Traders behavior can influence the evolution of thestock price movement due to their ability to use the information of some internal and external factors to place an order on the market. The goal of this paper is to create an expert system that simulates the behavior and the reaction of informed and noise traders in order to better understand the effect of the traders and how we can minimize the effect of noise traders on the market.We proposed an expert system that uses rule based techniques in order to describe the behavior of informed and noise traders to any kind of news, historical data and the external information.The system makes a correlation between the traders behavioron a given moment and the information that is known at thatparticular moment. It also describes the type of traders and how they usually act on the market. It is important to know that a trader can learn on the market and can change their status and their behavior. We developed a prototype in order to simulate the movement and evolution of traders behavior on the market and also to classify and quantify the effect of traders behavior on the stock price movement.
{"title":"Traders' Behavior Effect on Stock Price Evolution","authors":"M. Tirea","doi":"10.1109/SYNASC.2013.43","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.43","url":null,"abstract":"Traders behavior can influence the evolution of thestock price movement due to their ability to use the information of some internal and external factors to place an order on the market. The goal of this paper is to create an expert system that simulates the behavior and the reaction of informed and noise traders in order to better understand the effect of the traders and how we can minimize the effect of noise traders on the market.We proposed an expert system that uses rule based techniques in order to describe the behavior of informed and noise traders to any kind of news, historical data and the external information.The system makes a correlation between the traders behavioron a given moment and the information that is known at thatparticular moment. It also describes the type of traders and how they usually act on the market. It is important to know that a trader can learn on the market and can change their status and their behavior. We developed a prototype in order to simulate the movement and evolution of traders behavior on the market and also to classify and quantify the effect of traders behavior on the stock price movement.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134214435","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}
We present a robust EPTAS for scheduling on identical machines. The running time for adding one job is bounded by 2O((1/ε2) log3(1/ε)). The migration factor required to gain a (1+ ε)-approximate schedule in each iteration is bounded by 2O((1/ε) log2(1/ε)).
{"title":"Online-Scheduling on Identical Machines with Bounded Migration","authors":"Thorsten Ehlers, K. Jansen","doi":"10.1109/SYNASC.2013.54","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.54","url":null,"abstract":"We present a robust EPTAS for scheduling on identical machines. The running time for adding one job is bounded by 2<sup>O((1/ε2)</sup> log<sup>3(1/ε))</sup>. The migration factor required to gain a (1+ ε)-approximate schedule in each iteration is bounded by 2<sup>O((1/ε) log2(1/ε))</sup>.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132388127","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}
The goal of this paper is to develop a system able to coordinate a trader in optimizing a stock market portfolio in order to improve the profitability of a short or medium time period investment. The system is able to classify the risk and quantifies its effect on an investment based on sentiment analysis, certain characteristics, the traders confidence level, and by measuring the potential loss over a certain period of time. The system id also able to create certain types of portfolios based on different methods of computing the investment risk and on the associated level of confidence. We proposed a multi-agent system that uses sentiment analysis, volatility, Monte Carlo simulation, trust models and risk models/limits in order to choose the appropriate mix of investments in order to minimize the risk and maximize the gain on a stock portfolio taking in consideration also the traders possibilities to enter in an investment. A prototype was developed on which we validated our research.
{"title":"Managing Risk Behavior on an Evolutionary Market -- A Risk Limits and Value-at-Risk Measures Approach","authors":"M. Tirea, V. Negru","doi":"10.1109/SYNASC.2013.77","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.77","url":null,"abstract":"The goal of this paper is to develop a system able to coordinate a trader in optimizing a stock market portfolio in order to improve the profitability of a short or medium time period investment. The system is able to classify the risk and quantifies its effect on an investment based on sentiment analysis, certain characteristics, the traders confidence level, and by measuring the potential loss over a certain period of time. The system id also able to create certain types of portfolios based on different methods of computing the investment risk and on the associated level of confidence. We proposed a multi-agent system that uses sentiment analysis, volatility, Monte Carlo simulation, trust models and risk models/limits in order to choose the appropriate mix of investments in order to minimize the risk and maximize the gain on a stock portfolio taking in consideration also the traders possibilities to enter in an investment. A prototype was developed on which we validated our research.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"263 1‐5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132442457","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}
This paper presents a significantly improved version to a recently introduced hyperplane classifier, Probabilistic Vector Machine (PVM). The main goal is to provide a formulation which allows fast and robust resolution of the classification problem as approached by the PVM algorithm. The main result is the introduction of a single linear program (LP) form which avoids the iterative process initially introduced by PVM. This allows comparison to state of the art algorithms such as Least Squares Twin Support Vector Machines(LSTSVM) and Robust Twin Support Vector Machines (R-TSVM). The results prove that PVM is both highly competitive and stable.
