About the issue of Internet banking adoption, based on technology acceptance model (TAM), past researches mainly focused on the customers, but seldom researches looked at the Internet banking adoption from banks and their personnel. The bank personnel have financial professionals and are crucial users...

This paper examines the effect of the amendment of an education-related law on university efficiency using the 1994 University Law amendment in Taiwan as a case study. The results indicate that prior to the 1994 amendment; private universities operate in a more efficient manner than public universities....

Traditional evaluation of firm’s market value in credit risk analysis could be contaminated by market noises. The purpose of this article is to price the credit risk in the distance to default with particle filter approach. Compared to the traditional methods, the estimate of the distance to default...

Last year, a Tokyo-based internet venture firm, Hatena Co., ran a political prediction market that was designed to predict the result of the General Election of the Lower House of the Diet, held on September 11, 2005. The market showed reasonable predictive ability that was comparable with the predictions...

Bank runs are usually happened as such that depositors panic and following the consequence of interaction between depositors withdraw their deposits. It is an issue of debt obligation between bank and depositors and an issue of bank capitals distribution among depositors. We consider the role of information...

In this paper we analyse insurance data using Artificial Neural Networks (ANN)[1]. In particular, we use ANN for the problem of Loss Reserving. Loss reserving is the practice of estimating the future payments for the claims which have occurred on an insurance portfolio. A difficulty in forecasting future...

This paper examines the volatility dynamics of the greater China stock markets (Shanghai A- and B-shares, Shenzhen A- and B-shares, Taiwan, and Hong Kong) by employing a multivariate (tetravariate) framework that incorporates the features of asymmetries, persistence, and time-varying correlations, which...

The link between stock returns and economic growth has been an important research topic in the financial economic literature. The purpose of this study is to employ a threshold vector autoregressive (TVAR) approach in order to investigate the non-linear relationship between stock returns and output growth...

This paper proposes a class of nonlinear stochastic volatility (SV) models based on the Box-Cox transformation. The proposed class encompasses many parametric SV models that have appeared in the literature, including the well known lognormal SV model, and has an advantage in the ease with which different...

Due to the rapid grow up of transaction volume of derivatives in the financial market, the Black-Scholes options pricing model (BSM) is played an important role recently and widely applied in various options contract. However, this theoretical model limited by the influences of many unexpected real world...

This paper presents a framework and tools for modeling and simulating societies as complex systems. Although the concept of the complex systems has been highly demanded in social sciences, there is no satisfactory scheme for modeling and simulating it. In this paper, we propose the model framework, which...

This paper extends the dynamic programming, utility maximization model proposed by Wang (2004) to value an investment opportunity whose income streams follows a regime-switching process in incomplete markets. Specifically, the model is applied to solve for certainty equivalent of an investment opportunity...

This study develops inter-temporal dynamic asset allocation with stochastic volatility (DAASV) models. The DAASV models integrate the stochastic volatility feature inherent in asset returns into the allocation procedure. By applying the DAASV, an investor can more efficiently diversify the unsystematic...

The convergence of estimators, e.g., maximum likelihood estimators, for increasing sample size is well understood in many cases. However, even when the rate of convergence of the estimator is known, practical application is hampered by the fact, that the estimator cannot always be obtained at tenable...

The significant jump in world crude oil price over the past year has raised great concern over the economic impact that such a price shock may bring about on Taiwan’s economy, which has been characterized by extremely high import-oil dependence. Previous analyses have been tackling similar issue from...

In 1980s, many empirical researches’ findings (i.e., Shiller(1984), Thaler (1985) et al. ) did not support efficient market hypothesis (EMH). Previous studies (e.g., Bernartzi and Thaler, 1995) related to behavioral model suggest that certain market anomalies are consistent with the presence of irrational...

In this paper, we studied complexity and entropy density of stock market by modeling epsilon-machine of Korean Composition Stock Price Index (KOSPI) from year 1992 to 2003 using causal-state splitting reconstruction (CSSR) algorithm.

