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2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.最新文献

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Pricing S&P 500 index options with Heston's model 用赫斯顿模型为标准普尔500指数期权定价
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196246
Jin E. Zhang, Jinghong Shu
{"title":"Pricing S&P 500 index options with Heston's model","authors":"Jin E. Zhang, Jinghong Shu","doi":"10.1109/CIFER.2003.1196246","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196246","url":null,"abstract":"This paper studies the price of S&P 500 index options by using Heston's (1993) stochastic volatility option pricing model. The Heston model is calibrated by a two-step estimation procedure to incorporate both the information from time-series asset return and the information from cross-sectional option data. We find that both the Black-Scholes model and the Heston model overprice the out-of-the-money option and under price the in-the-money options, but the degree of the bias is different. The Heston model significantly outperforms the Black-Scholes model in almost all moneyness-maturity group. On average, the Heston model can reduce pricing errors by about 25%. However, pricing bias still exists in the Heston model, In particular, the Heston model always overprices short-term options, indicating that some other factors, such as the random jump, may also be needed to explain the option price.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115082773","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}
引用次数: 31
Mean-variance optimization and pair-wise strategies 均方差优化和配对策略
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196268
E. Qian
{"title":"Mean-variance optimization and pair-wise strategies","authors":"E. Qian","doi":"10.1109/CIFER.2003.1196268","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196268","url":null,"abstract":"This paper analyzes quantitative active strategies based on forecasting models and mean-variance optimization. The central concept in our analysis is pairwise strategy. We demonstrate that the correct metric for assessing forecast quality is pair-wise information coefficient. We prove that a general active strategy using mean-variance optimization is equivalent to a linear combination of pair-wise strategies and the relative weights of the pairs in this combination are directly connected to the covariance matrix used in the optimization. In addition, we derive the expected long-term performance of an active quantitative strategy and optimal choice of pair-wise combination that attains maximum information ratio.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129484109","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}
引用次数: 1
Co-evolutionary multi-agent-based modeling of artificial stock market by using the GP approach 基于GP方法的协同进化多主体人工股票市场建模
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196256
Xiaorong Chen
{"title":"Co-evolutionary multi-agent-based modeling of artificial stock market by using the GP approach","authors":"Xiaorong Chen","doi":"10.1109/CIFER.2003.1196256","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196256","url":null,"abstract":"The paper deals with a multi-agent-based architecture for an artificial stock market. We attempt to add more heterogeneity to agents. Specifically, in this architecture rational agents prefer forecast equation models or simple trading rules to support their decision making, and own their own individual base or just learn from a public base. Besides these rational agents, a type of irrational agent is also defined. We focus on applying the GP approach to model cognitive behavior of adaptive agents. Time series generated from this multi-agent-based artificial stock market are demonstrated to replicate some features and compared with empirical studies.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130796107","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}
引用次数: 4
Inflation forecasting - a comparison between econometric methods and a computational approach based on genetic-neural fuzzy rule-bases 通货膨胀预测-计量经济学方法和基于遗传神经模糊规则基础的计算方法的比较
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196259
Stefan Kooths, T. Mitze, Eric Ringhut
{"title":"Inflation forecasting - a comparison between econometric methods and a computational approach based on genetic-neural fuzzy rule-bases","authors":"Stefan Kooths, T. Mitze, Eric Ringhut","doi":"10.1109/CIFER.2003.1196259","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196259","url":null,"abstract":"The paper seeks to determine whether the predictive power of linear econometric models outperforms models based on artificial intelligence methods (computational methods) concerning forecasting inflation. Various models of both types are constructed and compared according to a battery of test statistics. We find some superiority of the computational approach.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132647397","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}
引用次数: 5
Simple decision making criterion as real options 作为实物期权的简单决策标准
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196236
H. Suto, James Alleman, Paul N. Rappoport
{"title":"Simple decision making criterion as real options","authors":"H. Suto, James Alleman, Paul N. Rappoport","doi":"10.1109/CIFER.2003.1196236","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196236","url":null,"abstract":"The purpose of this paper is providing a simple decision making criterion under uncertainty for the managers who are not so familiar with statistics. We introduce a new decision-making index d, which is the expectation of NPV normalized by its standard deviation. We show the break-even point, d = D* = 0.276 occurs when NPV is equal to ROV (real option value). Using D*, we can make more sophisticated decisions considering opportunity loss and cost of uncertainty. This criterion is useful when NPV lies near zero or uncertainty is large. We provide an example that shows the reasonableness of using this decision criterion.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114207289","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}
引用次数: 2
Genetic learning as an explanation of stylized facts of foreign exchange markets 遗传学习作为对外汇市场风格化事实的解释
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196262
T. Lux, Sascha Schornstein
