International journal of applied mathematics and statistics, 2015
This paper introduces an infinite mixture model which can be used to fit the real data set for 1,... more This paper introduces an infinite mixture model which can be used to fit the real data set for 1,296 observations. We also compare the result of the fit for three classical models (i.e. exponential, inverse exponential and lognormal distributions) and that of infinite mixture distribution. The K-S test reveals that the infinite mixture distribution gives the best fit.
In risk theory, insurance premiums are calculated from a model using claim data which can be cons... more In risk theory, insurance premiums are calculated from a model using claim data which can be constructed in two dimensions with one dimension representing time and the other representing distinct insured individuals. Several models found in the literature allow for independent assumptions across different risks for the sake of convenience and mathematical tractability. However, these assumptions may be violated in some practical situations. In this paper, modeling claim dependence is built under the common effect. According to the model, we express the expected claims given the history of all observable claims (Bayesian premiums) in explicit form with lognormal claim amounts distribution.
In this paper, we study the existence of periodic solution for impulsive periodic control system ... more In this paper, we study the existence of periodic solution for impulsive periodic control system with parameter perturbation on infinite dimensional space, in these cases where the differential operator involved is the infinitesimal generator of $ C_ {0}$ semigroup.
Data stream analysis is the process of computing various summaries and derived values from large ... more Data stream analysis is the process of computing various summaries and derived values from large amounts of data which are continuously generated at a rapid rate. The nature of a stream does not allow a revisit on each data element. Furthermore, data processing must be fast to produce timely analysis results. These requirements impose constraints on the design of the algorithms to balance correctness against timely responses. Several techniques have been proposed over the past few years to address these challenges. These techniques can be categorized as either dataoriented or task-oriented. The data-oriented approach analyzes a subset of data or a smaller transformed representation, whereas taskoriented scheme solves the problem directly via approximation techniques. We propose a hybrid approach to tackle the data stream analysis problem. The data stream has been both statistically transformed to a smaller size and computationally approximated its characteristics. We adopt a Monte C...
In this paper, we forecast SET50 Index (The stock prices of the top 50 listed companies on SET (S... more In this paper, we forecast SET50 Index (The stock prices of the top 50 listed companies on SET (Stock Exchange of Thailand)) by using multiple regression. At the same time, we consider the existence of a high correlation (the multicolinearity problem) between the explanatory variables. One of the approaches to avoid this problem is the use of principal component analysis (PCA). In this study, we employ principal component scores (PC) in a multiple regression analysis. As can be seen, 99.4% of variation in SET50 can be explained by all PCAs. Accordingly, we forecast SET50 Index closed price for the period 1/03/2011 through 31/03/2011 by using three models. We compare loss function, the model forecast explained by all PCs have a minimum of all loss function. 1 Program of Mathematics and Applied Statistics, Faculty of Science and Technology, Nakhon Ratchasima Rajabhat University, Nakhon Ratchasima, Thailand. e-mail: nopsopipan@gmail.com , wanava29@gmail.com 2 School of Mathematics, Sur...
One of the problems of stock trading is that the stock prices are not consistent, depending on ma... more One of the problems of stock trading is that the stock prices are not consistent, depending on market condition. The Mean Reversion process of Pairs Trading is a market neutral strategy, which is independent of market movements and carried an assumption that any trading index will reverse to its mean value. This paper proposes a novel algorithm, called ‘multiclass Pairs Trading’ , which is an advance of co-integration method in Pairs Trading technique. The proposed model uses Mean Reversion and coefficient of variance (CV) to analyze and classify a series of stocks to have different distribution. It provides a buffer-trading zone when the paired stocks are about to change their directions from high to low and vice versa . Moreover, this model extends an opportunity for any highly correlated and paired stocks to cross-trade with any lowly correlated and paired stocks. It serves to improve performance in portfolio trading. The 10-year data were collected from 127 stocks listed in the ...
Seleccionar todos Título: El uso de trazos y puntos como ayuda para la ubicación del texto litera... more Seleccionar todos Título: El uso de trazos y puntos como ayuda para la ubicación del texto literario en los cancioneros franceses y españoles de finales del siglo XV y comienzos del XVI Autores: OLMOS, Ángel Manuel Revista: Revista de musicología, 2001 ENE-DIC; XXIV (1-2 ...
16th International Workshop on Database and Expert Systems Applications (DEXA'05)
ABSTRACT Clustering is a task of grouping data based on similarity. A popular k-means algorithm g... more ABSTRACT Clustering is a task of grouping data based on similarity. A popular k-means algorithm groups data by firstly assigning all data points to the closest clusters, then determining the cluster means. The algorithm repeats these two steps until it has converged. We propose a variation called weighted k-means to improve the clustering scalability. To speed up the clustering process, we develop the reservoir-biased sampling as an efficient data reduction technique since it performs a single scan over a data set. Our algorithm has been designed to group data of mixture models. We present an experimental evaluation of the proposed method.
ABSTRACT In this paper, we forecast the volatility and price of SET50 Index using the Markov Regi... more ABSTRACT In this paper, we forecast the volatility and price of SET50 Index using the Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether the MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecast volatility and price of the SET50 Index. The MRS-GARCH under the GED distribution is best performance model for the SET50 Index volatility. Moreover, we forecast closing price of SET50 Index, we found the MRS-GARCH under t-distribution with two degree of freedoms model is perform best.