The Black-Scholes options pricing model (BSM) is limited by the influences of many unexpected real world phenomena caused due to its six unreasonable assumptions, which often make the miss-pricing result because of the difference of market convention in practical. If we were to soundly take these phenomena...

M&A and green field investment (GFI) are very important methods of company growth. Each of the investment ways could bring different outstanding achievement and development of company, so it is very important to choose the way of investment. This paper discusses the boundary of M&A and green field investment...

The prospect theory implies that the inclusion of a gain-lock-in device into the floor of portfolio insurance can benefit the long-term asset management under loss aversion. We find that the relaxation of the multiple of the CPPI from a constant to a dynamic can improve the performance in the short-term....

This paper examined bankruptcy predictive accuracy of five statistics models--discriminant analysis logistic regression, probit regression, neural networks, support vector machine (SVM), and genetic-based SVM (GA-SVM) that influenced by variable selection. Empirical results indicate that the SVM-based...

Security Exchange Commission in Taiwan requires all public companies to file and announce their monthly sales figure by the of the following month. This requirement has established another channel for market investors to obtain additional accounting information on a more timely basis than quarterly or...

Knowledge management (KM) is suggested as a method to manage and apply knowledge for business management. In this paper, we suggest a framework based on OPF (Open Process Framework) meta model for the knowledge-based decision-making. Based on the modeling method of OPF, we can translate partial and implicit...

This study attempts to find the possibility of making relatively higher profit with lower risk when trading futures commodities. The system applies XCS classifiers to explore the rules of spread trading of these commodities. Our simulation holds a trading strategy that in every transaction, the proposed...

The purpose of this empirical study is intended to investigate XCS (Extended Classifier System) based model with knowledge rules for dynamic TIPP (Time Invariant Portfolio Protection) policy. There are two XCS-based agents in the proposed model (MA-TIPP).One agent dynamically optimizes Multiple and Tolerance...

A hybrid BPNN-weighted GREY-C3LSP prediction (BWGC) is used for resolving the overshooting phenomenon significantly; however, it may lose the localization once volatility clustering occurs. Thus, we propose a compensation to deal with the time-varying variance in the residual errors, that is, incorporating...

We provide a framework for learning risk-neutral measures (Martingale measures) for pricing options from high frequency financial data. In a simple geometric Brownian motion model, a price volatility, a fixed interest rate and a no-arbitrage condition suffice to determine a unique risk-neutral measure....

In this paper, we replicate Nelson-Winter model in order to analyze the inter-enterprise competition from the perspective of economic change. For this purpose, we build the simulation model as Multi-Agent-Based Simulation in PlatBox Simulator. By replicating the Nelson-Winter model, which clarifies the...

This paper provides the most complete evidence to date on the importance of monetary aggregates as a policy tool in an inflation forecasting experiment. Every possible definition of ‘money’ in the USA is being considered for the full data period (1960 – 2006), using the most sophisticated non-linear...

Stock data mining such as financial pairs mining is useful for trading supports and market surveillance. Financial pairs mining targets mining pair relationships between financial entities such as stocks and markets. This paper introduces a fuzzy genetic algorithm framework and strategies for discovering...

The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable classification accuracy. In this paper, we propose a combination of genetic...

In this paper we adopt the Markov-switching specification to establish the hybrid model with time-varying loading on each of chartist and fundamentalist techniques. The US dollar exchange rates of four Asian tiger countries’ currencies serve as the representative examples in this paper. Our empirical...

Most of GA-based portfolio assets allocation uses normalization method to allocate investment asset’s weight. However, the normalization process will cause unease converging and even diverging characteristics, because it changes the gene’s relativity of address in chromosome. In this paper, we propose...

Artificial intelligence decision support system is always a popular topic in providing the human user with an optimized decision recommendation when operating under uncertainty in complex environments. The particular focus of our discussion is to compare different methods of artificial intelligence decision...

This paper outlines a data mining approach to analysis and prediction of the trend of stock prices. The approach consists of three steps, namely partitioning, analysis and prediction. A modification of the commonly used k-means clustering algorithm is used to partition stock price time series data. After...