{"title":"Genetic learning as an explanation of stylized facts of foreign exchange markets","authors":"T. Lux, Sascha Schornstein","doi":"10.1109/CIFER.2003.1196262","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196262","url":null,"abstract":"This paper revisits the Kareken-Wallace model of exchange rate formation. Following the seminal paper by Arifovic (1996) we investigate a dynamic version of the model in which agents' decision rules are updated using genetic algorithms. Time series analysis of simulated data indicates that for particular parameterizations, the characteristics of the exchange rate dynamics are very similar to those of empirical data. The similarity appears to be quite insensitive with respect to the ingredients of the GA algorithm. However, appearance or not of realistic time series characteristics depends crucially on the mutation probability (which should be low) and the number of agents (not more than about 1000).","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123197774","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}
引用次数: 104
Self-organizing maps as a foundation for charting or geometric pattern recognition in financial time series 自组织地图作为金融时间序列中制图或几何模式识别的基础
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196286
Chueh-Yung Tsao, Shu-Heng Chen
{"title":"Self-organizing maps as a foundation for charting or geometric pattern recognition in financial time series","authors":"Chueh-Yung Tsao, Shu-Heng Chen","doi":"10.1109/CIFER.2003.1196286","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196286","url":null,"abstract":"For a long time technical analysts have detected trading signals with charts. Nonetheless, from a scientific viewpoint, charts are somewhat subjective objects. Using Kohonen's self-organizing maps (SOMs), the research presented proposes a systematic and automatic approach to charting, or more generally stated, geometric pattern recognition. It is found that the charts discovered using SOM in empirical time series do transmit useful information, and that it is hard for such information to be captured by ordinary econometric methods.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128687746","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}
引用次数: 6
Attrition and preemption in credit/debit cards incentives: models and experiments 信用卡/借记卡激励中的损耗和抢占:模型和实验
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196258
Edward Jimenez
{"title":"Attrition and preemption in credit/debit cards incentives: models and experiments","authors":"Edward Jimenez","doi":"10.1109/CIFER.2003.1196258","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196258","url":null,"abstract":"Incentives might guide marketing actions according to bank politics and Basel Core Principles which include partner's behavior. These patterns may optimize a utility function, represent simple preferences, or may be irrational. An incitement to cooperate \"using a credit/debit card product frequently\", produces a surplus to be distributed between diners club international (Principal), partners (agents) and merchants (establishments). The author uses the bimatrix chicken game as a paradigm of incitement to cooperate. The net current value represents the utility function. The author determines the microeconomic characteristics of the partner's behavior which include: risk aversion or risk loving. The individual preferences related to risk will allow us to make decisions based on when, how and to whom the incentives are given.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133969063","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}
引用次数: 0
c-ascending support vector machines for financial time series forecasting 金融时间序列预测的c-升序支持向量机
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196277
Lijuan Cao, K. Chua, Lim Kian Guan
{"title":"c-ascending support vector machines for financial time series forecasting","authors":"Lijuan Cao, K. Chua, Lim Kian Guan","doi":"10.1109/CIFER.2003.1196277","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196277","url":null,"abstract":"This paper proposes a modified version of support vector machines (SVMs), called c-ascending support vector machines (c-ASVMs), to model non-stationary financial time series. c-ASVMS are obtained by a simple modification of the regularized risk function in SVMs whereby the recent /spl epsiv/-insensitive errors are penalized more heavily than the distant /spl epsiv/-insensitive errors. This procedure is based on the prior knowledge that in the non-stationary financial time series, the recent past data could provide more important information than the distant past data. In the experiment, c-ASVMS are tested using three real futures collected from the Chicago Mercantile Market. It is shown that the c-ASVMS with the actually ordered sample data consistently forecast better than the standard SVMs, with the worst performance when the reversely ordered sample data are used. Furthermore, the c-ASVMs use fewer support vectors than those of the standard SVMs, resulting in a sparser representation of solution.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131947567","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}
引用次数: 15
Hedging a portfolio of derivatives by modeling cost 通过建模成本对衍生品投资组合进行对冲
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196243
Katharyn A. Boyle, T. Coleman, Yuying Li
{"title":"Hedging a portfolio of derivatives by modeling cost","authors":"Katharyn A. Boyle, T. Coleman, Yuying Li","doi":"10.1109/CIFER.2003.1196243","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196243","url":null,"abstract":"We consider the problem of hedging the loss of a given portfolio of derivatives using a set of more liquid derivative instruments. We illustrate why the typical mathematical formulation for this hedging problem is ill-posed. We propose to determine a hedging portfolio by minimizing a proportional cost subject to an upper bound on the hedge risk; this bound is typically slightly larger than the optimal hedge risk achievable without cost consideration. We illustrate that the optimal hedging portfolio obtained by the proposed method is attractive since it consists of fewer instruments with a comparable risk. Finally we illustrate the importance of modeling volatility uncertainty in hedge risk minimization.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132001949","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}
引用次数: 3
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