{"title":"Resolution of the Probabilistic Vector Machine Problem via Single Linear Program","authors":"Mihai Cimpoesu, Andrei Sucila, H. Luchian","doi":"10.1109/SYNASC.2013.78","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.78","url":null,"abstract":"This paper presents a significantly improved version to a recently introduced hyperplane classifier, Probabilistic Vector Machine (PVM). The main goal is to provide a formulation which allows fast and robust resolution of the classification problem as approached by the PVM algorithm. The main result is the introduction of a single linear program (LP) form which avoids the iterative process initially introduced by PVM. This allows comparison to state of the art algorithms such as Least Squares Twin Support Vector Machines(LSTSVM) and Robust Twin Support Vector Machines (R-TSVM). The results prove that PVM is both highly competitive and stable.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130273278","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}
Very large sparse matrices are often processed on massively parallel computer systems with distributed memory architectures consisting of tens or hundreds of thousands of processor cores. The problem occurs when we want or need to load/store these matrices from/to a distributed file system. This paper deals with the design of new formats for storing very large sparse matrices suitable for parallel I/O systems. The first one is based on arithmetic coding and the second one is based on binary tree format. We compare the space complexity of common storage formats and our new formats and prove that the latter are considerably more space efficient.
{"title":"Space Efficient Formats for Structure of Sparse Matrices Based on Tree Structures","authors":"I. Šimeček, D. Langr, P. Tvrdík","doi":"10.1109/SYNASC.2013.52","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.52","url":null,"abstract":"Very large sparse matrices are often processed on massively parallel computer systems with distributed memory architectures consisting of tens or hundreds of thousands of processor cores. The problem occurs when we want or need to load/store these matrices from/to a distributed file system. This paper deals with the design of new formats for storing very large sparse matrices suitable for parallel I/O systems. The first one is based on arithmetic coding and the second one is based on binary tree format. We compare the space complexity of common storage formats and our new formats and prove that the latter are considerably more space efficient.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122407020","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}
The investigation deals with the slip effects on the problem of viscous incompressible flows induced by a stretching sheet. This problem correspond to the planar stretching. The flow is governed by a third-order nonlinear boundary value problem which has been solved by Optimal Homotopy Asymptotic Method (OHAM). Convergence of the OHAM solution is checked. Our method does not depend upon small parameter and obtained results reveal that this procedure is very effective, simple and accurate.
{"title":"Planar Stretching Flows with Partial Slip","authors":"R. Ene, V. Marinca, R. Negrea","doi":"10.1109/SYNASC.2013.24","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.24","url":null,"abstract":"The investigation deals with the slip effects on the problem of viscous incompressible flows induced by a stretching sheet. This problem correspond to the planar stretching. The flow is governed by a third-order nonlinear boundary value problem which has been solved by Optimal Homotopy Asymptotic Method (OHAM). Convergence of the OHAM solution is checked. Our method does not depend upon small parameter and obtained results reveal that this procedure is very effective, simple and accurate.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131536527","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}
Érik Martin-Dorel, L. Rideau, L. Théry, Micaela Mayero, I. Pasca
We present a library for univariate Taylor models that has been developed with the COQ proof assistant. Each algorithm of this library is executable and has been formally proved correct. Using this library, one can then effectively compute rigorous and sharp approximations of univariate functions composed of usual functions such as reciprocal, square root, exponential, or sine among others. In this paper, we present the key parts of the formalisation as well as of the proofs of correctness, and we evaluate the quality of our certified library on a set of examples.
{"title":"Certified, Efficient and Sharp Univariate Taylor Models in COQ","authors":"Érik Martin-Dorel, L. Rideau, L. Théry, Micaela Mayero, I. Pasca","doi":"10.1109/SYNASC.2013.33","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.33","url":null,"abstract":"We present a library for univariate Taylor models that has been developed with the COQ proof assistant. Each algorithm of this library is executable and has been formally proved correct. Using this library, one can then effectively compute rigorous and sharp approximations of univariate functions composed of usual functions such as reciprocal, square root, exponential, or sine among others. In this paper, we present the key parts of the formalisation as well as of the proofs of correctness, and we evaluate the quality of our certified library on a set of examples.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121568260","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}
Exception handling is a mechanism that highlights exceptional functionality of software systems. Currently there are empirical studies pointing out that design entities (classes) that use exceptions are more defect prone than the other classes and sometimes developers neglect exceptional functionality, minimizing its importance. In this paper we investigate if classes that use exceptions are the most complex classes from software systems and, consequently, have an increased likelihood to exhibit defects. We also detect two types of improper usages of exceptions in three releases of Eclipse and investigate the relations between classes that handle/do not handle properly exceptions and the defects those classes exhibit. The results show that (i) classes that use exceptions are more complex than the other classes and (ii) classes that handle improperly the exceptions in the source code exhibit an increased likelihood of exhibiting defects than classes which handle them properly. Based on the provided evidence, practitioners get knowledge about the correlations between exceptions and complexity and are advised once again about the negative impact deviations from best programming practices have at a source code level.