This paper uses data from Taiwan’s banking sector to investigate if state-owned banks can serve as an internal regulation mechanism to sustain market competition. In contrast to the traditional second-best literature, the evidence shows that a certain degree of market coordination exists in the industry,...

As everyone knows, multiple regression analysis is an important approach to prediction studies. However, regression model has some limitations and constraints in the real world practices. This study applied fuzzy regression using neural network (FRNN) to predict organizational performance, and the findings...

A novel training paradigm for artificial neural networks had been developed and presented in this article. In the proposed approach, a revised version of particle swarm optimization (PSO) had been employed to find out the optimal connection weights of feed-forward artificial neural networks for given...

GARCH model has a long history and permeates the modern financial theory. Most researchers use several thousands of financial data and maximum likelihood to estimate the coefficients of model. Statistically, more samples imply better estimation but are hard to obtain. How many samples are sufficient...

In order to be competitive in the semiconductor manufacturing industry, quality improvement and yield enhancement have received increasing attention. The research focuses on the molding process of Integrated Circuit (IC) assembly. The defects often occurred in molding process include hole, vein, crack,...

we propose a hybrid decision model for supporting the ranking financial status of corporations using case-based reasoning augmented with genetic algorithms and the fuzzy nearest neighbor method. An empirical experimentation on 746 cases was conducted that shows that the average accuracy of the ranking...

Concept hierarchies are important for generalization in many data mining applications. We propose a method to automatically build a concept hierarchy from a provided distance matrix. The method is a modification of traditional agglomerative hierarchical clustering algorithm. When two closest clusters...

In this paper, we propose a new genetic algorithm based on the two-dimensional encoding method. Appropriate two-dimensional crossover and mutation operations are designed based on the two-dimensional representation to generate the next generations. A two-dimensional repairing mechanism is also proposed...

A major failure of rational models (cognitive science, game theory) of organizations is the use of static concepts of interdependence to predict dynamic behavior. A quantum model of organizations transforms the traditional model with its dynamic interdependence of uncertainty. We consider field and laboratory...

Investors’ overconfidence and regret aversion lead to behavioral biases, such as over-reaction、under-reaction and disposition effect. By constructing a numerical simulation model, this paper shows that, return distributions under the behavioral biases have higher peaks and fatter tails, and they are...

The main objective of this study is developing a linguistic cluster model in order to meet the public security index requirement and extract crime rule in time series. In contrast to the current studies in crime theory which mostly rely on traditional behavior science, we turned to a hybrid approach...

Information technology (IT) has been extensively adopted in banking industries. The reasons for this massive adoption of IT are mainly twofold: for individual banks, IT can reduce banks’ operational costs (the cost advantage), and facilitate transactions among customers within the same network (the network...

Most researches have focused on the use of document feedback or factor analysis as metrics for financial distress prediction. The theoretical basis for the former is relatively weak, while the latter is severely limited by data requirements. As such, this paper will instead use grey relation analysis...

A general phenomenon puzzles all investors is that on one hand, most individual investors believe they need to construct the portfolio consisting of 15 or more stocks to prevent risk because that large investment companies frequently get high returns is due to they obey the existing investment theory...

As the era of knowledge economy is prevalent in U.S. during 1992, knowledge economy plays an important role around the world. The value and competition of the traditional companies accounted on tangible assets. However, in the era of knowledge economy, the value and continuing operation of the companies...

The medical care industry has been dramatically developed in the last two decades in Taiwan and it has resulted in an extremely risky position. The purpose of the research was the development of a neural network model to recognize profitable customers for dental services marketing. Data set was built...

This paper presents a institutional framework for the currency basket peg system. After the Asian currency crisis, the needs of seeking adaptive currency system has risen up but the best currency system has not still appeared. In this paper, we propose the model of “the currency basket peg system”. This...

The purpose of this study is to make a basic Foreign Exchange Market Model. It is important to make a simple basic model at first to understand the complex emergence of exchange rate which is caused by various factors. The model is a multiagent-based model, consisting of dealer and speculator. Both agents’...