International journal of applied mathematics and statistics, 2015
This paper introduces an infinite mixture model which can be used to fit the real data set for 1,... more This paper introduces an infinite mixture model which can be used to fit the real data set for 1,296 observations. We also compare the result of the fit for three classical models (i.e. exponential, inverse exponential and lognormal distributions) and that of infinite mixture distribution. The K-S test reveals that the infinite mixture distribution gives the best fit.
In risk theory, insurance premiums are calculated from a model using claim data which can be cons... more In risk theory, insurance premiums are calculated from a model using claim data which can be constructed in two dimensions with one dimension representing time and the other representing distinct insured individuals. Several models found in the literature allow for independent assumptions across different risks for the sake of convenience and mathematical tractability. However, these assumptions may be violated in some practical situations. In this paper, modeling claim dependence is built under the common effect. According to the model, we express the expected claims given the history of all observable claims (Bayesian premiums) in explicit form with lognormal claim amounts distribution.
In this paper, we study the existence of periodic solution for impulsive periodic control system ... more In this paper, we study the existence of periodic solution for impulsive periodic control system with parameter perturbation on infinite dimensional space, in these cases where the differential operator involved is the infinitesimal generator of $ C_ {0}$ semigroup.
Data stream analysis is the process of computing various summaries and derived values from large ... more Data stream analysis is the process of computing various summaries and derived values from large amounts of data which are continuously generated at a rapid rate. The nature of a stream does not allow a revisit on each data element. Furthermore, data processing must be fast to produce timely analysis results. These requirements impose constraints on the design of the algorithms to balance correctness against timely responses. Several techniques have been proposed over the past few years to address these challenges. These techniques can be categorized as either dataoriented or task-oriented. The data-oriented approach analyzes a subset of data or a smaller transformed representation, whereas taskoriented scheme solves the problem directly via approximation techniques. We propose a hybrid approach to tackle the data stream analysis problem. The data stream has been both statistically transformed to a smaller size and computationally approximated its characteristics. We adopt a Monte C...
In this paper, we forecast SET50 Index (The stock prices of the top 50 listed companies on SET (S... more In this paper, we forecast SET50 Index (The stock prices of the top 50 listed companies on SET (Stock Exchange of Thailand)) by using multiple regression. At the same time, we consider the existence of a high correlation (the multicolinearity problem) between the explanatory variables. One of the approaches to avoid this problem is the use of principal component analysis (PCA). In this study, we employ principal component scores (PC) in a multiple regression analysis. As can be seen, 99.4% of variation in SET50 can be explained by all PCAs. Accordingly, we forecast SET50 Index closed price for the period 1/03/2011 through 31/03/2011 by using three models. We compare loss function, the model forecast explained by all PCs have a minimum of all loss function. 1 Program of Mathematics and Applied Statistics, Faculty of Science and Technology, Nakhon Ratchasima Rajabhat University, Nakhon Ratchasima, Thailand. e-mail: nopsopipan@gmail.com , wanava29@gmail.com 2 School of Mathematics, Sur...
One of the problems of stock trading is that the stock prices are not consistent, depending on ma... more One of the problems of stock trading is that the stock prices are not consistent, depending on market condition. The Mean Reversion process of Pairs Trading is a market neutral strategy, which is independent of market movements and carried an assumption that any trading index will reverse to its mean value. This paper proposes a novel algorithm, called ‘multiclass Pairs Trading’ , which is an advance of co-integration method in Pairs Trading technique. The proposed model uses Mean Reversion and coefficient of variance (CV) to analyze and classify a series of stocks to have different distribution. It provides a buffer-trading zone when the paired stocks are about to change their directions from high to low and vice versa . Moreover, this model extends an opportunity for any highly correlated and paired stocks to cross-trade with any lowly correlated and paired stocks. It serves to improve performance in portfolio trading. The 10-year data were collected from 127 stocks listed in the ...
Seleccionar todos Título: El uso de trazos y puntos como ayuda para la ubicación del texto litera... more Seleccionar todos Título: El uso de trazos y puntos como ayuda para la ubicación del texto literario en los cancioneros franceses y españoles de finales del siglo XV y comienzos del XVI Autores: OLMOS, Ángel Manuel Revista: Revista de musicología, 2001 ENE-DIC; XXIV (1-2 ...
16th International Workshop on Database and Expert Systems Applications (DEXA'05)
ABSTRACT Clustering is a task of grouping data based on similarity. A popular k-means algorithm g... more ABSTRACT Clustering is a task of grouping data based on similarity. A popular k-means algorithm groups data by firstly assigning all data points to the closest clusters, then determining the cluster means. The algorithm repeats these two steps until it has converged. We propose a variation called weighted k-means to improve the clustering scalability. To speed up the clustering process, we develop the reservoir-biased sampling as an efficient data reduction technique since it performs a single scan over a data set. Our algorithm has been designed to group data of mixture models. We present an experimental evaluation of the proposed method.
ABSTRACT In this paper, we forecast the volatility and price of SET50 Index using the Markov Regi... more ABSTRACT In this paper, we forecast the volatility and price of SET50 Index using the Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether the MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecast volatility and price of the SET50 Index. The MRS-GARCH under the GED distribution is best performance model for the SET50 Index volatility. Moreover, we forecast closing price of SET50 Index, we found the MRS-GARCH under t-distribution with two degree of freedoms model is perform best.
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