Search results for: Stock price.

Authors: Petr Seďa

Abstract:

This paper deals with heterogeneous autoregressive models of realized volatility (HAR-RV models) on high-frequency data of stock indices in the USA. Its aim is to capture the behavior of three groups of market participants trading on a daily, weekly and monthly basis and assess their role in predicting the daily realized volatility. The benefits of this work lies mainly in the application of heterogeneous autoregressive models of realized volatility on stock indices in the USA with a special aim to analyze an impact of the global financial crisis on applied models forecasting performance. We use three data sets, the first one from the period before the global financial crisis occurred in the years 2006-2007, the second one from the period when the global financial crisis fully hit the U.S. financial market in 2008-2009 years, and the last period was defined over 2010-2011 years. The model output indicates that estimated realized volatility in the market is very much determined by daily traders and in some cases excludes the impact of those market participants who trade on monthly basis.

Keywords: Global financial crisis, heterogeneous autoregressive model, in-sample forecast, realized volatility, U.S. stock market.

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Authors: Leila Jafari, Viliam Makis

Abstract:

In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: Condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand.

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Authors: Shang-En Yu

Abstract:

Human society, there are many uncertainties, such as economic growth rate forecast of the financial crisis, many scholars have, since the the Song Chissom two scholars in 1993 the concept of the so-called fuzzy time series (Fuzzy Time Series)different mode to deal with these problems, a previous study, however, usually does not consider the relevant variables selected and fuzzy process based solely on subjective opinions the fuzzy semantic discrete, so can not objectively reflect the characteristics of the data set, in addition to carrying outforecasts are often fuzzy rules as equally important, failed to consider the importance of each fuzzy rule. For these reasons, the variable selection (Factor Selection) through self-organizing map (Self-Organizing Map, SOM) and proposed high-end weighted multivariate fuzzy time series model based on fuzzy neural network (Fuzzy-BPN), and using the the sequential weighted average operator (Ordered Weighted Averaging operator, OWA) weighted prediction. Therefore, in order to verify the proposed method, the Taiwan stock exchange (Taiwan Stock Exchange Corporation) Taiwan Weighted Stock Index (Taiwan Stock Exchange Capitalization Weighted Stock Index, TAIEX) as experimental forecast target, in order to filter the appropriate variables in the experiment Finally, included in other studies in recent years mode in conjunction with this study, the results showed that the predictive ability of this study further improve.

Keywords: Heterogeneity, residential mortgage loans, foreclosure.

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Authors: Madhukar Nagare, Pankaj Dutta, Amey Kambli

Abstract:

Perishable goods constitute a large portion of retailer inventory and lose value with time due to deterioration and/or obsolescence. Retailers dealing with such goods required considering the factors of short shelf life and the dependency of sales on inventory displayed in determining optimal procurement policy. Many retailers follow the practice of using two bins - primary bin sales fresh items at a list price and secondary bin sales unsold items at a discount price transferred from primary bin on attaining certain age. In this paper, mathematical models are developed for primary bin and for secondary bin that maximizes profit with decision variables of order quantities, optimal review period and optimal selling price at secondary bin. The demand rates in two bins are assumed to be deterministic and dependent on displayed inventory level, price and age but independent of each other. The validity of the model is shown by solving an example and the sensitivity analysis of the model is also reported.

Keywords: Retail Inventory, Perishable Products, Two Bin, Profitable Sales.

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Authors: Viktória Sugár, Attila Talamon, András Horkai, Michihiro Kita

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The dense urban fabric of the Budapest 7th district is known as the former Jewish Quarter. The majority of the historical building stock contains multi-story tenement houses with courtyards, built around the end of the 19^th century. Various rehabilitation and urban planning attempt occurred until today, mostly left unfinished. Present paper collects the past rehabilitation plans, actions and their effect which took place in the former Jewish District of Budapest. The authors aim to assess the boundaries of a complex building stock rehabilitation, by taking into account the monument protection guidelines. As a main focus of the research, structural as well as energetic rehabilitation possibilities are analyzed in case of each building by using Geographic Information System (GIS) methods.

Keywords: Geographic information system, Hungary, Jewish quarter, monument, protection, rehabilitation.

