Hangsuck Lee, Yisub Kye, Haewon Seo, Donghyun Kim, Hongjun Ha
{"title":"Valuing American Fractional Lookback Options","authors":"Hangsuck Lee, Yisub Kye, Haewon Seo, Donghyun Kim, Hongjun Ha","doi":"10.1002/fut.70115","DOIUrl":"https://doi.org/10.1002/fut.70115","url":null,"abstract":"<div>\u0000 \u0000 <p>This study presents an analytical framework for the valuation of American fractional floating-strike lookback options, taking into account both path dependency and the possibility of early exercise. The proposed pricing methodology is based on the Mellin transform technique, through which we derive and solve the associated partial differential equations governing the pricing functions. A key contribution of this work is the explicit characterization of the early-exercise premium via an integral equation, in contrast to existing methods that typically rely on implicit expressions obtained through inverse transformations. This explicit form provides a more transparent understanding of the structure and behavior of the early-exercise premium. Numerical experiments are conducted to confirm the accuracy and stability of the proposed approach in approximating the true option values.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 9","pages":"1475-1500"},"PeriodicalIF":2.8,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148667466","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":"Neural Jumps for Option Pricing","authors":"Duosi Zheng, Hanzhong Guo, Yanchu Liu, Wei Huang","doi":"10.1002/fut.70125","DOIUrl":"https://doi.org/10.1002/fut.70125","url":null,"abstract":"<div>\u0000 \u0000 <p>Motivated by the importance of jump risk in option pricing, we propose a neural jump stochastic differential equation model that integrates neural networks as parameter estimators into a conventional jump-diffusion model. To address the incompatibility between the backpropagation algorithm and the jump process, we use the Gumbel-Softmax method to obtain differentiable gradients for jump parameters. We evaluate the model on both simulated data and S&P 500 index options. The results show that incorporating neural jump components substantially improves pricing accuracy relative to existing benchmark models.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 9","pages":"1660-1679"},"PeriodicalIF":2.8,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148667520","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":"Reciprocal Return Risk Premium and Option Returns","authors":"Bowen Du","doi":"10.1002/fut.70122","DOIUrl":"https://doi.org/10.1002/fut.70122","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper presents a robust new finding that reciprocal return risk premium, defined as the difference between the expected reciprocal of return under physical and risk-neutral measures, significantly predicts the option returns in the cross-section. Theoretical and empirical evidence underscore the pivotal role of the ex post volatility risk premium in this relation. We also find that the positive relation between reciprocal return risk premium and option return mainly resides in the <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 \u0000 <mrow>\u0000 <mi>R</mi>\u0000 \u0000 <mi>V</mi>\u0000 \u0000 <mi>I</mi>\u0000 \u0000 <msup>\u0000 <mi>X</mi>\u0000 \u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 </mrow>\u0000 </semantics></math> component, which is by definition a natural measure for return variation under the risk-neutral measure.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 9","pages":"1570-1606"},"PeriodicalIF":2.8,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148667198","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":"A New Analytical Approach for Pricing Variance and Volatility Swaps: Incorporating Liquidity and Self-Exciting Jumps","authors":"Xin-Jiang He, Dong Yan, Sha Lin","doi":"10.1002/fut.70120","DOIUrl":"https://doi.org/10.1002/fut.70120","url":null,"abstract":"<div>\u0000 \u0000 <p>Our investigation focuses on the valuation of variance and volatility swaps by incorporating both clustered jump behaviors and liquidity-related risk factors. The proposed modeling framework characterizes stock price movements using a jump-diffusion process, where Hawkes processes govern the jump component in the absence of liquidity effects. Stochastic liquidity is further integrated through a discount factor that modifies the underlying asset value. To preserve model generality, we introduce a complete correlation framework across all Brownian motions involved. A change of measure is applied to express the dynamics under a risk-neutral pricing measure. Subsequently, the forward characteristic function associated with the log-price is expressed analytically, enabling the derivation of closed-form swap valuation formulae. Using daily data from the Brent crude oil futures continuous contract, we calibrate relevant model parameters, providing empirical evidence supporting jump clustering. Numerical implementation of the formulae further offers insights into their sensitivity to variations in model parameters.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 9","pages":"1555-1569"},"PeriodicalIF":2.8,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148667333","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":"Correction to “Determinants of Price Discovery in Option Markets: An Interpretable Machine Learning Perspective”","authors":"","doi":"10.1002/fut.70130","DOIUrl":"https://doi.org/10.1002/fut.70130","url":null,"abstract":"<p>Liang, J., D. Yang, and Q. Han. 2026. “Determinants of Price Discovery in Option Markets: An Interpretable Machine Learning Perspective.” <i>Journal of Futures Markets</i> 46: 237–261.