. The distribution of electricity price-growth rates is characterized by extreme leptokurtosis and negative skewness, reflecting extreme price movements. These findings underscore the complex dynamics of these interconnected markets, offering valuable insights for market participants, policymakers, and risk managers in forecasting, hedging strategies, and pricing electricity derivatives during market turbulence.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 9","pages":"1253-1277"},"PeriodicalIF":2.3,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.22607","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811356","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":"Option Return Predictability via Machine Learning: New Evidence From China","authors":"Yuxiang Huang,&nbsp;Zhuo Wang,&nbsp;Zhengyan Xiao","doi":"10.1002/fut.22604","DOIUrl":"https://doi.org/10.1002/fut.22604","url":null,"abstract":"<div>\u0000 \u0000 <p>We extend the literature on empirical asset pricing to the Chinese options market by building and analyzing a comprehensive set of return prediction factors using various machine learning methods. In contrast to previous studies for the US market, we emphasize the uniqueness of this emerging market, investigate daily hedging strategies to construct delta-neutral portfolios, and identify the most important characteristics for return prediction. Short-selling restrictions in China's financial market diminish the effectiveness of spot hedging, whereas delta-neutral portfolios based on futures hedging deliver substantial improvements in both annual returns and Sharpe ratios. Machine learning models not only outperform the IPCA benchmark, but also demonstrate strong generalization ability when applied to newly issued option contracts. The out-of-sample performance remains economically significant after accounting for transaction costs.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 9","pages":"1232-1252"},"PeriodicalIF":2.3,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811325","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":"Generalized Modeling of Oil Futures Volatility Through Uncertainty Indicator Selection: A GARCH–MIDAS–AES Framework","authors":"Siyue Zheng,&nbsp;Mingdong Xu,&nbsp;Min Zhu","doi":"10.1002/fut.22605","DOIUrl":"https://doi.org/10.1002/fut.22605","url":null,"abstract":"<div>\u0000 \u0000 <p>Building on prior literature that has demonstrated the effectiveness of various uncertainty-related indicators in enhancing the accuracy of crude oil volatility forecasting, this paper first investigates the type and persistence of the impact of changes in these indicators on volatility and then compares these indicators across different scenarios to determine the optimal strategy for their implementation. We employ a more generalized approach by utilizing the GARCH–MIDAS–AES model, which accommodates features that vary with different indicators. The empirical results, based on data from 1997 to 2022, underscore the importance of considering threshold and leverage effects. We also identify two types of impact: directional and nondirectional. Furthermore, among the uncertainty indicators examined, our findings affirm the predictive prowess of the Financial Uncertainty indicator in the majority of cases. However, during periods of global crisis, the Index of Global Real Economic Activity emerges as a more practical choice.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 9","pages":"1182-1201"},"PeriodicalIF":2.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811305","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":"Black-Scholes Meet Imitation Learning: Evidence From Deep Hedging in China","authors":"Fuwei Jiang,&nbsp;Jie Kang,&nbsp;Ruzheng Tian,&nbsp;Qingdong Xu","doi":"10.1002/fut.22596","DOIUrl":"https://doi.org/10.1002/fut.22596","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper introduces an imitation learning deep hedging (ILDH) algorithm, which bridges the Black-Scholes-Merton (BSM) model with deep reinforcement learning (DRL) to address the option hedging problem in incomplete real markets. By leveraging imitation learning, the DRL agent optimizes its hedging policy using both freely explored action samples based on real trading data and corresponding action demonstrations derived from the BSM model. These demonstrations serve as data augmentation, enabling the agent to develop a meaningful policy even with a relatively small training data set and enhancing the management of tail risk. Empirical results show that ILDH achieves higher profit, lower risk, and lower cost in the Chinese stock index options market, as compared with other deep hedging algorithms and traditional delta hedging method. This outperformance is robust across call and put options, different transaction cost conditions, and varying levels of risk aversion.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 8","pages":"1071-1087"},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581794","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":"Identifying Stock Option Mispricing at a Large Cross Section","authors":"Yaofei Xu,&nbsp;Dalu Zhang,&nbsp;Zhiyong Li,&nbsp;Shuoxiang Wang","doi":"10.1002/fut.22606","DOIUrl":"https://doi.org/10.1002/fut.22606","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper introduces an innovative two-step approach for identifying implied volatility (IV) mispricing across a large cross-section, moving beyond the traditional volatility forecasting framework. The two-step process disentangles the contributions of historical volatility and other firm-specific characteristics, isolating the residual as the IV mispricing. Different from traditional IV misvaluation proxies, which primarily focus on 1-month at-the-money (ATM) options, our method demonstrates broader applicability. It accommodates options with wider maturities and extends to both ATM and out-of-the-money (OTM) call and put options. Applying a long-short delta-hedged options trading strategy, using the IV mispricing, achieves a high information ratio (IR). When incorporating short- and long-term historical volatility trends as conditions, while returns remain relatively unchanged, portfolio volatility is significantly reduced, further enhancing the IR to 4.093. This approach provides a robust predictive signal for option returns and remains resilient to transaction costs, consistently outperforming alternative signals, as validated through double-sorting analysis.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 9","pages":"1202-1231"},"PeriodicalIF":2.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811306","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":"Greeks-Neutral Option Excess Returns","authors":"Yaofei Xu,&nbsp;Yi Hong,&nbsp;Pei Jose Liu,&nbsp;Zhendong Zhang","doi":"10.1002/fut.22598","DOIUrl":"https://doi.org/10.1002/fut.22598","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;p&gt;This study investigates the linkage between ex-ante expected greeks-neutral excess return (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 \u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;EER&lt;/mi&gt;\u0000 \u0000 &lt;mi&gt;GN&lt;/mi&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) and ex-post realized greeks-neutral excess return (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 \u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;RER&lt;/mi&gt;\u0000 \u0000 &lt;mi&gt;GN&lt;/mi&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;). Employing the top-down framework, we show that &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 \u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;EER&lt;/mi&gt;\u0000 \u0000 &lt;mi&gt;GN&lt;/mi&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; is determined by the difference between the market-derived implied volatility and the estimated implied volatility absent arbitrage opportunities. Serving &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 \u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;EER&lt;/mi&gt;\u0000 \u0000 &lt;mi&gt;GN&lt;/mi&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; as the optimal predictor of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 \u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;RER&lt;/mi&gt;\u0000 \u0000 &lt;mi&gt;GN&lt;/mi&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, we first find that &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 \u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;EER&lt;/mi&gt;\u0000 \u0000 &lt;mi&gt;GN&lt;/mi&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; positively predicts &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 \u0000 &lt;mrow&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;RER&lt;/mi&gt;\u0000 \u0000 &lt;mi&gt;GN&lt;/mi&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;. Second, the bottom-up &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 \u0000 &lt;mrow&gt;\u0000 ","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"45 8","pages":"1049-1070"},"PeriodicalIF":1.8,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581853","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}