{"title":"Conditional Optimal Stopping: A Time-Inconsistent Optimization","authors":"Marcel Nutz, Yuchong Zhang","doi":"10.2139/ssrn.3409585","DOIUrl":"https://doi.org/10.2139/ssrn.3409585","url":null,"abstract":"Inspired by recent work of P.-L. Lions on conditional optimal control, we introduce a problem of optimal stopping under bounded rationality: the objective is the expected payoff at the time of stopping, conditioned on another event. For instance, an agent may care only about states where she is still alive at the time of stopping, or a company may condition on not being bankrupt. We observe that conditional optimization is time-inconsistent due to the dynamic change of the conditioning probability and develop an equilibrium approach in the spirit of R. H. Strotz' work for sophisticated agents in discrete time. Equilibria are found to be essentially unique in the case of a finite time horizon whereas an infinite horizon gives rise to non-uniqueness and other interesting phenomena. We also introduce a theory which generalizes the classical Snell envelope approach for optimal stopping by considering a pair of processes with Snell-type properties.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123357100","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 LC Model With Change-Points Regime","authors":"Vered Shapovalov, Z. Landsman, U. Makov","doi":"10.2139/ssrn.3319712","DOIUrl":"https://doi.org/10.2139/ssrn.3319712","url":null,"abstract":"This paper extends the widely used Lee Carter (LC) model (Lee & Carter, 1992) for mortality projection. We suggest a Bayesian change-points model for the time parameters in the Bayesian extension of the LC model suggested in Czado et al. (2005). In particular, we modify the simple linear trend to a piecewise linear trend. This model accounts for changes in trend over time and it is inspired by the Bayesian random level{shift model of McCulloch & Tsay (1993). In a validation-based examination, the proposed change-points model produces smaller prediction errors compared to the autoregressive model for the time parameters in Czado et al. (2005). Notably, this is true for all populations considered.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116485639","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 Theoretical Development on Market Risk with Fuzzy Logic","authors":"M. Alibeigi, Elahe Abdoos, Sahar Ataee Ashtiani","doi":"10.2139/ssrn.3313783","DOIUrl":"https://doi.org/10.2139/ssrn.3313783","url":null,"abstract":"Risk management involves planning and acting before the risk event. This is proactive rather than reactive management. The process of risk management is designed to reduce or eliminate the different risks of business.<br><br>The world is an uncertain place, therefore we need new methods which it’s calculate uncertain (or fuzzy) data in risk management.<br><br>In this study, first we define some important concepts, and we brief review of dynamic market risk charge, then we propose a new method for comparative two dynamic market risks with fuzzy distance measure. The most practical of this method with other ones that is when we have uncertain (or fuzzy) data. Finally, some numerical examples illustrate the presented method as well as comparing it with other various ones.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125430536","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":"Dependence-Robust Inference Using Resampled Statistics","authors":"Michael P. Leung","doi":"10.2139/ssrn.3036626","DOIUrl":"https://doi.org/10.2139/ssrn.3036626","url":null,"abstract":"We develop inference procedures robust to general forms of weak dependence. These involve test statistics constructed by resampling data in a manner that does not depend on the unknown correlation structure of the data. The statistics are simple to compute and asymptotically normal under the weak requirement that the target parameter can be consistently estimated at the parametric rate. This requirement holds for regular estimators under many well-known forms of weak dependence and justifies the claim of dependence-robustness. We consider applications to settings with unknown or complicated forms of dependence, with various forms network dependence as leading examples. We develop tests for both moment equalities and inequalities.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131929453","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":"Optimal Annuitisation, Housing Decisions and Means-Tested Public Pension in Retirement Under Expected Utility Stochastic Control Framework","authors":"J. Andreasson, P. Shevchenko","doi":"10.2139/ssrn.3174459","DOIUrl":"https://doi.org/10.2139/ssrn.3174459","url":null,"abstract":"In this paper, we develop a retirement model under the expected utility stochastic control framework to find optimal decisions with respect to consumption, risky asset allocation, access to annuities, reverse mortgage and the option to scale housing. The model is solved numerically using Least-Squares Monte Carlo method adapted to handle expected utility stochastic control problem in high dimensions. To demonstrate the applicability of the framework, the model is applied in the context of the Australian retirement system. Few retirees in Australia utilise financial products in retirement, such as annuities or reverse mortgages. Since the government-provided means-tested Age Pension in Australia is an indirect annuity stream which typically is higher than the average consumption floor, it is argued that this is the reason why Australians do not annuitise. In addition, in Australia where assets allocated to the family home are not included in the means tests of Age Pension, the incentive to over allocate wealth into housing assets is high. This raises the question whether a retiree is really better off over allocating into the family home, while accessing home equity later on either via downsizing housing or by taking out a reverse mortgage. Our findings confirm that means-tested pension crowds out voluntary annuitisation in retirement, and that annuitisation is optimal sooner rather than later once retired. We find that it is never optimal to downscale housing with the means-tested Age Pension when a reverse mortgage is available, only when there is no other way to access equity then downsizing is the only option.