Markov Chain Model provides a concise mathematical model to describe the online English auction process, converting the complicated interaction between the bidders and auctioneer into a tractable mathematical problem, which is a milestone for researches involved in this area. However, the assumptions...

The mean-variance framework for portfolio selection should be revised when investor’s concern is the downside risk. This is especially true when the asset returns are not normal. In this paper, we incorporate value-at-risk (VaR) in portfolio selection and the mean-VaR framework is proposed. Due to the...

Using the laboratory experiment and simple multi–Prisoner’s dilemma model, this paper explores the effect of the change in the number of contacts and in the contact (payoff) structure, and then the characteristics of the strategy that leads players to reach mutual cooperation. When the number of contacts...

One purpose of this paper is to propose hybrid neural network models for bankruptcy prediction. The proposed hybrid neural network models are, respecitvely, a MDA model integrated with financial ratios, a MDA model integrated with financial ratios and intellectual capital ratios, a MDA-assisted neural...

We are developing an artificial stock market model with investor agents in order to analyze characteristics of a market price. In this paper, we analyze the effects of agent’s reaction rate to technical indicators in a financial market. Intensive experiments have suggested that trend follow investor...

Resource allocation in the econophysics of competing supermarket chains, modelled as a Multi-Agent System is addressed in the context of finding good method to increase the competitiveness of the company in networked economy. A special swapping algorithm which increased the local clustering effects of...

A link in production network is usually a creditor-debtor relationship. If a firm goes into financial insolvency state or bankruptcy, then firms on its upstream can have secondary effect from the bankruptcy. By using the recent 10 years data of bankruptcy in japan, we show that these causes of ``link...

This paper adopts the grey prediction methods, to investigate the return and volatility of major index futures among American and Eurasian markets. The grey relational theory and GM(1,N) model are further used to observe the volatility spillover effect and find the main influence factor in the volatility...

Combining the concepts of balanced scorecard, fuzzy set theory and entropy, a systematic fuzzy multiple criteria decision making (MCDM) for airlines operating performance evaluation is proposed. A hierarchical structure is constructed through the concept of balance scorecard includes four perspectives:...

Building on the framework presented in The Nature of Creative Development (Stanford U. Press, 2006), I describe an approach for representing researchers' focuses of research activity in a field; the approach is based on use of a knowledge representation framework. Application is made to the field of...

In order to reduce the bias of linguistic recognitions among the group decision makings, this study develops “fuzzy multiple preference model” with two stages to better determining the suitable service innovation. A real numerical application in the chain wholesale has also been demonstrated.

This research utilizes the Agent-Based Model to clarify microscopic and macroscopic links between investor behavior and price fluctuations in the financial market. This analysis places focus on the role that investors’ overconfidence plays in the financial market. As a result of this analysis, it has...

Consider an enterprise that wants to expand its business to multiple cities in global and to be one of well-known multinational enterprises (MNEs). Suppose the MNE hopes each planning investment subsidiary gleans a specific target return within a constant time horizon. Under this premise, this paper...

In the trading operation of dynamic portfolio insurance, TIPP (Time Invariant Portfolio Protection), when adjusting active assets, only considers the scale of asset of that time regardless of how market trend proceeds. In other words, TIPP is clumsy in evading loss and pursuing profits. This study makes...

We compare the use of artificial neural networks and Gaussian processes for forecasting. We show that Artificial Neural Networks have the advantage of being utilisable with greater volumes of data but Gaussian processes can more easily be utilised to deal with non-stationarity.

In this paper, we apply the CART ,C5.0 , GP decision tree classifiers and compares with logic model and ANN model for Taiwan listed electronic companies bankruptcy prediction. Results reveal that the GP decision tree can outperform all the classifiers either in overall percentage of correct or k-fold...

This paper is intended to integrate Internet Marketing, Customer Experience, E-brand and Integrated Marketing Communications to develop a high benefits Internet Marketing Framework. This framework not only can combine marketing resources effectively, let enterprises obtain the greatest benefits; it also...

This study focuses on an enterprise that wants to expand its business to multiple cities in global and to be one of well-known multinational enterprises (MNEs). Suppose the enterprise utilizes the wholly owned market entry strategy, as well as the decentralized synchronized (market) advancement strategy...

