Search results for: stocks market

Authors: Sang Hoon Kang, Seong-Min Yoon

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Little attention has been paid to information transmission between the portfolios of large stocks and small stocks in the Korean stock market. This study investigates the return and volatility transmission mechanisms between large and small stocks in the Korea Exchange (KRX). This study also explores whether bad news in the large stock market leads to a volatility of the small stock market that is larger than the good news volatility of the large stock market. By employing the Granger causality test, we found unidirectional return transmissions from the large stocks to medium and small stocks. This evidence indicates that pat information about the large stocks has a better ability to predict the returns of the medium and small stocks in the Korean stock market. Moreover, by using the asymmetric GARCH-BEKK model, we observed the unidirectional relationship of asymmetric volatility transmission from large stocks to the medium and small stocks. This finding suggests that volatility in the medium and small stocks following a negative shock in the large stocks is larger than that following a positive shock in the large stocks.

Keywords: Asymmetric GARCH-BEKK model, Asymmetric volatility transmission, Causality, Korean stock market, Spillover effect

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Authors: Chih-Hsiang Chang, Fang-Jyun Su

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This paper explores whether stock characteristics influence the herding formation among investors in the US equity market. To extend the research scope of the existing literature, this paper further examines the role that stock risk characteristics play in the US equity market, and the way they influence investors’ decision-making. First, empirical results show that whether general stocks or high-risk stocks, there are no herding behaviors among the investors in the US equity market during the whole research period or during four great events. Moreover, stock characteristics have great influence on investors’ trading decisions. Finally, there is a bidirectional lead-lag relationship of the herding formation between high-risk stocks and low-risk stocks, but the influence of high-risk stocks on the low-risk stocks is stronger than that of low-risk stocks on the high-risk stocks.

Keywords: Stock characteristics, herding formation, investment decision, US equity market, lead-lag relationship.

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Authors: Zahra Hatami, Hesham Ali, David Volkman

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Selecting a portfolio for investing is a crucial decision for individuals and legal entities. In the last two decades, with economic globalization, a stream of financial innovations has rushed to the aid of financial institutions. The importance of selecting stocks for the portfolio is always a challenging task for investors. This study aims to create a financial network to identify optimal portfolios using network centralities metrics. This research presents a community detection technique of superior stocks that can be described as an optimal stock portfolio to be used by investors. By using the advantages of a network and its property in extracted communities, a group of stocks was selected for each of the various time periods. The performance of the optimal portfolios was compared to the famous index. Their Sharpe ratio was calculated in a timely manner to evaluate their profit for making decisions. The analysis shows that the selected potential portfolio from stocks with low centrality measurement can outperform the market; however, they have a lower Sharpe ratio than stocks with high centrality scores. In other words, stocks with low centralities could outperform the S&P500 yet have a lower Sharpe ratio than high central stocks.

Keywords: Portfolio management performance, network analysis, centrality measurements, Sharpe ratio.

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Authors: Changju Lee, Seungmo Ku, Sondo Kim, Woojin Chang

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How to detecting financial bubble? Addressing this simple question has been the focus of a vast amount of empirical research spanning almost half a century. However, financial bubble is hard to observe and varying over the time; there needs to be more research on this area. In this paper, we used abnormal difference between common stocks price and those preferred stocks price to explain financial bubble. First, we proposed the ‘W-index’ which indicates spread between common stocks and those preferred stocks in stock market. Second, to prove that this ‘W-index’ is valid for measuring financial bubble, we showed that there is an inverse relationship between this ‘W-index’ and S&P500 rate of return. Specifically, our hypothesis is that when ‘W-index’ is comparably higher than other periods, financial bubbles are added up in stock market and vice versa; according to our hypothesis, if investors made long term investments when ‘W-index’ is high, they would have negative rate of return; however, if investors made long term investments when ‘W-index’ is low, they would have positive rate of return. By comparing correlation values and adjusted R-squared values of between W-index and S&P500 return, VIX index and S&P500 return, and TED index and S&P500 return, we showed only W-index has significant relationship between S&P500 rate of return. In addition, we figured out how long investors should hold their investment position regard the effect of financial bubble. Using this W-index, investors could measure financial bubble in the market and invest with low risk.

Keywords: Financial bubbles, detection, preferred stocks, pairs trading, future return, forecast.

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: Machine learning, stock market trading, logistic principal component analysis, automated stock investment system.

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Authors: Siddhant Sahu, P. James Daniel Paul

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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: Brownhilder N. Neneh, A. Van Aardt Smit

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Underpricing is one anomaly in initial public offerings (IPO) literature that has been widely observed across different stock markets with different trends emerging over different time periods. This study seeks to determine how IPOs on the JSE performed on the first day, first week and first month over the period of 1996-2011. Underpricing trends are documented for both hot and cold market periods in terms of four main sectors (cyclical, defensive, growth stock and interest rate sensitive stocks). Using a sample of 360 listed companies on the JSE, the empirical findings established that IPOs on the JSE are significantly underpriced with an average market adjusted first day return of 62.9%. It is also established that hot market IPOs on the JSE are more underpriced than the cold market IPOs. Also observed is the fact that as the offer price per share increases above the median price for any given period, the level of underpricing decreases substantially. While significant differences exist in the level of underpricing of IPOs in the four different sectors in the hot and cold market periods, interest rates sensitive stocks showed a different trend from the other sectors and thus require further investigation to uncover this pattern.

Keywords: Underpricing, hot and cold markets, South Africa, JSE.