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Authors: Varun Gupta, Ankit Pandey

Abstract:

Crude oil market is an immensely complex and dynamic environment and thus the task of predicting changes in such an environment becomes challenging with regards to its accuracy. A number of approaches have been adopted to take on that challenge and machine learning has been at the core in many of them. There are plenty of examples of algorithms based on machine learning yielding satisfactory results for such type of prediction. In this paper, we have tried to predict crude oil prices using Long Short-Term Memory (LSTM) based recurrent neural networks. We have tried to experiment with different types of models using different epochs, lookbacks and other tuning methods. The results obtained are promising and presented a reasonably accurate prediction for the price of crude oil in near future.

Keywords: Crude oil price prediction, deep learning, LSTM, recurrent neural networks.

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Authors: T. Kamalakis, I. Neokosmidis, D. Varoutas, T. Sphicopoulos

Abstract:

The photonic component industry is a highly innovative industry with a large value chain. In order to ensure the growth of the industry much effort must be devoted to road mapping activities. In such activities demand and price evolution forecasting tools can prove quite useful in order to help in the roadmap refinement and update process. This paper attempts to provide useful guidelines in roadmapping of optical components and considers two models based on diffusion theory and the extended learning curve for demand and price evolution forecasting.

Keywords: Roadmapping, Photonic Components, Forecasting, Diffusion Theory.

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Authors: R. A. Sabir , X. Xinping , S.A. Sabr

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This paper has presented research in progress concerning the contribution of target costing approach to achievement competitive price in the Iraqi firm. The title of the paper is one of the subjects that get large concerns in the finance and business world in the present time. That is because many competitive firms have appeared in the regional and global markets and the rapid changes that covered all fields of life. On the other hand, this paper concentrated on lack knowledge of the industrial firms, regarding the significant role of target cost for achieving the competitive prices. The paper depends on the main supposition, using the competitive price to get the target cost in the industrial firms. In order to achieve competitive advantage in business world the firms should rely on modern methods to manage cost and profit. From strategic perspective the target cost achieves a so powerful competitive advantage represented in cost reduction. Nevertheless the target cost does not exclude the calculation and survey of costs during the production process. Products- estimated costs are calculated and compared with the target costs.

Keywords: Target Costing, Competitive Price, Target Profit, Iraq Kurdistan Region.

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Authors: Siddhant Sahu, P. James Daniel Paul

Abstract:

Technical analysis comprised by various technical indicators is a holistic way of representing price movement of stocks in the market. Various forms of indicators have evolved from the primitive ones in the past decades. There have been many attempts to introduce volume as a major determinant to determine strong patterns in market forecasting. The law of demand defines the relationship between the volume and price. Most of the traders are familiar with the volume game. Including the time dimension to the law of demand provides a different visualization to the theory. While attempting the same, it was found that there are different thresholds in the market for different companies. These thresholds have a significant influence on the price. This article is an attempt in determining the thresholds for companies using the three dimensional graphs for optimizing the portfolios. It also emphasizes on the magnitude of importance of volumes as a key factor for determining of predicting strong price movements, bullish and bearish markets. It uses a comprehensive data set of major companies which form a major chunk of the Indian automotive sector and are thus used as an illustration.

Keywords: Technical Analysis, Expert System, Law of demand, Stocks, Portfolio Analysis, Indian Automotive Sector.

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Authors: Viktória Sugár, Zoltán Laczó, András Horkai, Gyula Kiss, Attila Talamon

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The majority of the building stock of Budapest inner districts was built around the turn of the 19^th and 20^th century. Although the structural stability of the buildings is not questioned, as the load bearing structures are in sufficient state, the secondary structures are aged, resulting unsatisfactory energetic state. The renovation of these historical buildings requires special methodology and technology: their ornamented facades and custom-made fenestration cannot be insulated or exchanged with conventional solutions without damaging the heritage values. The present paper aims to introduce and systematize the possible technological solutions for heritage respecting energy retrofit in case of a historical residential building stock. Through case study, the possible energy saving potential is also calculated using multiple renovation scenarios.

Keywords: Energy efficiency, heritage, historical building, renovation, technical solutions.