In this paper empirical tests for the overreaction and underreaction hypothesis in the Brazilian stock market are presented. For these tests, due to the complexity of these phenomena, a new model based on the fuzzy set theory is proposed. It is shown that such model is strongly connected with two heuristics...

This paper proposes a modified copula approach to defining correlation dependence used for pricing credit derivatives. For both single-name and multiname products, how default correlations react to common shocks should be appropriately measured. The copula approach is an effective method for this purpose....

Annuities can be effective tools in managing longevity risk in retirement planning. This paper develops a framework that merges annuity purchase decisions with consumption-investment selections in retirement planning. After introducing a pricing model and a benefit payment model for an annuity, we construct...

Stock time series query is one of the fundamental components in technical analysis. Technical analysts would like to query either a whole time series or a segment of a time series in different resolutions for long-term or short-term investigations. Moreover, unnecessary data points should be filtered...

Traditional financial planning procedures began from taking into account the planner’s initial financial situation, his/her financial goals, and expectations for the future, etc. and then calculating the future cash flows for different time periods under variant scenarios. If the planning result cannot...

Academic researchers and practitioners have proposed various stock-screening models that always contain more than one stock selecting rule and corresponding parameters. However, the criteria in traditional screening models employ crisp norms, which are unreasonable in reality. This paper proposes the...

This paper aims at proposing a hybrid mining approach for e-retailers to analyze returns patterns from both the customer and product perspectives, classify customers and products by returns ratios, and then adopt proper returns policies and marketing strategies to the identified classes for reducing...

The prior studies are focus on the association between merge and acquisition (M&A) announcement and stockholders’ wealth. There are few studies examining the change in the level of information asymmetry at M&A announcement. Our study, therefore, goes to fill out the aspect. This paper empirically investigates...

This paper suggests that the interaction between consumers has an impact on market structure, in addition to each consumer’s own behavior. In this paper, we replicate the artificial market model proposed by Onozaki and Yanagita, and extend it by adding the network of consumers in order to show that the...

This study combines extended Kalman filters (EKFs) and support vector machines (SVMs) to implement a fast online predictor for option prices. The EKF is used to infer latent variables and makes a prediction based on the Black-Scholes formula, while the SVM is employed to capture the nonlinear residuals...

Recent financial liberalization in Taiwan has caused local banks to face major structural changes. This paper examines the cost structure of 36 local banks in Taiwan using the translog cost function and attempts to identify suitable operating strategies for cost reduction and performance improvements....

We extend the basic random walk Markov-Switching model in two ways and evaluate the out-of-sample forecasting performance on the Japanese yen during 1995-2004. First, we estimate both a two- and also a three-regime Markov switching models. Second, we add four exogenous variables as suggested in the monetary...

To understand the causal relationship of stock market is always a top priority for investors. Most investors use some fundamental knowledge and basic analysis techniques to analyze or predict the trends. However, there are always some other factors beyond our control or unexpected events that might affect...

The study examines whether the contrarian investment strategy, implies simultaneously buying previous losers and selling previous winners, exists in stock market of Taiwan. This study utilizes De Bondt and Thaler (1985) contrarian strategies into listed electronic and informational stocks in Taiwan from...

The behaviors of the real exchange rate corresponding to capital mobility within an open-economy macroeconomic framework are investigated. Chaotic phenomena are reasonable candidates for analyzing the random walk behaviors of the given real exchange rate model similar to the simple logistic map. Method...

Index funds are popular investment tools currently being used in modern portfolio management; moreover, it has been observed that the performances of index funds are better than those of many other actively managed funds Elton, et al. (1996). The strategy is taken by fund managers when their portfolios...

Classical Genetic Algorithms(CGAs)accomplish the global search by selection,crossover and mutation. It has many shortages. Here we proposed a restricted genetic algorithm based on ascending of tangent plane(RGAATP). Our algorithm is simple and effective, which approaches the global solution step by step....

