发布求助
文献互助 智能选刊 最新文献

Journal of Computational Finance最新文献

筛选
英文 中文
Analytical conversion between implied volatilities based on different dividend models 基于不同股利模型的隐含波动率的分析转换
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2022-01-01 DOI: 10.21314/jcf.2022.026
V. Lucic, V. Jovanovic
{"title":"Analytical conversion between implied volatilities based on different dividend models","authors":"V. Lucic, V. Jovanovic","doi":"10.21314/jcf.2022.026","DOIUrl":"https://doi.org/10.21314/jcf.2022.026","url":null,"abstract":"","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67703072","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}
引用次数: 0
A general firm value model under partial information 部分信息下的一般企业价值模型
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2022-01-01 DOI: 10.21314/jcf.2022.020
Cheikh Mbaye, Abass Sagna, Frédéric Vrins
{"title":"A general firm value model under partial information","authors":"Cheikh Mbaye, Abass Sagna, Frédéric Vrins","doi":"10.21314/jcf.2022.020","DOIUrl":"https://doi.org/10.21314/jcf.2022.020","url":null,"abstract":"","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67702934","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}
引用次数: 0
Simulating the Cox–Ingersoll–Ross and Heston processes: matching the first four moments 模拟Cox-Ingersoll-Ross和Heston过程:匹配前四阶矩
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2022-01-01 DOI: 10.21314/jcf.2022.022
Ostap Okhrin, M. Rockinger, M. Schmid
{"title":"Simulating the Cox–Ingersoll–Ross and Heston processes: matching the first four moments","authors":"Ostap Okhrin, M. Rockinger, M. Schmid","doi":"10.21314/jcf.2022.022","DOIUrl":"https://doi.org/10.21314/jcf.2022.022","url":null,"abstract":"","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67702956","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}
引用次数: 3
Automatic differentiation for diffusion operator integral variance reduction 自动微分扩散算子积分方差减少
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2022-01-01 DOI: 10.21314/jcf.2021.013
Johan Auster
{"title":"Automatic differentiation for diffusion operator integral variance reduction","authors":"Johan Auster","doi":"10.21314/jcf.2021.013","DOIUrl":"https://doi.org/10.21314/jcf.2021.013","url":null,"abstract":"","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":"23 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138537391","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}
引用次数: 0
Multilevel Monte Carlo simulation for VIX options in the rough Bergomi model 在粗糙的Bergomi模型中对VIX期权进行多层蒙特卡罗模拟
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2021-05-11 DOI: 10.21314/jcf.2022.023
Florian Bourgey, S. Marco
{"title":"Multilevel Monte Carlo simulation for VIX options in the rough Bergomi model","authors":"Florian Bourgey, S. Marco","doi":"10.21314/jcf.2022.023","DOIUrl":"https://doi.org/10.21314/jcf.2022.023","url":null,"abstract":"We consider the pricing of VIX options in the rough Bergomi model. In this setting, the VIX random variable is defined by the one-dimensional integral of the exponential of a Gaussian process with correlated increments, hence approximate samples of the VIX can be constructed via discretization of the integral and simulation of a correlated Gaussian vector. A Monte-Carlo estimator of VIX options based on a rectangle discretization scheme and exact Gaussian sampling via the Cholesky method has a computational complexity of order $mathcal{O}(varepsilon^{-4})$ when the mean-squared error is set to $varepsilon^2$. We demonstrate that this cost can be reduced to $mathcal{O}(varepsilon^{-2} log^2(varepsilon))$ combining the scheme above with the multilevel method, and further reduced to the asymptotically optimal cost $mathcal{O}(varepsilon^{-2})$ when using a trapezoidal discretization. We provide numerical experiments highlighting the efficiency of the multilevel approach in the pricing of VIX options in such a rough forward variance setting.","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43819467","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}
引用次数: 5
Least squares Monte Carlo methods in stochastic Volterra rough volatility models 随机Volterra粗糙波动模型的最小二乘蒙特卡罗方法
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2021-05-10 DOI: 10.21314/jcf.2022.027
H. Guerreiro, João Guerra
{"title":"Least squares Monte Carlo methods in stochastic Volterra rough volatility models","authors":"H. Guerreiro, João Guerra","doi":"10.21314/jcf.2022.027","DOIUrl":"https://doi.org/10.21314/jcf.2022.027","url":null,"abstract":"In stochastic Volterra rough volatility models, the volatility follows a truncated Brownian semi-stationary process with stochastic vol-of-vol. Recently, efficient VIX pricing Monte Carlo methods have been proposed for the case where the vol-of-vol is Markovian and independent of the volatility. Following recent empirical data, we discuss the VIX option pricing problem for a generalized framework of these models, where the vol-of-vol may depend on the volatility and/or not be Markovian. In such a setting, the aforementioned Monte Carlo methods are not valid. Moreover, the classical least squares Monte