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131806530","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 Non-Bayesian Theory of State-Dependent Utility","authors":"Brian Hill","doi":"10.2139/ssrn.3177028","DOIUrl":"https://doi.org/10.2139/ssrn.3177028","url":null,"abstract":"Many decision situations involve two or more of the following divergences from subjective expected utility: imprecision of beliefs (or ambiguity), imprecision of tastes (or multi‐utility), and state dependence of utility. This paper proposes and characterizes a model of uncertainty averse preferences that can simultaneously incorporate all three phenomena. The representation supports a principled separation of (imprecise) beliefs and (potentially state‐dependent, imprecise) tastes. Moreover, the representation permits comparative statics separating the roles of beliefs and tastes, and is modular: it easily delivers special cases involving various combinations of the phenomena, as well as state‐dependent multi‐utility generalizations covering popular ambiguity models.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133469182","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":"Feature Selection With Optimal Coordinate Ascent (OCA)","authors":"D. Saltiel, E. Benhamou","doi":"10.2139/ssrn.3293503","DOIUrl":"https://doi.org/10.2139/ssrn.3293503","url":null,"abstract":"In machine learning, Feature Selection (FS) is a major part of efficient algorithm. It fuels the algorithm and is the starting block for our prediction. In this paper, we present a new method, called Optimal Coordinate Ascent (OCA) that allows us selecting features among block and individual features. OCA relies on coordinate ascent to find an optimal solution for gradient boosting methods score (number of correctly classified samples). OCA takes into account the notion of dependencies between variables forming blocks in our optimization. The coordinate ascent optimization solves the issue of the NP hard original problem where the number of combinations rapidly explode making a grid search unfeasible. It reduces considerably the number of iterations changing this NP hard problem into a polynomial search one. OCA brings substantial differences and improvements compared to previous coordinate ascent feature selection method: we group variables into block and individual variables instead of a binary selection. Our initial guess is based on the k-best group variables making our initial point more robust. We also introduced new stopping criteria making our optimization faster. We compare these two methods on our data set. We found that our method outperforms the initial one. We also compare our method to the Recursive Feature Elimination (RFE) method and find that OCA leads to the minimum feature set with the highest score. This is a nice byproduct of our method as it provides empirically the most compact data set with optimal performance.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126662566","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 Generalization of Stochastic Calculus--A Conjecture","authors":"David E. Harris","doi":"10.2139/ssrn.3197451","DOIUrl":"https://doi.org/10.2139/ssrn.3197451","url":null,"abstract":"Existing models of calculus in finance, such as Ito calculus have an underlying assumption that the parameters are known. This paper relaxes that assumption. The paper proposes the creation of differentiable paths that do not require an expectation to exist. Further, the path minimizes the expected loss from using a predictive calculus and, under mild conditions, stochastically dominates any other path. Further, the path is assured to produce fair gambling odds if used in finance. This method maps to Ito and Stratonovich methods if the parameters are known and dominate them if they are not in the general case.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124979699","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":"European Rainbow Option Values under the Two-Asset Merton Jump-Diffusion Model","authors":"Lynn Boen","doi":"10.2139/ssrn.3290656","DOIUrl":"https://doi.org/10.2139/ssrn.3290656","url":null,"abstract":"Abstract In this paper we present a semi-closed analytical formula for the values of European call and put options on the minimum or maximum of two assets under the two-asset Merton jump-diffusion model. In addition, useful formulas for several first- and second-order Greeks of these options are derived.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"R-36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126542813","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":"Auctions with Entry versus Entry in Auctions","authors":"Jiafeng Chen, S. Kominers","doi":"10.2139/ssrn.3281615","DOIUrl":"https://doi.org/10.2139/ssrn.3281615","url":null,"abstract":"We show that charging entry fees can sometimes dominate the benefit of recruiting additional bidders to auctions, even though the fees themselves implicitly reduce competition at the auction stage. We also highlight that admission fees and reserve prices are different instruments in a setting with uncertainty over entry costs, and that optimal mechanisms in such settings may be higher-dimensional than in Myerson (1981). Our results provide a counterpoint to the broad intuition of Bulow and Klemperer (1996) that market thickness often takes precedence over market power in auction design.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116330559","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}
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