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Authors: Piotr Prewysz-Kwinto

Abstract:

The market of financial instruments with high risk is developing very dynamically in recent years and attracts more and more interest of investors. It consists essentially of two groups of instruments, i.e. derivatives and exchange traded product (ETP), and each year new types are introduced and offered to investors. The aim of this paper is to present the principles concerning financial instruments with high investment risk available on the Warsaw Stock Exchange (WSE), because they have quite complex constructions, and to evaluate the development of this market. In order to achieve this aim, statistical data from 2014-2016 was analyzed. The results confirm that the financial instruments with high investment risk available on the WSE constitute a diversified and the most numerous group of financial instruments and attract the most interest of investors. Responsible investing requires, however, a good knowledge of how they work and how they can generate profit to not expose oneself to unexpected losses.

Keywords: Derivatives, exchange traded products, financial instruments, financial market, risk, stock exchange.

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Authors: Ling Shi Cai, Leau Yu Beng, Charlie Albert Lasuin, Tan Soo Fun, Chin Pei Yee

Abstract:

This paper explains the development of Multifunctional Barcode Inventory Management System (MBIMS) to manage inventory and stock ordering. Today, most of the retailing market is still manually record their stocks and its effectiveness is quite low. By providing MBIMS, it will bring effectiveness to retailing market in inventory management. MBIMS will not only save time in recording input, output and refilling the inventory stock, but also in calculating remaining stock and provide auto-ordering function. This system is developed through System Development Life Cycle (SDLC) and the flow and structure of the system is fully built based on requirements of a retailing market. Furthermore, this system has been developed from methodical research and study where each part of the system is vigilantly designed. Thus, MBIMS will offer a good solution to the retailing market in achieving effectiveness and efficiency in inventory management.

Keywords: Inventory, Retailing Market, Barcode, Automated Alerting and Ordering

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Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

Abstract:

In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: Fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange.

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Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model, where document topics are extracted using LDA. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: Regression model, social mood, stock market prediction, Twitter.

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Authors: Mohammad Hadi Zohdi, Mohamad Reza Dalvand, Maryam Zohdi

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In this research relationship between to be smooth the interest and output of accepted companies stock at negotiable paper exchange of Tehran is studied. Static community capacity included 363 companies member of negotiable paper exchange of Tehran that 54 companies were, by considering research limitation, selected from 2004 to 2009. Needed data for model test in librarian method was chosen from RAH AVARDE NOVIN informative banks, TADBIR and collecting needed data was selected from Tehran negotiable paper exchange archive. Given results show that in spite of belief among people based on companies have more smooth interest have more output, but resulted outcomes of test-done reveals that there is no relation between smooth interest and stock output.

Keywords: Smooth interest, interest fluctuation, interest level, output average, cost capital

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Authors: Alhaji M. H. Conteh, Xiangbin Yan, Alfred V. Gborie

Abstract:

The goal of this study was to increase the awareness of the description and assessments of rice acreage response and to offer mechanisms for agricultural policy scrutiny. The ordinary least square (OLS) technique was utilized to determine the coefficients of acreage response models for the rice varieties. The magnitudes of the coefficients (λ) of both the ROK lagged and NERICA lagged acreages were found positive and highly significant, which indicates that farmers’ adjustment rate was very low. Regarding lagged actual price for both the ROK and NERICE rice varieties, the short-run price elasticitieswere lower than long-run, which is suggesting a long term adjustment of the acreage under the crop.

However, the apparent recommendations for policy transformation are to open farm gate prices and to decrease government’s involvement in agricultural sector especially in the acquisition of agricultural inputs. Impending research have to be centered on how this might be better realized. Necessary conditions should be made available to the private sector by means of minimizing price volatility. In accordance with structural reforms, it is necessary to convey output prices to farmers with minimum distortion. There is need to eradicate price subsidies and control, which generate distortion in the market in addition to huge financial costs.

Keywords: Acreage response, rate of adjustment, rice varieties, Sierra Leone.

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Authors: GuentherSchuh, Till Potente, SaschaFuchs, Annika Hauptvogel, Tobias Welter

Abstract:

Producing companies aspire to high delivery availability despite appearing disruptions. To ensure high delivery availability safety stocksare required. Howeversafety stock leads to additional capital commitment and compensates disruptions instead of solving the reasons.The intention is to increase the stability in production by configuring the production planning and control systematically. Thus the safety stock can be reduced. The largest proportion of inventory in producing companies is caused by batch inventory, schedule deviations and variability of demand rates.These reasons for high inventory levels can be reduced by configuring the production planning and control specifically. Hence the inventory level can be reduced. This is enabled by synchronizing the lot size straightening the demand as well as optimizing the releasing order, sequencing and capacity control.

