Pub Date : 2024-01-13DOI: 10.1007/s10287-023-00469-9
K. Yagi, R. Sioshansi
{"title":"Nested Benders’s decomposition of capacity-planning problems for electricity systems with hydroelectric and renewable generation","authors":"K. Yagi, R. Sioshansi","doi":"10.1007/s10287-023-00469-9","DOIUrl":"https://doi.org/10.1007/s10287-023-00469-9","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"32 7","pages":"1-31"},"PeriodicalIF":0.9,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-21DOI: 10.1007/s10287-023-00495-7
Fuad Aleskerov, O. Khutorskaya, Viacheslav Yakuba, Anna Stepochkina, Ksenia Zinovyeva
{"title":"Affiliations based bibliometric analysis of publications on parkinson’s disease","authors":"Fuad Aleskerov, O. Khutorskaya, Viacheslav Yakuba, Anna Stepochkina, Ksenia Zinovyeva","doi":"10.1007/s10287-023-00495-7","DOIUrl":"https://doi.org/10.1007/s10287-023-00495-7","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"139 34","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138953332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-08DOI: 10.1007/s10287-023-00491-x
E. Di Lorenzo, G. Piscopo, M. Sibillo
{"title":"Addressing the economic and demographic complexity via a neural network approach: risk measures for reverse mortgages","authors":"E. Di Lorenzo, G. Piscopo, M. Sibillo","doi":"10.1007/s10287-023-00491-x","DOIUrl":"https://doi.org/10.1007/s10287-023-00491-x","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"31 38","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138589139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-17DOI: 10.1007/s10287-023-00488-6
C. C. Chu, Simon S. W. Li
{"title":"A multiobjective optimization approach for threshold determination in extreme value analysis for financial time series","authors":"C. C. Chu, Simon S. W. Li","doi":"10.1007/s10287-023-00488-6","DOIUrl":"https://doi.org/10.1007/s10287-023-00488-6","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"51 2","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139264012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract We study large-scale portfolio optimization problems in which the aim is to maximize a multi-moment performance measure extending the Sharpe ratio. More specifically, we consider the adjusted for skewness Sharpe ratio, which incorporates the third moment of the returns distribution, and the adjusted for skewness and kurtosis Sharpe ratio, which exploits in addition the fourth moment. Further, we account for two types of real-world trading constraints. On the one hand, we impose stock market restrictions through cardinality, buy-in thresholds, and budget constraints. On the other hand, a turnover threshold restricts the total allowed amount of trades in the rebalancing phases. To deal with these asset allocation models, we embed a novel hybrid constraint-handling procedure into an improved dynamic level-based learning swarm optimizer. A repair operator maps candidate solutions onto the set characterized by the first type of constraints. Then, an adaptive $$ell _1$$ ℓ1 -exact penalty function manages turnover violations. The focus of the paper is to highlight the importance of including higher-order moments in the performance measures for long-run investments, in particular when the market is turbulent. We carry out empirical tests on two worldwide sets of assets to illustrate the scalability and effectiveness of the proposed strategies, and to evaluate the performance of our investments compared to the strategy maximizing the Sharpe ratio.
{"title":"A constrained swarm optimization algorithm for large-scale long-run investments using Sharpe ratio-based performance measures","authors":"Massimiliano Kaucic, Filippo Piccotto, Gabriele Sbaiz","doi":"10.1007/s10287-023-00483-x","DOIUrl":"https://doi.org/10.1007/s10287-023-00483-x","url":null,"abstract":"Abstract We study large-scale portfolio optimization problems in which the aim is to maximize a multi-moment performance measure extending the Sharpe ratio. More specifically, we consider the adjusted for skewness Sharpe ratio, which incorporates the third moment of the returns distribution, and the adjusted for skewness and kurtosis Sharpe ratio, which exploits in addition the fourth moment. Further, we account for two types of real-world trading constraints. On the one hand, we impose stock market restrictions through cardinality, buy-in thresholds, and budget constraints. On the other hand, a turnover threshold restricts the total allowed amount of trades in the rebalancing phases. To deal with these asset allocation models, we embed a novel hybrid constraint-handling procedure into an improved dynamic level-based learning swarm optimizer. A repair operator maps candidate solutions onto the set characterized by the first type of constraints. Then, an adaptive $$ell _1$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:msub> <mml:mi>ℓ</mml:mi> <mml:mn>1</mml:mn> </mml:msub> </mml:math> -exact penalty function manages turnover violations. The focus of the paper is to highlight the importance of including higher-order moments in the performance measures for long-run investments, in particular when the market is turbulent. We carry out empirical tests on two worldwide sets of assets to illustrate the scalability and effectiveness of the proposed strategies, and to evaluate the performance of our investments compared to the strategy maximizing the Sharpe ratio.","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"8 32","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-06DOI: 10.1007/s10287-023-00485-9
