{"title":"The Role of Price-Volatility Cojumps in Volatility Forecasting","authors":"Kefu Liao","doi":"10.1002/fut.70091","DOIUrl":"https://doi.org/10.1002/fut.70091","url":null,"abstract":"<p>This paper investigates whether simultaneous jumps in prices and volatility improve volatility forecasting. Using up-to-date high-frequency S&P 500 and VIX data, we identify price-volatility cojumps at the intraday granularity and construct upside, downside, and asymmetric measures. Embedding these into the Heterogeneous Autoregressive (HAR) model, we provide new empirical evidence that downside cojumps increase future volatility, upside cojumps reduce volatility. Out-of-sample analysis further shows that incorporating these impacts of cojumps significantly enhances HAR model forecasting performance. Moreover, our results reveal that recent price jumps become important predictors of volatility when accompanied by simultaneous volatility jumps, an effect not previously documented in the literature. Finally, we also document the economic interpretation, policy implications, and economic value of price-volatility cojumps.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":"931-951"},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668286","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":"VIX Term Structure in the Rough Heston Model via Markovian Approximation","authors":"Yifan Ye, Zheqi Fan, Yue Kuen Kwok","doi":"10.1002/fut.70082","DOIUrl":"https://doi.org/10.1002/fut.70082","url":null,"abstract":"<div>\u0000 \u0000 <p>We model the VIX term structure using the rough Heston model. Since the direct numerical modeling of the rough Heston model is computationally inefficient, we adopt a Markovian approximation approach. Building on the Markovian framework, we eliminate the need for simulation by exploiting an analytical expression for VIX. The resulting formula for squared VIX under the Markovian approximation provides an analytical approximation to its counterpart under the rough Heston model. Another efficiency in the calibration procedure is achieved by exploiting the analytical gradient formulas of squared VIX. Empirically, using an extensive dataset of daily VIX term structures, we show that the rough Heston model outperforms various competing Heston-type models with jumps in both in-sample and out-of-sample fit and yields more reliable estimates of spot volatility, validating that rough volatility is preferred to jumps in modeling VIX term structure.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":"799-823"},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147669006","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":"Forecasting Crude Oil Volatility With Geopolitical Risk: The RSV–MIDAS–GPR Model and Its Economic Value","authors":"Ke Yang, Xuebao Yin, Fengping Tian","doi":"10.1002/fut.70084","DOIUrl":"https://doi.org/10.1002/fut.70084","url":null,"abstract":"<div>\u0000 \u0000 <p>The paper proposes a new integrated realized stochastic volatility–mixed data sampling–geopolitical risk (RSV–MIDAS–GPR) model to model and forecast crude oil futures volatility. The model jointly models returns and the realized measure of volatility, leverages contemporaneous volatility information, and captures the effects of GPR on crude oil futures volatility. The empirical results demonstrate a significant positive correlation between GPR and crude oil futures volatility. Meanwhile, the RSV–MIDAS–GPR model, which incorporates both GPR and realized volatility, exhibits a synergistic effect, leading to a substantial improvement in out-of-sample forecasting performance. Furthermore, the model demonstrates notable capability in identifying high-volatility states and achieves higher forecasting accuracy than competing models during market turmoil. Finally, economic value tests confirm that the inclusion of GPR provides valuable guidance for investor decision-making. These findings offer both methodological and empirical contributions to the related research field.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":"824-842"},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668080","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":"Journal of Futures Markets: Volume 46, Number 5, May 2026","authors":"","doi":"10.1002/fut.70109","DOIUrl":"https://doi.org/10.1002/fut.70109","url":null,"abstract":"","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70109","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668135","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":"Connectedness Across Healthcare Cryptocurrencies, DeFi, and NFTs Tokens: Which Global Risk Factors Should Be Given More Attention?","authors":"Nasir Khan, Khaled Guesmi, Tong Su, Brian Lucey","doi":"10.1002/fut.70085","DOIUrl":"https://doi.org/10.1002/fut.70085","url":null,"abstract":"<div>\u0000 \u0000 <p>The study examines interconnectedness among categories of cryptocurrencies, healthcare cryptocurrencies, decentralized finance indices (DeFi), and non-fungible tokens using TVP-VAR extended joint connectedness, based on daily data from September 4, 2019, to July 31, 2024. The outcomes indicate that DeFi is the return shock and leading net transmitter, while healthcare cryptocurrencies are the net receivers. Secondly, we also analyze the effect of four news-based global uncertainties on total returns using the BVAR model. The outcomes reveal that geopolitical risk (GPR) does not significantly influence global connectedness; however, some individual DeFi protocols, such as Chain Link, Tezos, and Maker, respond positively to GPR. Conversely, economic policy uncertainty reduces the total connectedness index, while infectious disease equity market volatility increases it. Using weekly data covering cryptocurrency uncertainty indices, exerts a positive effect on total return connectedness. The findings underline the influential crypto assets and should be monitored by investors and policymakers.