Pub Date : 2000-03-26DOI: 10.1109/CIFER.2000.844599
P. Glasserman, P. Heidelberger, P. Shahabuddin
This paper develops methods for computationally efficient calculation of value-at-risk (VAR) in the presence of heavy-tailed risk factors. The methods model market risk factors through a multivariate t-distribution, which has both heavy tails and empirical support. Our key mathematical result is a transform analysis of a quadratic form in multivariate t random variables. Using this result, we develop two computational methods. The first uses Fourier transform inversion to develop a heavy-tailed delta-gamma approximation; this method is extremely fast, but like any delta-gamma method is only as accurate as the quadratic approximation. For greater accuracy, we therefore develop an efficient Monte Carlo method; this method uses our heavy-tailed delta-gamma approximation as a basis for variance reduction. Specifically, we use the numerical approximation to design a combination of importance sampling and stratified sampling of market scenarios that can produce enormous speed-ups compared with standard Monte Carlo.
{"title":"Value-at-risk with heavy-tailed risk factors","authors":"P. Glasserman, P. Heidelberger, P. Shahabuddin","doi":"10.1109/CIFER.2000.844599","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844599","url":null,"abstract":"This paper develops methods for computationally efficient calculation of value-at-risk (VAR) in the presence of heavy-tailed risk factors. The methods model market risk factors through a multivariate t-distribution, which has both heavy tails and empirical support. Our key mathematical result is a transform analysis of a quadratic form in multivariate t random variables. Using this result, we develop two computational methods. The first uses Fourier transform inversion to develop a heavy-tailed delta-gamma approximation; this method is extremely fast, but like any delta-gamma method is only as accurate as the quadratic approximation. For greater accuracy, we therefore develop an efficient Monte Carlo method; this method uses our heavy-tailed delta-gamma approximation as a basis for variance reduction. Specifically, we use the numerical approximation to design a combination of importance sampling and stratified sampling of market scenarios that can produce enormous speed-ups compared with standard Monte Carlo.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129689753","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844592
R. Kowalczyk, Van Bui
This paper overviews an experimental fuzzy e-negotiation agents system, FeNAs, that can support automated negotiation in the presence of imprecise information. The system uses the principles of fuzzy constraint-based reasoning involving fuzzy constraint modeling, satisfaction and propagation. It is demonstrated with a prototype for the used car-trading problem. The system supports multi-issue negotiations where offers consist of a number of issues that can include the price of the car and other value-added services such as warranty and the value of the trade-in car. The agents exchange offers on the basis of the information available and negotiation strategies used by each party. Information available to both the buyer and the seller can include the make, model, color, transmission, age and mileage of the car. Each agent has also some private information including preferences, priorities and financial constraints that are not available to other agents. This information can be imprecise where constraints, preferences and priorities are defined as fuzzy constraints describing the level of satisfaction of an agent (and its user) with different potential solutions. The overall objective of an agent is to find a solution that maximizes the agent's utility at the highest possible level of constraint satisfaction subject to its acceptability by other agents. During negotiation the agents follow a common protocol of negotiation and individual negotiation strategies.
{"title":"FeNAs: a fuzzy e-negotiation agents system","authors":"R. Kowalczyk, Van Bui","doi":"10.1109/CIFER.2000.844592","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844592","url":null,"abstract":"This paper overviews an experimental fuzzy e-negotiation agents system, FeNAs, that can support automated negotiation in the presence of imprecise information. The system uses the principles of fuzzy constraint-based reasoning involving fuzzy constraint modeling, satisfaction and propagation. It is demonstrated with a prototype for the used car-trading problem. The system supports multi-issue negotiations where offers consist of a number of issues that can include the price of the car and other value-added services such as warranty and the value of the trade-in car. The agents exchange offers on the basis of the information available and negotiation strategies used by each party. Information available to both the buyer and the seller can include the make, model, color, transmission, age and mileage of the car. Each agent has also some private information including preferences, priorities and financial constraints that are not available to other agents. This information can be imprecise where constraints, preferences and priorities are defined as fuzzy constraints describing the level of satisfaction of an agent (and its user) with different potential solutions. The overall objective of an agent is to find a solution that maximizes the agent's utility at the highest possible level of constraint satisfaction subject to its acceptability by other agents. During negotiation the agents follow a common protocol of negotiation and individual negotiation strategies.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"197 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113983983","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844625
Marcelo A. Bittencourt, F. Lin
In our global village the currency exchange rate of a country is considered by international investors as an important yardstick for measuring the health of its economy. In the paper an analysis is made of the Brazilian Real using three different methodologies: the Box-Jenkins or SARIMA; exponential smoothing; and a backpropagation neural network trained by the Levenberg-Marquardt algorithm. Not surprisingly, our study indicates that given the same input data different paradigms yield different results. However, presumably due to the intervention of the Central Bank, the time series exhibits quasiperiodic behaviour. Extrapolations are made into the future. Possible implications are discussed. Our methodology can be applied to any currency extant.