Dmitry Metelev, Alexander Rogozin, Alexander Gasnikov, Dmitry Kovalev
{"title":"Decentralized saddle-point problems with different constants of strong convexity and strong concavity","authors":"Dmitry Metelev, Alexander Rogozin, Alexander Gasnikov, Dmitry Kovalev","doi":"10.1007/s10287-023-00485-9","DOIUrl":"https://doi.org/10.1007/s10287-023-00485-9","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135635452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.1007/s10287-023-00486-8
Youssef El-Khatib, Zororo S. Makumbe, Josep Vives
Abstract Under a two-factor stochastic volatility jump (2FSVJ) model we obtain an exact decomposition formula for a plain vanilla option price and a second-order approximation of this formula, using Itô calculus techniques. The 2FSVJ model is a generalization of several models described in the literature such as Heston (Rev Financ Stud 6(2):327–343, 1993); Bates (Rev Financ Stud 9(1):69–107, 1996); Kou (Manag Sci 48(8):1086–1101, 2002); Christoffersen et al. (Manag Sci 55(12):1914–1932, 2009) models. Thus, the aim of this study is to extend some approximate pricing formulas described in the literature, like formulas in Alòs (Finance Stoch 16(3):403–422, 2012); Merino et al. (Int J Theor Appl Finance 21(08):1850052, 2018); Gulisashvili et al. (J Comput Finance 24(1), 2020), to pricing under the more general 2FSVJ model. Moreover, we provide numerical illustrations of our pricing method and its accuracy and computational advantage under double exponential and log-normal jumps. Numerically, our pricing method performs very well compared to the Fourier integral method. The performance is ideal for out-of-the-money options as well as for short maturities.
摘要在双因素随机波动跳变(2FSVJ)模型下，利用Itô微积分技术，得到了普通期权价格的精确分解公式和该公式的二阶近似。2FSVJ模型是文献中描述的几个模型的概括，如Heston (Rev finance Stud 6(2): 327-343, 1993);贝茨(Rev finance Stud 9(1): 69-107, 1996);管理科学48(8):1086-1101,2002);Christoffersen et al.(管理科学55(12):1914-1932,2009)模型。因此，本研究的目的是扩展文献中描述的一些近似定价公式，如Alòs中的公式(Finance Stoch 16(3): 403-422, 2012);Merino et al.(国际理论与应用金融杂志21(08):1850052,2018);Gulisashvili et al. (J computer Finance 24(1)， 2020)，在更通用的2FSVJ模型下定价。此外，我们还提供了数值实例说明我们的定价方法及其在双指数和对数正态跳跃下的准确性和计算优势。在数值上，与傅里叶积分法相比，我们的定价方法表现得非常好。这种表现对于现金外期权和短期期权都是理想的。
{"title":"Approximate option pricing under a two-factor Heston–Kou stochastic volatility model","authors":"Youssef El-Khatib, Zororo S. Makumbe, Josep Vives","doi":"10.1007/s10287-023-00486-8","DOIUrl":"https://doi.org/10.1007/s10287-023-00486-8","url":null,"abstract":"Abstract Under a two-factor stochastic volatility jump (2FSVJ) model we obtain an exact decomposition formula for a plain vanilla option price and a second-order approximation of this formula, using Itô calculus techniques. The 2FSVJ model is a generalization of several models described in the literature such as Heston (Rev Financ Stud 6(2):327–343, 1993); Bates (Rev Financ Stud 9(1):69–107, 1996); Kou (Manag Sci 48(8):1086–1101, 2002); Christoffersen et al. (Manag Sci 55(12):1914–1932, 2009) models. Thus, the aim of this study is to extend some approximate pricing formulas described in the literature, like formulas in Alòs (Finance Stoch 16(3):403–422, 2012); Merino et al. (Int J Theor Appl Finance 21(08):1850052, 2018); Gulisashvili et al. (J Comput Finance 24(1), 2020), to pricing under the more general 2FSVJ model. Moreover, we provide numerical illustrations of our pricing method and its accuracy and computational advantage under double exponential and log-normal jumps. Numerically, our pricing method performs very well compared to the Fourier integral method. The performance is ideal for out-of-the-money options as well as for short maturities.","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"44 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135819590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.1007/s10287-023-00487-7
Gianfranco Liberona, David Salas, Léonard von Niederhäusern
{"title":"The Value of Shared Information for allocation of drivers in ride-hailing: a proof-of-concept study","authors":"Gianfranco Liberona, David Salas, Léonard von Niederhäusern","doi":"10.1007/s10287-023-00487-7","DOIUrl":"https://doi.org/10.1007/s10287-023-00487-7","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"29 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135873850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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