Keywords: inventory level, inventory management, production planning and control, safety stock

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Authors: C. Slim

Abstract:

Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: Stationarity, unit root tests, economic time series.

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Authors: W. A. Pamungkas, R. B. Setyawati, A. F. Rifai, C. P. Setiawan, A. W. Budiman, Inayati, J. Waluyo, S. H. Pranolo

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The increase in LPG consumption in Indonesia is not balanced with the amount of supply. The high demand for LPG due to the success of the government's kerosene-to-LPG conversion program and the COVID-19 pandemic in 2020 led to an increase in LPG consumption in the household sector and caused Indonesia's trade balance to experience a deficit. The high consumption of LPG encourages the need for alternative fuels which aims to substitute LPG. Dimethyl Ether (DME) is an organic compound with the chemical formula CH3OCH3, has a high cetane number and has characteristics similar to LPG. DME can be produced from various sources such as coal, biomass and natural gas. Based on the economic analysis conducted at 10% Internal Rate of Return (IRR), coal has the largest Net Present Value (NPV) of Rp. 20,034,837,497,241 with a payback period of 3.86 years, then biomass with an NPV of Rp. 10,401,526,072,850 and payback period of 5.16. The latter is natural gas with an NPV of IDR 7,401,272,559,191 and a payback period of 6.17 years. Of the three sources of raw materials used, if the sensitivity is calculated using the selling price of DME equal to the selling price of LPG, it will get an NPV value that is greater than the NPV value when using the current DME price. The advantages of coal as a raw material for DME are profitableness, low price and abundant resources, but it has high greenhouse gas emission.

Keywords: LPG, DME, coal, biomass, natural gas.

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Authors: Chava Sunil Kumar, P.S. Subrahmanyan, J. Amarnath

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In this paper variation of spot price and total profits of the generating companies- through wholesale electricity trading are discussed with and without Central Generating Stations (CGS) share and seasonal variations are also considered. It demonstrates how proper analysis of generators- efficiencies and capabilities, types of generators owned, fuel costs, transmission losses and settling price variation using the solutions of Optimal Power Flow (OPF), can allow companies to maximize overall revenue. It illustrates how solutions of OPF can be used to maximize companies- revenue under different scenarios. And is also extended to computation of Available Transfer Capability (ATC) is very important to the transmission system security and market forecasting. From these results it is observed that how crucial it is for companies to plan their daily operations and is certainly useful in an online environment of deregulated power system. In this paper above tasks are demonstrated on 124 bus real-life Indian utility power system of Andhra Pradesh State Grid and results have been presented and analyzed.

Keywords: OPF, ATC, Electricity Market, Bid, Spot Price

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Authors: Amina Amirat, Abdelfettah Bouri

Abstract:

If price and quantity are the fundamental building blocks of any theory of market interactions, the importance of trading volume in understanding the behavior of financial markets is clear. However, while many economic models of financial markets have been developed to explain the behavior of prices -predictability, variability, and information content- far less attention has been devoted to explaining the behavior of trading volume. In this article, we hope to expand our understanding of trading volume by developing a new measure of herding behavior based on a cross sectional dispersion of volumes betas. We apply our measure to the Toronto stock exchange using monthly data from January 2000 to December 2002. Our findings show that the herd phenomenon consists of three essential components: stationary herding, intentional herding and the feedback herding.

Keywords: Herding behavior, market return, trading volume.

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: Big data, building-value analysis, machine learning, price prediction.

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Authors: Hamed Sabahno

Abstract:

In this paper, an inventory model with finite and constant replenishment rate, price dependant demand rate, time value of money and inflation, finite time horizon, lead time and exponential deterioration rate and with the objective of maximizing the present worth of the total system profit is developed. Using a dynamic programming based solution algorithm, the optimal sequence of the cycles can be found and also different optimal selling prices, optimal order quantities and optimal maximum inventories can be obtained for the cycles with unequal lengths, which have never been done before for this model. Also, a numerical example is used to show accuracy of the solution procedure.

Keywords: Deteriorating items, Dynamic programming, Finitereplenishment rate, Inventory control, Operation Research.

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Authors: S. Homrossukon, D. Aromstain

Abstract:

The simple methods used to plan and measure non patterned production system are developed from the basic definition of working efficiency. Processing time is assigned as the variable and used to write the equation of production efficiency. Consequently, such equation is extensively used to develop the planning method for production of interest using one-dimensional stock cutting problem. The application of the developed method shows that production efficiency and production planning can be determined effectively.