{"title":"Time series for currency exchange rate of the Brazilian Real","authors":"Marcelo A. Bittencourt, F. Lin","doi":"10.1109/CIFER.2000.844625","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844625","url":null,"abstract":"In our global village the currency exchange rate of a country is considered by international investors as an important yardstick for measuring the health of its economy. In the paper an analysis is made of the Brazilian Real using three different methodologies: the Box-Jenkins or SARIMA; exponential smoothing; and a backpropagation neural network trained by the Levenberg-Marquardt algorithm. Not surprisingly, our study indicates that given the same input data different paradigms yield different results. However, presumably due to the intervention of the Central Bank, the time series exhibits quasiperiodic behaviour. Extrapolations are made into the future. Possible implications are discussed. Our methodology can be applied to any currency extant.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130273998","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844614
V. Darley, Alexander Outkin, T. Plate, Frank Gao
We have built a model that represents a highly realistic picture of a dealer-mediated market like Nasdaq, with the flexibility to model many features of real-world markets. While we have conducted a fairly significant amount of research using the model, we have limited it to four areas: 1) investigating, mainly in a qualitative fashion, the consequences of regulatory and structural changes to the market (the most important being tick size effects); 2) investigating whether our model, at least in a stylized fashion, is able to replicate some of the observed features of real-world markets; 3) validating the model (this encompasses the previous two points); 4) designing learning agents, and investigating the behaviors they learn and their ability to perform profitably in the market. Our results are significant in two respects. First, the model is robust: the simulated market as a whole, as well as the investors and dealers that make it up, perform realistically under a wide variety of conditions. Second, the market dynamics produced by the model have the same qualitative properties as those observed in real markets. Thus the model provides a test bed in which to investigate the effects of changes in market rules and conditions, and to investigate other aspects of the Nasdaq market.
{"title":"Sixteenths or pennies? Observations from a simulation of the Nasdaq stock market","authors":"V. Darley, Alexander Outkin, T. Plate, Frank Gao","doi":"10.1109/CIFER.2000.844614","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844614","url":null,"abstract":"We have built a model that represents a highly realistic picture of a dealer-mediated market like Nasdaq, with the flexibility to model many features of real-world markets. While we have conducted a fairly significant amount of research using the model, we have limited it to four areas: 1) investigating, mainly in a qualitative fashion, the consequences of regulatory and structural changes to the market (the most important being tick size effects); 2) investigating whether our model, at least in a stylized fashion, is able to replicate some of the observed features of real-world markets; 3) validating the model (this encompasses the previous two points); 4) designing learning agents, and investigating the behaviors they learn and their ability to perform profitably in the market. Our results are significant in two respects. First, the model is robust: the simulated market as a whole, as well as the investors and dealers that make it up, perform realistically under a wide variety of conditions. Second, the market dynamics produced by the model have the same qualitative properties as those observed in real markets. Thus the model provides a test bed in which to investigate the effects of changes in market rules and conditions, and to investigate other aspects of the Nasdaq market.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127443386","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844613
Ilia Bouchouev
Despite its obvious shortcoming, Black's formula for futures options is still widely used for pricing energy derivatives. The lognormality assumption that underlies this formula is inconsistent with the market implied distribution for many commodities and as a result, out-of-the-money options are mispriced by Black's formula. Our objective is to develop a self-consistent term-structure pricing framework based on the general diffusions and derive simple pricing formulas similar to Black's one with a few additional parameters that can be easily estimated from market prices of liquid options. We assume the following risk neutral dynamics for futures prices: df(t,T)=/spl sigma//sub 1/(f,t,T)dz/sub 1/+/spl sigma//sub 2/(f,t,T)dz/sub 2/, dz/sub 1/dz/sub 2/=0. The value of the discounted European call option V(t,f) on T-maturity futures struck at K is determined as the solution to the following diffusion problem /spl part/V//spl part/t+ 1/2 (/spl sigma//sub 1//sup 2/(f,t,T)+/spl sigma//sub 2//sup 2/(f,t,T))/spl part//sup 2/V//spl part/f/sup 2/, V(T,f)=(f-K)/sup +/.
