{"title":"Deep Hedging: Learning to Simulate Equity Option Markets","authors":"Magnus Wiese, Lianjun Bai, Ben Wood, Hans Buehler","doi":"10.2139/ssrn.3470756","DOIUrl":"https://doi.org/10.2139/ssrn.3470756","url":null,"abstract":"We construct realistic equity option market simulators based on generative adversarial networks (GANs). We consider recurrent and temporal convolutional architectures, and assess the impact of state compression. Option market simulators are highly relevant because they allow us to extend the limited real-world data sets available for the training and evaluation of option trading strategies. We show that network-based generators outperform classical methods on a range of benchmark metrics, and adversarial training achieves the best performance. Our work demonstrates for the first time that GANs can be successfully applied to the task of generating multivariate financial time series.","PeriodicalId":394523,"journal":{"name":"CompSciRN: Computing Tools (Topic)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127074251","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}
{"title":"A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data","authors":"Rishabh D Guha, Serena Ng","doi":"10.2139/ssrn.3345283","DOIUrl":"https://doi.org/10.2139/ssrn.3345283","url":null,"abstract":"This paper analyzes weekly scanner data collected for 108 groups at the county level between 2006 and 2014. The data display multi-dimensional weekly seasonal effects that are not exactly periodic but are cross-sectionally dependent. Existing univariate procedures are imperfect and yield adjusted series that continue to display strong seasonality upon aggregation. We suggest augmenting the univariate adjustments with a panel data step that pools information across counties. Machine learning tools are then used to remove the within-year seasonal variations. A demand analysis of the adjusted budget shares finds three factors: one that is trending, and two cyclical ones that are well aligned with the level and change in consumer confidence. The effects of the Great Recession vary across locations and product groups, with consumers substituting towards home cooking away from non-essential goods. The adjusted data also reveal changes in spending to unanticipated shocks at the local level. The data are thus informative about both local and aggregate economic conditions once the seasonal effects are removed. The two-step methodology can be adapted to remove other types of nuisance variations provided that these variations are cross-sectionally dependent.","PeriodicalId":394523,"journal":{"name":"CompSciRN: Computing Tools (Topic)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126005644","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}
Youcheng Lou, Moris S. Strub, Duan Li, Shouyang Wang
{"title":"Reference Point Formation in Social Networks, Wealth Growth, and Inequality","authors":"Youcheng Lou, Moris S. Strub, Duan Li, Shouyang Wang","doi":"10.2139/ssrn.3013124","DOIUrl":"https://doi.org/10.2139/ssrn.3013124","url":null,"abstract":"We investigate reference point formation in a social network of multiple investors and study its impact on wealth growth and inequality under a framework of Prospect Theory. The reference point of each individual investor contains both personal and social components. Whereas the personal component depends on the investor’s own history of wealth, the social component is determined by the wealth level of other investors in her network. In the benchmark case without social interactions and under the assumption of homogeneous preferences, each investor’s expected wealth grows at a common rate, the wealth gaps widens and the Gini coefficient remains constant. On the other hand, if the reference point is determined solely by social interactions, then, while the specific behavior depends on the model parameters, it is possible that the network simultaneously experiences high wealth growth and a reduction in inequality. Finally, for the general case where the reference point incorporates both personal and social components, we numerically show that increasing the degree of social interaction is beneficial for both increasing wealth growth and<br>reducing inequality.","PeriodicalId":394523,"journal":{"name":"CompSciRN: Computing Tools (Topic)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124290929","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}
{"title":"On Conjectures About The Simultaneous Pell Equations x2−(a2−1)y2=1 and y2−pz2=1.","authors":"Michael C. I. Nwogugu","doi":"10.2139/ssrn.3610352","DOIUrl":"https://doi.org/10.2139/ssrn.3610352","url":null,"abstract":"This article shows that the Qu (2018) conjectures, the Yang & Fu (2018) conjectures, the Jiang (2020) Conjecture-#1, the Tao (2016) Conjecture-#1, the Cipu & Mignotte (2007) Conjecture and the Cipu (2007) Conjecture [all of which pertain to the system of Simultaneous Pell equations x2−(a2−1)y2=1 and y2−pz2=1] are wrong.","PeriodicalId":394523,"journal":{"name":"CompSciRN: Computing Tools (Topic)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125461152","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}