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":"878-903"},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668742","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":"Downside Risk and Agriculture Commodity Futures Returns: A Study Using Self-Organizing Maps","authors":"Santanu Das","doi":"10.1002/fut.70088","DOIUrl":"https://doi.org/10.1002/fut.70088","url":null,"abstract":"<div>\u0000 \u0000 <p>This study analyzes downside risk and nonlinear dependence in agricultural commodity futures using a hybrid framework that integrates Self-Organizing Maps (SOMs) with Copula-based dependence modeling. Agricultural returns exhibit asymmetric behavior, making linear correlation inadequate for risk assessment. The SOM identifies distinct market regimes based on return dynamics and volatility structure, while Student-<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <mi>t</mi>\u0000 </mrow>\u0000 </mrow>\u0000 </semantics></math> and Clayton copulas quantify symmetric and lower-tail dependence within each regime. Results show a clear escalation of dependence from tranquil to crisis states, with tail-dependence coefficients rising monotonically across SOM clusters. The Student-<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <mi>t</mi>\u0000 </mrow>\u0000 </mrow>\u0000 </semantics></math> copula captures symmetric co-movements in extreme returns, whereas the Clayton copula highlights strong joint downside risk during high-volatility phases. These patterns confirm that diversification benefits across agricultural commodities weaken substantially under stress. The proposed SOM–Copula hybrid framework provides a regime-sensitive approach to modeling tail interdependence in commodity markets.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":"863-877"},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668472","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":"Trading Periodicity and Algorithmic Divide in Cryptocurrency Markets","authors":"Andrei Shynkevich","doi":"10.1002/fut.70089","DOIUrl":"https://doi.org/10.1002/fut.70089","url":null,"abstract":"<div>\u0000 \u0000 <p>Distinctive periodic patterns in trading activity at subsecond frequencies are present in the spot market and perpetual futures for Bitcoin and Ethereum at the major cryptocurrency exchange. Trading periodicity in the spot market is indicative of agency algorithms taking liquidity. The periodic pattern of trading activity in perpetual futures is symbolic of proprietary algorithms taking liquidity. Periodic surges in trading activity recurring at regular time intervals increase volatility and raise transaction costs, but they do not cause a significant adverse price impact. The largest share of price discovery occurs during the periods of trading activity associated with proprietary algorithms taking liquidity.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":"904-930"},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668743","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":"Harnessing Sunshine: A Dynamic Spillover Analysis of the Diversification Effects of China's Photovoltaic Weather Index","authors":"Yu Wei, Yue Shang, Qian Wang, Xiaodan Chen","doi":"10.1002/fut.70087","DOIUrl":"https://doi.org/10.1002/fut.70087","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the diversification effects of China's new photovoltaic weather index (PVWI) on commodity portfolios. Using a TVP-VAR spillover analysis, we find the PVWI is highly insulated from the commodity system, acting as a net shock receiver and confirming its diversification potential. We then construct novel “minimum-connectedness portfolios” (MCoP). Results show that portfolios incorporating the PVWI, particularly the MCoP, significantly enhance risk-adjusted returns and demonstrably outperform traditional minimum-variance benchmarks. This study validates the practical benefits of well-designed weather derivatives and the superiority of spillover-aware asset allocation frameworks.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":"843-862"},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668398","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":"Oil Futures Prices, Inflation Expectations, and Bond Risk Premiums","authors":"Haibo Jiang","doi":"10.1002/fut.70083","DOIUrl":"https://doi.org/10.1002/fut.70083","url":null,"abstract":"<p>By decomposing West Texas Intermediate futures price changes into structural supply and demand shocks, this paper shows that dissecting the oil price significantly improves inflation forecasts. Empirically, demand-driven shocks predict a negative real bond risk premium but a positive inflation risk premium; these opposing effects result in an insignificant net effect on the nominal bond risk premium. A two-sector New Keynesian model formalizes the dynamics among oil shocks, inflation, and bond yields, reconciling two distinct historical episodes: anchored inflation during the 2000s oil crisis and the surge in tandem with oil prices following the 2022 Russian invasion of Ukraine.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 5","pages":"779-798"},"PeriodicalIF":2.3,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668906","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}
Markus Ulze, Johannes Stadler, Andreas W. Rathgeber
{"title":"The Case of Fleeting Orders and Flickering Quotes","authors":"Markus Ulze, Johannes Stadler, Andreas W. Rathgeber","doi":"10.1002/fut.70076","DOIUrl":"https://doi.org/10.1002/fut.70076","url":null,"abstract":"<p>The literature controversially discusses the ambiguous motives and driving forces behind quickly cancelled limit orders (fleeting orders), which are characteristic of high-frequency markets. In particular, manipulative and dysfunctional characteristics are feared. We analyze top-of-book fleeting orders—so-called flickering quotes—and show with an ultra-low latency derivative data set that none of these properties have to be dreaded. On the contrary, flickering quotes are associated with liquid market environments, for example: the prices of “flickering” order books improve by <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <mn>3.90</mn>\u0000 \u0000 <mo>%</mo>\u0000 </mrow>\u0000 </mrow>\u0000 </semantics></math> before trades. The results reveal that flickering quotes are likely due to beneficial price discovery processes. Additionally, HFTs might offer their excess positions at a discount to other participants with these orders.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 4","pages":"629-652"},"PeriodicalIF":2.3,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147567198","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}