{"title":"An analytic framework for pricing energy derivatives","authors":"Ilia Bouchouev","doi":"10.1109/CIFER.2000.844613","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844613","url":null,"abstract":"Despite its obvious shortcoming, Black's formula for futures options is still widely used for pricing energy derivatives. The lognormality assumption that underlies this formula is inconsistent with the market implied distribution for many commodities and as a result, out-of-the-money options are mispriced by Black's formula. Our objective is to develop a self-consistent term-structure pricing framework based on the general diffusions and derive simple pricing formulas similar to Black's one with a few additional parameters that can be easily estimated from market prices of liquid options. We assume the following risk neutral dynamics for futures prices: df(t,T)=/spl sigma//sub 1/(f,t,T)dz/sub 1/+/spl sigma//sub 2/(f,t,T)dz/sub 2/, dz/sub 1/dz/sub 2/=0. The value of the discounted European call option V(t,f) on T-maturity futures struck at K is determined as the solution to the following diffusion problem /spl part/V//spl part/t+ 1/2 (/spl sigma//sub 1//sup 2/(f,t,T)+/spl sigma//sub 2//sup 2/(f,t,T))/spl part//sup 2/V//spl part/f/sup 2/, V(T,f)=(f-K)/sup +/.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123250604","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844593
Mingming Ma, W. S. Wijesoma
The paper proposes an automatic on-line signature verification system based on multiple models, a frequency function model, a shape-related parameter model, and a dynamics-related parameter model. This system uses fuzzy logic instead of the traditional Euclidean distance metric for comparison, and uses a personalized feature selection algorithm based on the DP function for parameter model building. From the statistical results it is concluded that fuzzy logic, the personalized feature selection algorithm based on the DP function and the multiple models method are helpful for automatic on-line signature verification.
{"title":"Automatic on-line signature verification based on multiple models","authors":"Mingming Ma, W. S. Wijesoma","doi":"10.1109/CIFER.2000.844593","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844593","url":null,"abstract":"The paper proposes an automatic on-line signature verification system based on multiple models, a frequency function model, a shape-related parameter model, and a dynamics-related parameter model. This system uses fuzzy logic instead of the traditional Euclidean distance metric for comparison, and uses a personalized feature selection algorithm based on the DP function for parameter model building. From the statistical results it is concluded that fuzzy logic, the personalized feature selection algorithm based on the DP function and the multiple models method are helpful for automatic on-line signature verification.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114259122","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844618
Sameer Singh, J. Fieldsend
In this paper, the concept of long memory systems for forecasting is developed. The pattern modelling and recognition system and fuzzy single nearest neighbour methods are introduced as local approximation tools for forecasting. Such systems are used for matching the current state of the time-series with past states to make a forecast. In the past, the PMRS system has been successfully used for forecasting the Santa Fe competition data. In this paper, we forecast the FTSE 100 and 250 financial returns indices, as well as the stock returns of five FTSE 100 companies and compare the results of the two different systems with those of exponential smoothing and random walk on seven different error measures. The results show that pattern recognition based approaches in time-series forecasting are highly accurate. Simple theoretical trading strategies are also mentioned, highlighting real applications of the system.