Keywords: Production Planning, Parallel Machine, Production Measurement, Cutting and Packing.

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: Deregulated energy market, forecasting, machine learning, system marginal price, energy efficiency and quality.

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Authors: Gulsevim Yumuk Gunay, Suleyman Gokhan Gunay

Abstract:

Corporate social responsibility (CSR) can be defined as the management of social, environmental, economical and ethical concepts and firms sensivities to the expectations of the social stakeholders. CSR is seen as an important competitive advantage in the textile sector because this sector has an important impact on the environment and it is labor extensive. Textile sector has a strong advantage when compared with other sectors in Turkey due to its low labor costs and abundancy of raw materials. Turkey was a producer and an exporter of cotton, and an importer of fiber, clothes and dresses until 1950s. After 1950s, Turkey has begun to export fiber, ready-made clothes and become one of the most important textile producers in the world recently. CSR practices of the textile firms that are quoted in Istanbul Stock Exchange and these firms sensivities to their internal and external stakeholders and environment will be presented in this study.

Keywords: corporate social responsibility, Istanbul Stock Exchange, textile sector, Turkey

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Authors: Yi-Chang Chen, Shan-Lin Chang, Chia-Chun Wu

Abstract:

Unlike this study focused extensively on trading behavior of option market, those researches were just taken their attention to model-driven option pricing. For example, Black-Scholes (B-S) model is one of the most famous option pricing models. However, the arguments of B-S model are previously mentioned by some pricing models reviewing. This paper following suggests the importance of the dynamic character for option pricing, which is also the reason why using the genetic algorithm (GA). Because of its natural selection and species evolution, this study proposed a hybrid model, the Genetic-BS model which combining GA and B-S to estimate the price more accurate. As for the final experiments, the result shows that the output estimated price with lower MAE value than the calculated price by either B-S model or its enhanced one, Gram-Charlier garch (G-C garch) model. Finally, this work would conclude that the Genetic-BS pricing model is exactly practical.

Keywords: genetic algorithm, Genetic-BS, option pricing model.

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Authors: Yousef Abu Nahleh, Alhasan Hakami, Arun Kumar, Fugen Daver

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This study considers the problem of calculating safety stocks in disaster situations inventory systems that face demand uncertainties. Safety stocks are essential to make the supply chain, which is controlled by forecasts of customer needs, in response to demand uncertainties and to reach predefined goal service levels. To solve the problem of uncertainties due to the disaster situations affecting the industry sector, the concept of Emergency Safety Stock (ESS) was proposed. While there exists a huge body of literature on determining safety stock levels, this literature does not address the problem arising due to the disaster and dealing with the situations. In this paper, the problem of improving the Order Quantity Model to deal with uncertainty of demand due to disasters is managed by incorporating a new idea called ESS which is based on the probability of disaster occurrence and uses probability matrix calculated from the historical data. 

Keywords: Emergency Safety Stocks, Safety stocks, Order Quantity Model, Supply chain.

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Authors: Shih-Ching Lo, Yu-Ping Liao

Abstract:

Social-economic variables influence transportation demand largely. Analyses of discrete choice model consider social-economic variables to study traveler-s mode choice and demand. However, to calibrate the discrete choice model needs to have plenty of questionnaire survey. Also, an aggregative model is proposed. The historical data of passenger volumes for high speed rail and domestic civil aviation are employed to calibrate and validate the model. In this study, models with different social-economic variables, which are oil price, GDP per capita, CPI and economic growth rate, are compared. From the results, the model with the oil price is better than models with the other social-economic variables.

Keywords: forecasting, passenger volume, dynamic competitive model, social-economic variables, oil price.

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Authors: E. Pop, M. Barbos

Abstract:

Using mobile Internet access technologies and eservices, various economic agents can efficiently offer their products or services to a large number of clients. With the support of mobile communications networks, the clients can have access to e-services, anywhere and anytime. This is a base to establish a convergence of technological and financial interests of mobile operators, software developers, mobile terminals producers and e-content providers. In this paper, a client server system is presented, using 3G, EDGE, mobile terminals, for Stock Exchange e-services access.

Keywords: Mobile communications, e-services access, stockexchange.

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