{"title":"A moment based analysis of hedging under discrete trading","authors":"J. Primbs, Yuji Yamada","doi":"10.1109/CIFER.2003.1196244","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196244","url":null,"abstract":"This paper analyzes the performance of two hedging strategies on three different options when trading is limited to take place at discrete times. Specifically, we compare the mean, standard deviation, skewness, and kurtosis of the hedging error resulting from applying a delta hedge and mean square optimal hedge to a European call option, a digital call option, and a down-and-out barrier call option. The results indicate that the two hedges perform equally well on the European call option and digital option, but the mean square optimal hedge is superior when hedging the barrier option.","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":"115994738","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":"Application of neural control to economic growth problems","authors":"A. Alessandri, C. Cervellera, F. Grassia","doi":"10.1109/CIFER.2003.1196255","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196255","url":null,"abstract":"The evolution of the freight transportation market is a complex phenomenon that can be described by means of suitable dynamic models. This model depends on a set of control variables (i.e., the percentage of carbon tax on the fuel cost, the operational cost coverages, and growth rates of the various transportation modes, such as railway, roadway, and waterway) that can be chosen in such a way as to minimize a given cost function (e.g., carbon emissions, public and private costs, fuel consumption, etc.). The problem has been addressed by searching for a feedback control law that can be approximated by means of the combination of both dynamic programming and neural networks. Simulation results with the afore-mentioned model are presented to demonstrate the effectiveness of the proposed method.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"8 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":"115385346","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":"Nonlinear phillips curves in the Euro area and USA? Evidence from linear and neural network models","authors":"P. McNelis","doi":"10.1109/CIFER.2003.1196254","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196254","url":null,"abstract":"The paper applies neural network methodology to inflation forecasting in the Euro-area and the USA. Neural network methodology outperforms linear forecasting methods for the Euro Area at forecast horizons of one, three, and six month horizons, while the linear model is preferable for US data. The nonlinear estimation shows that unemployment is a significant predictor of inflation for the Euro Area. Neither model detects a significant effect of unemployment on inflation for the US data.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"45 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":"116638933","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 process control approach to investment risk","authors":"L. MacLean, Yonggan Zhao, W. Ziemba","doi":"10.1109/CIFER.2003.1196270","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196270","url":null,"abstract":"The problem of misdirected investment strategies based on erroneous forecasts is the motivation for a Process Control (PC) approach to volatility and risk. Upper and lower limits on the capital accumulation process are used to determine if the current investment strategy continues. If a limit is reached then rebalancing occurs, where returns are re-estimated, new limits are established and a new strategy is determined. This variable planning horizon approach is compared to the standard Value-at-Risk (VaR) methodology, where the time horizon is fixed. In an application to asset allocation involving stocks, bonds and cash, it is shown that for any VaR strategy there exists process control limits so that the corresponding PC strategy has greater expected return with equivalent downside risk. The advantage in the process control approach comes from intervening when the wealth process deviates significantly from expectations.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"18 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":"114140449","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":"Stock prediction: Integrating text mining approach using real-time news","authors":"G. Fung, J. Yu, Wai Lam","doi":"10.1109/CIFER.2003.1196287","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196287","url":null,"abstract":"Mining textual documents and time series concurrently, such as predicting the movements of stock prices based on news articles, is an emerging topic in data mining society nowadays. Previous research has already suggested that the relationship between news articles and stock prices do exist. However, all of the existing approaches are concerning in mining single time series only. The interrelationships among different stocks are not well-addressed. Mining multiple time series concurrently is not only more informative but also far more challenging. Research in such a direction is lacking. In this paper, we try to explore such an opportunity and propose a systematic framework for mining multiple time series based on Efficient Market Hypothesis.","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":"129009041","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":"The valuation of a Euro-Convertible Bond","authors":"Chung-Gee Lin, Chuang-Chang Chang, Min-Teh Yu","doi":"10.1109/CIFER.2003.1196250","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196250","url":null,"abstract":"A Euro-Convertible Bond (ECB) is a hybrid security with the properties of both stock and bond. Further, since there are two currencies involved in this hybrid security, in addition to the conversion option, there is also a currency option embedded. We employed Least Square Monte Carlo simulation (LSM) approach developed by Longstaff and Schwartz (2001) to value ECB. The value of conversion option and currency option embedded in ECB were extracted from the differences between values of pure corporate bond, convertible bond (CB), and ECB. We also investigate the effects of exchange rate volatility, stock price volatility and correlations of state variables to the value of ECB.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"126 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":"124528711","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":"Data-analytic approaches to the estimation of Value-at-Risk","authors":"Jianqing Fan, Juan Gu","doi":"10.1109/CIFER.2003.1196271","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196271","url":null,"abstract":"Value-at-risk measures the worst loss to be expected of a portfolio over a given time horizon at a given confidence level. Calculation of VaR frequently involves estimating the volatility of return processes and quantiles of standardized returns. In this paper, several semiparametric techniques are introduced to estimate the volatilities. In addition, both parametric and nonparametric techniques are proposed to estimate the quantiles of standardized return processes. The newly proposed techniques also have the flexibility to adapt automatically to the changes in the dynamics of market prices over time. The combination of newly proposed techniques for estimating volatility and standardized quantiles yields several new techniques for evaluating multiple period VaR. The performance of the newly proposed VaR estimators is evaluated and compared with some of existing methods. Our simulation results and empirical studies endorse the newly proposed time-dependent semiparametric approach for estimating VaR.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"24 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":"124051050","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":"Statistical properties of African FX rates: An application of the Stable Paretian Hypothesis","authors":"David Basterfield, Thomas Bundt, Grattan Murphy","doi":"10.1109/CIFER.2003.1196264","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196264","url":null,"abstract":"This paper fits Stable Paretian distributions to daily returns data for 41 continental African currencies. Data analysis shows that the returns from all currencies are non-normally distributed and can befitted as non-normal members of the class of stable distributions. This implies that returns for all currencies have infinite variance. In addition, several currencies have characteristic exponents less than unity, implying that no moments exist for these currencies. The implications for mean-variance portfolio management and risk management are also discussed.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"31 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":"128239991","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":"Fast Monte Carlo valuation of barrier options for jump diffusion processes","authors":"S. Metwally, A. Atiya","doi":"10.1109/CIFER.2003.1196248","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196248","url":null,"abstract":"We present a fast and unbiased Monte Carlo approach to pricing barrier options when the underlying security follows a simple jump diffusion process with constant parameters and a continuously monitored barrier. We develop an algorithm that is based on the Brownian bridge concept and on a sampling approach to successively evaluate an integral that results from the application of the Brownian bridge. This method achieves zero bias. In addition, it is about 100 times faster than the conventional Monte Carlo method for which the discretization interval is chosen so as to achieve acceptable bias.","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":"123663792","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":"Does anything beat a GARCH(1,1)? A comparison based on test for superior predictive ability","authors":"P. Hansen, Asger Lunde","doi":"10.1109/CIFER.2003.1196275","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196275","url":null,"abstract":"We compare 330 GARCH-type models in terms of their ability to predict the conditional variance using out-of-sample data. Our question of interest is whether more sophisticated volatility models are able to outperform the simple GARCH(1,1) model. This question is addressed using the test for superior predictive ability (SPA) by [18]. A salient property of this test is that it takes the performance of all models into account simultaneously, thereby avoiding crude approximations and the distortion that arises from pair-wise comparisons. The evaluation is based on daily realized volatility of IBM equity return data and find that the GARCH(1,1) is significantly outperformed by other models, mainly those that accommodate a leverage effect.","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":"117202472","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}