{"title":"Financial time series forecasts using fuzzy and long memory pattern recognition systems","authors":"Sameer Singh, J. Fieldsend","doi":"10.1109/CIFER.2000.844618","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844618","url":null,"abstract":"In this paper, the concept of long memory systems for forecasting is developed. The pattern modelling and recognition system and fuzzy single nearest neighbour methods are introduced as local approximation tools for forecasting. Such systems are used for matching the current state of the time-series with past states to make a forecast. In the past, the PMRS system has been successfully used for forecasting the Santa Fe competition data. In this paper, we forecast the FTSE 100 and 250 financial returns indices, as well as the stock returns of five FTSE 100 companies and compare the results of the two different systems with those of exponential smoothing and random walk on seven different error measures. The results show that pattern recognition based approaches in time-series forecasting are highly accurate. Simple theoretical trading strategies are also mentioned, highlighting real applications of the system.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124060714","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844597
G. A. Agasandian
Methods for the definition of preferences of portfolio investors for the multi-period investment horizon are considered and the dependence of investor behavior on the horizon length is studied. It is assumed that the capitalization share of each portfolio security doesn't vary in time. Hence, portfolio restructuring on each step of the investment process is necessary to allocate the whole portfolio value between the component securities in a proportion chosen by the investor. It is supposed that the restructuring transaction costs are equal to zero. In portfolio theory, different approaches are used. In this paper, three of them are considered. The first involves the definition of the effective portfolio set, the second involves the concept of indifference curves and the third involves drawdown criteria.
{"title":"Classes of preferences of portfolio investors for multi-period case and their asymptotic properties","authors":"G. A. Agasandian","doi":"10.1109/CIFER.2000.844597","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844597","url":null,"abstract":"Methods for the definition of preferences of portfolio investors for the multi-period investment horizon are considered and the dependence of investor behavior on the horizon length is studied. It is assumed that the capitalization share of each portfolio security doesn't vary in time. Hence, portfolio restructuring on each step of the investment process is necessary to allocate the whole portfolio value between the component securities in a proportion chosen by the investor. It is supposed that the restructuring transaction costs are equal to zero. In portfolio theory, different approaches are used. In this paper, three of them are considered. The first involves the definition of the effective portfolio set, the second involves the concept of indifference curves and the third involves drawdown criteria.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"276 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134037157","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844594
Kei-Keung Hung, C. Cheung, L. Xu
In this paper, we formulate methods for portfolio selection for investors with different attitudes in the return-risk trade-off. We defined an objective function based on the Sharpe ratio (Sharpe, 1966) and downside risk (Fishburn, 1977), plus introducing two new terms called "upside volatility" and "diversification". We propose the maximization of the objective function WRT the portfolio weights as a method of determining suitable weights. We also propose practical methods for controlling the expected return while minimizing risk, of controlling risk while maximising expected return. Experiments showed that the proposed methods yielded successful results.
{"title":"New Sharpe-ratio-related methods for portfolio selection","authors":"Kei-Keung Hung, C. Cheung, L. Xu","doi":"10.1109/CIFER.2000.844594","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844594","url":null,"abstract":"In this paper, we formulate methods for portfolio selection for investors with different attitudes in the return-risk trade-off. We defined an objective function based on the Sharpe ratio (Sharpe, 1966) and downside risk (Fishburn, 1977), plus introducing two new terms called \"upside volatility\" and \"diversification\". We propose the maximization of the objective function WRT the portfolio weights as a method of determining suitable weights. We also propose practical methods for controlling the expected return while minimizing risk, of controlling risk while maximising expected return. Experiments showed that the proposed methods yielded successful results.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132474403","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 : 2000-03-26DOI: 10.1109/CIFER.2000.844612
A. Kuruc
We present fundamental research on new notions of "vega" that, unlike the usual ones, can sensibly be added together across different valuation models. First, we describe the basic ideas using simple models of equity prices. Next, we outline the application of these ideas to interest-rate derivatives.
{"title":"Apples to oranges: reconciling \"vegas\" from inconsistent valuation models by a stochastic change of coordinates","authors":"A. Kuruc","doi":"10.1109/CIFER.2000.844612","DOIUrl":"https://doi.org/10.1109/CIFER.2000.844612","url":null,"abstract":"We present fundamental research on new notions of \"vega\" that, unlike the usual ones, can sensibly be added together across different valuation models. First, we describe the basic ideas using simple models of equity prices. Next, we outline the application of these ideas to interest-rate derivatives.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"2009 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127321389","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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