{"title":"Should We Beware the Exceptions? An Empirical Study on the Eclipse Project","authors":"C. Marinescu","doi":"10.1109/SYNASC.2013.40","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.40","url":null,"abstract":"Exception handling is a mechanism that highlights exceptional functionality of software systems. Currently there are empirical studies pointing out that design entities (classes) that use exceptions are more defect prone than the other classes and sometimes developers neglect exceptional functionality, minimizing its importance. In this paper we investigate if classes that use exceptions are the most complex classes from software systems and, consequently, have an increased likelihood to exhibit defects. We also detect two types of improper usages of exceptions in three releases of Eclipse and investigate the relations between classes that handle/do not handle properly exceptions and the defects those classes exhibit. The results show that (i) classes that use exceptions are more complex than the other classes and (ii) classes that handle improperly the exceptions in the source code exhibit an increased likelihood of exhibiting defects than classes which handle them properly. Based on the provided evidence, practitioners get knowledge about the correlations between exceptions and complexity and are advised once again about the negative impact deviations from best programming practices have at a source code level.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133037778","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}
In handwritten mathematics, it is common to have characters in various sizes and for writing not to follow simple baselines. For example, subscripts and superscripts appear relatively smaller than normal text and are written slightly below or above it. Rather than use the location, features and size to identify the character, it may be more effective to do the reverse --- to use knowledge about specific characters to determine baseline, size, etc. In this approach, it is necessary to find the location of certain expected features that are determined by particular points. In earlier work, we have presented a method to derive the determining points for a new instance of a symbol from those on an average model for each symbol type. For those characters that are significantly different from the average instance, one can use a numerical homotopy between the average instance and the target character, and apply the determining point algorithm at each step. The present article studies the factors to be taken into account in performing such homotopies. We examine two strategies for possible starting points for the homotopy, and we examine the relation between the distance and the number of steps required. The first starting point strategy performs a homotopy from the average of samples of the same type. The second strategy uses a homotopy from the nearest neighbour with known determining points. Our experimental results show a useful relation between the homotopy distance and the number of steps usually required and improved strategies to find determining points for poorly written characters.
{"title":"Identifying Features via Homotopy on Handwritten Mathematical Symbols","authors":"Rui Hu, S. Watt","doi":"10.1109/SYNASC.2013.15","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.15","url":null,"abstract":"In handwritten mathematics, it is common to have characters in various sizes and for writing not to follow simple baselines. For example, subscripts and superscripts appear relatively smaller than normal text and are written slightly below or above it. Rather than use the location, features and size to identify the character, it may be more effective to do the reverse --- to use knowledge about specific characters to determine baseline, size, etc. In this approach, it is necessary to find the location of certain expected features that are determined by particular points. In earlier work, we have presented a method to derive the determining points for a new instance of a symbol from those on an average model for each symbol type. For those characters that are significantly different from the average instance, one can use a numerical homotopy between the average instance and the target character, and apply the determining point algorithm at each step. The present article studies the factors to be taken into account in performing such homotopies. We examine two strategies for possible starting points for the homotopy, and we examine the relation between the distance and the number of steps required. The first starting point strategy performs a homotopy from the average of samples of the same type. The second strategy uses a homotopy from the nearest neighbour with known determining points. Our experimental results show a useful relation between the homotopy distance and the number of steps usually required and improved strategies to find determining points for poorly written characters.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122191825","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}
Alexandru-Ciprian Zavoianu, E. Lughofer, G. Bramerdorfer, W. Amrhein, E. Klement
The task of designing electrical drives is a multi-objective optimization problem (MOOP) that remains very slow even when using state-of-the-art approaches like particle swarm optimization and evolutionary algorithms because the fitness function used to assess the quality of a proposed design is based on time-intensive finite element (FE) simulations. One straightforward solution is to replace the original FE-based fitness function with a much faster-to-evaluate surrogate. In our particular case each optimization scenario poses rather unique challenges (i.e., goals and constraints) and the surrogate models need to be constructed on-the-fly, automatically, during the run of the evolutionary algorithm. In the present research, using three industrial MOOPs, we investigated several approaches for creating such surrogate models and discovered that a strategy that uses ensembles of multi-layer perceptron neural networks and Pareto-trimmed training sets is able to produce very high quality surrogate models in a relatively short time interval.
{"title":"An Effective Ensemble-Based Method for Creating On-the-Fly Surrogate Fitness Functions for Multi-objective Evolutionary Algorithms","authors":"Alexandru-Ciprian Zavoianu, E. Lughofer, G. Bramerdorfer, W. Amrhein, E. Klement","doi":"10.1109/SYNASC.2013.38","DOIUrl":"https://doi.org/10.1109/SYNASC.2013.38","url":null,"abstract":"The task of designing electrical drives is a multi-objective optimization problem (MOOP) that remains very slow even when using state-of-the-art approaches like particle swarm optimization and evolutionary algorithms because the fitness function used to assess the quality of a proposed design is based on time-intensive finite element (FE) simulations. One straightforward solution is to replace the original FE-based fitness function with a much faster-to-evaluate surrogate. In our particular case each optimization scenario poses rather unique challenges (i.e., goals and constraints) and the surrogate models need to be constructed on-the-fly, automatically, during the run of the evolutionary algorithm. In the present research, using three industrial MOOPs, we investigated several approaches for creating such surrogate models and discovered that a strategy that uses ensembles of multi-layer perceptron neural networks and Pareto-trimmed training sets is able to produce very high quality surrogate models in a relatively short time interval.","PeriodicalId":293085,"journal":{"name":"2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125029661","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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