The notion of a ripple effect in the housing market implies stationarity in regional:national house price ratios. The central aim of this study is to investigate whether the ripple effect exists in Taiwan’s regional house price ratio by implementing the Breuer et al. (2001) Panel SURADF unit root tests,...

This study adopts derivative pricing as an indicator of market expectations, with those results suggesting that general investors can use market expectations to predict the final settlement value of underlying assets. Most investment textbooks note that one of the major functions of futures is price...

The aim of this paper is to gain the broad explanation of corruption using simple computational model. We elaborated further the model of corruption described previously in [4], with some additions in model’s properties. We performed hundreds of experiments computationally using Swarm and constructed...

This paper examines the welfare implications of managing asset-price with consumer-price inflation targeting by monetary authorities who have to learn the laws of motion for both inflation rates. Our results show that the Central Bank can improve welfare if it targets both consumer and asset-price inflation...

Global competition is fierce. Especially, it is in the telecom market. It is a more and more difficult task for retaining profitable customers for a telecom company. In this paper, a retention system based on the customer intelligence is introduced. The system was successfully used for one telecom company...

This paper describes a decision making support system developed for asset liability management of a Paraguayan pension fund company. The model combines a parallel Multi-objective Evolutionary Algorithm and stochastic scenario generators to find good asset allocations that optimize several conflicting...

Stock options are usually sold in bundles of 100 units, and their price can be quoted either per unit or per bundle. In this paper, the effect of different methods of quoting financial asset prices on the subjective value of a contract was examined experimentally. In particular, we examined differences...

Traditional portfolio insurance (PI) strategy, such as CPPI, only considers the floor constraint but not the goal aspect. This paper proposes a goal-directed (GD) strategy to express an investor's goal-directed trading behavior and combines this floor-less GD strategy with the goal-less CPPI strategy...

The purpose of this research is to explore the IPO pricing behavior in an underwriting system by applying the fuzzy game theory. Results of this study are: (1) The application of the fuzzy game theory is more consistent with the uncertainty relationship of human interference between independent and dependent...

This paper uses a grey forecasting model GM(1,1) on improving the investment performance of classical Markowitz efficiency frontier’s investment portfolio using the component markets’ indexes of MSCI World Index from 1999 to 2005 as the samples. Using grey Markowitz efficiency frontier’s investment portfolio...

This article compares the forecasting performance of the conditional autoregressive range (CARR) model with the commonly adopted GARCH model. Two major stock indices, FTSE 100 and Nikkei 225, are studies using the daily range data and daily close price data over the period 1990 to 2000. Our results suggest...

Increasing complexity of the modern market dynamics requires new quantitative frameworks for the discovery of stable portfolio strategies. Important requirements include the ability of the coupled and self-consistent optimization of the dynamic strategies and asset allocations as well as robust built-in...

AN EVOLUTIONARY IDEA OF EVOLUTION: A PEIRCEAN INTERPRETATION OF A HYBRID-AGENT ORGANIZATION MODEL This paper proposes an evolutionary interpretation of a hybrid-agent organization model. Charles S. Peirce’s conception of evolution, a combination in some Darwinian and Lamarckian ideas, is a key component...

In the financial time series forecasting field, the problem that we often encountered is how to increase the predict accuracy as possible using the noisy financial data. In this study, we discuss the use of supervised neural networks as the metamodeling technique to design a financial time series forecasting...

In this paper we present a semi-automated search procedure to deal with the problem of the identification of the contemporaneous causal structure connected to a large class of multivariate time series models. We propose to use graphical causal models for recovering partial information about the contemporaneous...

Based upon the raw S&P 500 portfolio performance in eight consecutive years, this paper gives an overview analysis of the application of influence diagram to portfolio management. Our findings provide a ground for the question: Is the structure information provide by the expert superior to the one generated...

This paper aims to analyse the risks involved in reverse mortgage on a forward sale of house by elderly homeowner. We provide a practical solution to institutions planning to issue such reverse mortgages. We propose the formation of Senior Citizens Housing Trust for retired homeowners who wish to sell...