</p><p>There is a factual error in the affiliation for the third (and corresponding) author, Qian Han. The current version “Lingnan College, Sun Yat-Sen University, Hunan University, Guangzhou, Guangdong, China.” is incorrect.</p><p>Please remove “Hunan University”. The correct affiliation should be: “Lingnan College, Sun Yat- sen University, Guangzhou, Guangdong, China.”</p><p>We apologize for this error.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 9","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148667410","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":"Pricing Parisian and ParAsian Options by a Vectorized Binomial or Trinomial Tree","authors":"James X. Wu, Tao Wu","doi":"10.1002/fut.70110","DOIUrl":"https://doi.org/10.1002/fut.70110","url":null,"abstract":"<div>\u0000 \u0000 <p>We extend binomial and trinomial trees to price European and American style Parisian and ParAsian options by keeping track of a vector of option prices under different scenarios at each tree node. We also incorporate the method for choosing the number of time-steps that will yield more precise price estimates. The vectorized tree models can easily price exotic path-dependent options such as American double barrier Parisian options and look-back options, which present challenges to other existing methods.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 8","pages":"1380-1389"},"PeriodicalIF":2.8,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534434","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":"Asymmetric Option Returns in China","authors":"Xianzhen Wang, Xin Zhou","doi":"10.1002/fut.70095","DOIUrl":"https://doi.org/10.1002/fut.70095","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper documents two return asymmetries in China's options market: call (put) returns are positive (negative) overnight but negative (positive) intraday. We provide a demand-pressure-based explanation for this phenomenon, identifying retail investors' gambling motives as the primary catalyst, which are particularly salient following negative realizations of underlying returns. Additionally, insurance-driven demand accounts for the negative overnight put returns, while attention-driven demand contributes to the night-day asymmetry in call returns. Despite institutional investors exploiting these mispricings, the asymmetries persist over time, leaving retail investors to bear losses as counterparties.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 8","pages":"1315-1349"},"PeriodicalIF":2.8,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148532894","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":"Analytically Pricing European Options Under Two-Factor Stochastic Volatility With Stochastic Liquidity Risks","authors":"Xin-Jiang He, Hang Chen, Sha Lin","doi":"10.1002/fut.70114","DOIUrl":"https://doi.org/10.1002/fut.70114","url":null,"abstract":"<div>\u0000 \u0000 <p>This article examines the pricing of European options while incorporating liquidity risks, extending the classical Heston stochastic volatility framework. A new methodology is proposed by incorporating both liquidity risk and stochastic long-term variance into the model, improving its capacity to reflect market dynamics. By applying measure transformation, the model dynamics are formulated under an equivalent martingale measure, leading to an analytical expression for the characteristic function of the stock price logarithm. This yields a closed-form solution for European option pricing, which is subsequently benchmarked against existing models through numerical simulations to evaluate its pricing accuracy and parameter sensitivity. Empirical analysis is conducted to examine the performance of the model using market data.</p>\u0000 </div>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 8","pages":"1423-1439"},"PeriodicalIF":2.8,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534416","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":"Time-Varying Skewness–Kurtosis Dynamics in Bitcoin Markets","authors":"Ariston Karagiorgis, Antonis Ballis","doi":"10.1002/fut.70117","DOIUrl":"https://doi.org/10.1002/fut.70117","url":null,"abstract":"<p>This paper examines the relationship between skewness and kurtosis in Bitcoin spot and futures markets using high-frequency data. We document a strong convex skewness–kurtosis relationship consistent with theoretical moment restrictions. Trading activity is positively associated with realized kurtosis, particularly in futures markets, though sensitive to specification and driven by extreme-return episodes. Allowing the relationship to evolve over time reveals substantial curvature variation, indicating state-dependent higher-moment dynamics. The close co-movement of results across markets suggests patterns reflect broad market-wide conditions. The empirical framework is reduced-form and results should be interpreted as conditional associations rather than causal effects.</p>","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 8","pages":"1440-1452"},"PeriodicalIF":2.8,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534467","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 8, August 2026","authors":"","doi":"10.1002/fut.70129","DOIUrl":"https://doi.org/10.1002/fut.70129","url":null,"abstract":"","PeriodicalId":15863,"journal":{"name":"Journal of Futures Markets","volume":"46 8","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fut.70129","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148532572","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}