Carlo faces exponentially increasing complexity with the number of grid time steps, whilst the nested Monte Carlo method requires a prohibitive number of simulations. By exploring the infinite dimensional Markovian representation of these models, we device a scalable least squares Monte Carlo for VIX option pricing. We apply our method firstly under the independence assumption for benchmarks, and then to the generalized framework. We also discuss the rough vol-of-vol setting, where Markovianity of the vol-of-vol is not present. We present simulations and benchmarks to establish the efficiency of our method. Keywords— VIX, rough volatility, stochastic Volterra models, least squares Monte Carlo, volatility of volatility ∗Supported by FCT Grant SFRH/BD/147161/2019. †Partially supported by the project CEMAPRE/REM-UiDB/05069/2020 financed by FCT/MCTES through national funds. 1 ar X iv :2 10 5. 04 51 1v 1 [ qfi n. PR ] 1 0 M ay 2 02 1","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46636320","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}
引用次数: 1
The CTMC–Heston model: calibration and exotic option pricing with SWIFT CTMC-Heston模型:校准和外来的期权定价与SWIFT
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2021-03-29 DOI: 10.21314/JCF.2020.398
Álvaro Leitao, J. Kirkby, L. Ortiz-Gracia
{"title":"The CTMC–Heston model: calibration and exotic option pricing with SWIFT","authors":"Álvaro Leitao, J. Kirkby, L. Ortiz-Gracia","doi":"10.21314/JCF.2020.398","DOIUrl":"https://doi.org/10.21314/JCF.2020.398","url":null,"abstract":"","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43328770","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}
引用次数: 0
Penalty methods for bilateral XVA pricing in European and American contingent claims by a partial differential equation model 基于偏微分方程模型的欧美或有索赔双边XVA定价惩罚方法
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2021-03-23 DOI: 10.21314/JCF.2020.402
Yuwei Chen, C. Christara
{"title":"Penalty methods for bilateral XVA pricing in European and American contingent claims by a partial differential equation model","authors":"Yuwei Chen, C. Christara","doi":"10.21314/JCF.2020.402","DOIUrl":"https://doi.org/10.21314/JCF.2020.402","url":null,"abstract":"","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47783360","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}
引用次数: 0
Gradient boosting for quantitative finance 定量金融的梯度增强
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2021-03-18 DOI: 10.21314/JCF.2020.403
Jesse Davis, Laurens Devos, S. Reyners, W. Schoutens
{"title":"Gradient boosting for quantitative finance","authors":"Jesse Davis, Laurens Devos, S. Reyners, W. Schoutens","doi":"10.21314/JCF.2020.403","DOIUrl":"https://doi.org/10.21314/JCF.2020.403","url":null,"abstract":"In this paper, we discuss how tree-based machine learning techniques can be used in the context of derivatives pricing. Gradient boosted regression trees are employed to learn the pricing map for a couple of classical, time-consuming problems in quantitative finance. In particular, we illustrate this methodology by reducing computation times for pricing exotic derivative products and American options. Once the gradient boosting model is trained, it is used to make fast predictions of new prices. We show that this approach leads to speed-ups of several orders of magnitude, while the loss of accuracy is very acceptable from a practical point of view. Besides the predictive performance of machine learning methods, financial regulators attach more and more importance to the interpretability of pricing models. For both applications, we therefore look under the hood of the gradient boosting model and try to reveal how the price is constructed and interpreted.","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49231821","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}
引用次数: 3
Deep learning for efficient frontier calculation in finance 深度学习在金融领域的前沿计算
IF 0.9 4区 经济学
Journal of Computational Finance Pub Date : 2021-01-06 DOI: 10.21314/jcf.2021.017
X. Warin
{"title":"Deep learning for efficient frontier calculation in finance","authors":"X. Warin","doi":"10.21314/jcf.2021.017","DOIUrl":"https://doi.org/10.21314/jcf.2021.017","url":null,"abstract":"We propose deep neural network algorithms to calculate efficient frontier in some Mean-Variance and Mean-CVaR portfolio optimization problems. We show that we are able to deal with such problems when both the dimension of the state and the dimension of the control are high. Adding some additional constraints, we compare different formulations and show that a new projected feedforward network is able to deal with some global constraints on the weights of the portfolio while outperforming classical penalization methods. All developed formulations are compared in between. Depending on the problem and its dimension, some formulations may be preferred.","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2021-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45017909","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}
引用次数: 4
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信