This paper aims at identifying steady state relations (cointegrated relationships) in a system that contains multidirectional nexuses for a hypothetical economic structure. The study discusses various econometric tools needed to identify long run cointegration vectors and employs these tools to derive...

We present a Markov process that provides an analytical framework for a comprehensive analysis of trading efficiency comprising price and order data. Agents place orders and/or accept already placed orders. Transactions are generated by matching orders. We apply the well known Discrete Choice logit approach...

The purpose of this paper is to provide an algorithm for commercial banks in Taiwan to evaluate the credibility of their potential debtors from the default probability viewpoint under fuzzy environment. The fundamental concepts we have adopted include the eigenvector method, fuzzy Delphi method, fuzzy...

We employ the methods of neural network (hereafter NN) and genetic programming (hereafter GP) in this paper to construct a spread trading system, respectively, to forecast the trend of the price spread between Taiwan Stock Exchange Electronic Index Futures (hereafter TE) and Taiwan Stock Exchange Finance...

The purpose of this paper is to provide an algorithm for the motion picture companies to evaluate the key capabilities from firm viewpoint under fuzzy environment. The fundamental concepts we have adopted include the eigenvector method, fuzzy Delphi method, fuzzy set theory, and multi-criteria decision...

This paper studies the possibilities that genetic algorithm describes investor sentiment, and time series properties of estimated models. For these purposes, first we identify the conditions for describing investor sentiment by altering parameters of genetic algorithm. Then the auto-correlations and...

Based on a thorough comparison of the basic assumptions and economic underpinning of the Ramsey and over lapping generation (OLG) model, this study builds both static and dynamic computable general equilibrium tax policy models to analyze the effect of tax reform on Taiwan’s economy. The new tax structure...

We propose a new method based on evolutionary optimization for obtaining an optimal Lp-quantizer of a multidimensional random variable. First, we remind briefly the main results about quantization. Then, we present the classical gradient-based approach used up to now to find a “local” optimal Lp-quantizer....

Online group purchasing or collective purchasing is the activity in which people who desire to buy the same merchandises join together so that they can negotiate with sellers for a better price through Internet. This paper utilizes fuzzy logic to develop a bargaining model for such activities. The model...

The hybrid Monte Carlo (HMC) algorithm is used for Bayesian analysis of the generalized autoregressive conditional heteroscedasticity (GARCH) model. The HMC algorithm is one of Markov chain Monte Carlo (MCMC) algorithms and it updates all parameters at once. We demonstrate that how the HMC reproduces...

This research presents the application of the Goal Graph in the methodology of generating software requirements specification, in order to improve the modifiability of the customization the Goal Graph. We propose an algorithm that optimizes the quality factor of modifiability for the Goal Graph to enhance...

Quality Function Deployment (QFD) is an approach to translate customer requirements into technical requirements for a product or service. The traditional QFD provides a fundamental analysis, but it is still inconvenient when decision making in technical design should address business objection. The competition...

This paper advances Multilevel Stochastic Dynamic Process (MSDP) models as a new framework for modeling nonstationary and nonlinear time series and complex systems, and discuss possible applications of MSDP models in global financial market analysis and surveillance. Under the heterogeneous market hypothesis,...

Shopping online has become more and more popular. Many people participate in online auctions. Due to the popularity of online auction, this study intends to study the possible factors that affect the transactions in online auction. This study uses the MP3 in the auction of Yahoo! Taiwan as the target...

Is just only one cointegrating vector among the panel variables? Based on the multivariate maximum likelihood cointegration tests offered by Larsson et al. (2001), the findings here provide solid evidence of the presence of at least two cointegrated vectors for the money demand function in GCC countries.

Using artificial neural network is a common approach for the stock time series prediction problem. Unlike variety of researches that focus on selecting different indicators, network training, network architecture, etc., we are focusing on the selection of appropriate time points from the time sequence...

The traditional multi-step ahead prediction is based on sequential algorithm to run multi-step ahead prediction and it brings error propagation problem. Furthermore, the prediction error of multi-step ahead includes both system and propagation errors. Therefore, how to decrease the propagation error...