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Authors: S. Al Wadi, Mohd Tahir Ismail, Samsul Ariffin Abdul Karim

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It is well known that during the developments in the economic sector and through the financial crises occur everywhere in the whole world, volatility measurement is the most important concept in financial time series. Therefore in this paper we discuss the volatility for Amman stocks market (Jordan) for certain period of time. Since wavelet transform is one of the most famous filtering methods and grows up very quickly in the last decade, we compare this method with the traditional technique, Fast Fourier transform to decide the best method for analyzing the volatility. The comparison will be done on some of the statistical properties by using Matlab program.

Keywords: Fast Fourier transforms, Haar wavelet transform, Matlab (Wavelet tools), stocks market, Volatility.

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Authors: J. Arneric, A. Rozga

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In this paper usefulness of quasi-Newton iteration procedure in parameters estimation of the conditional variance equation within BHHH algorithm is presented. Analytical solution of maximization of the likelihood function using first and second derivatives is too complex when the variance is time-varying. The advantage of BHHH algorithm in comparison to the other optimization algorithms is that requires no third derivatives with assured convergence. To simplify optimization procedure BHHH algorithm uses the approximation of the matrix of second derivatives according to information identity. However, parameters estimation in a/symmetric GARCH(1,1) model assuming normal distribution of returns is not that simple, i.e. it is difficult to solve it analytically. Maximum of the likelihood function can be founded by iteration procedure until no further increase can be found. Because the solutions of the numerical optimization are very sensitive to the initial values, GARCH(1,1) model starting parameters are defined. The number of iterations can be reduced using starting values close to the global maximum. Optimization procedure will be illustrated in framework of modeling volatility on daily basis of the most liquid stocks on Croatian capital market: Podravka stocks (food industry), Petrokemija stocks (fertilizer industry) and Ericsson Nikola Tesla stocks (information-s-communications industry).

Keywords: Heteroscedasticity, Log-likelihood Maximization, Quasi-Newton iteration procedure, Volatility.

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

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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: Ioan Popa, Radu Lupu, Cristiana Tudor

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In this paper, we apply the FM methodology to the cross-section of Romanian-listed common stocks and investigate the explanatory power of market beta on the cross-section of commons stock returns from Bucharest Stock Exchange. Various assumptions are empirically tested, such us linearity, market efficiency, the “no systematic effect of non-beta risk" hypothesis or the positive expected risk-return trade-off hypothesis. We find that the Romanian stock market shows the same properties as the other emerging markets in terms of efficiency and significance of the linear riskreturn models. Our analysis included weekly returns from January 2002 until May 2010 and the portfolio formation, estimation and testing was performed in a rolling manner using 51 observations (one year) for each stage of the analysis.

Keywords: Bucharest Stock Exchange, Fama-Macbeth methodology, systematic risk, non-linear risk-return dependence.

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Authors: Azwadi Ali

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The survival of publicly listed companies largely depends on their stocks being liquidly traded. This goal can be achieved when new investors are attracted to invest on companies- stocks. Among different groups of investors, individual investors are generally less able to objectively evaluate companies- risks and returns, and tend to be emotionally biased in their investing decisions. Therefore their decisions may be formed as a result of perceived risks and returns, and influenced by companies- images. This study finds that perceived risk, perceived returns and trust directly affect individual investors- trading decisions while attitude towards brand partially mediates the relationships. This finding suggests that, in courting individual investors, companies still need to perform financially while building a good image can result in their stocks being accepted quicker than the stocks of good performing companies with hidden images.

Keywords: Behavioral Finance, Investment, Attitude towardsBrand, Partial Least Squares

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Authors: Rohit Choudhry, Kumkum Garg

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In this paper, we propose a hybrid machine learning system based on Genetic Algorithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators of highly correlated stocks, not only the stock to be predicted. The genetic algorithm is used to select the set of most informative input features from among all the technical indicators. The results show that the hybrid GA-SVM system outperforms the stand alone SVM system.

Keywords: Genetic Algorithms, Support Vector Machines, Stock Market Forecasting.

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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: P. Sankar, P. James Daniel Paul, Siddhant Sahu

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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian Automotive Sector, Stock Market Decisions, Equity Portfolio Analysis, Decision Tree Classifiers, Statistical Data Analysis.

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Authors: Chih-Hsiang Chang

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This study aims to explore the relationship between the disposition effect and herding behavior of investors trading Taiwanese information technology stocks. This study differs from previous literature in two aspects. First, in contrast with the earlier studies that focused on investigating investors’ herding behavior, this study explores the possibility that the disposition effect drives investors’ herding behavior. Additionally, it takes an in-depth look at the interdependence between the disposition effect and herding behavior of investors, including lead-lag relationship and volatility transmission effect. Empirical results show that investors trading Taiwan’s information technology stocks exhibit pronounced herding behavior and that the disposition effect has a great impact on their herding behavior.

Keywords: Herding behavior, Disposition effect, Behavioral finance.

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Authors: Bello Nurudeen Akinsola

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The study analyzed the risk and returns of commercial-property in Southwestern Nigeria and selected stocksmarket investment between 2000 and 2009; compared the inflation hedging characteristics and diversification potentials of investing in commercial-property and selected stock- market investment. Primary data were collected on characteristics, rental and capital values of commercial- properties from their property managers through the use of questionnaire. Secondary data on stock prices and dividends on banking, insurance and conglomerates sectors were sourced from the Nigerian Stock Exchange (2000-2009). The result showed that average return on all the selected stock- investments was higher than that of commercial-property. As regards risk, commercial-property indicated lower risk, compared to stocks. Also the stock-investment had better inflation hedging capacity than commercial-properties; combination of both had diversification potentials. The study concluded that stock-market investment offered attractive higher return than commercial-property although with higher risk and there could be diversification benefits in combining commercial-property with stock- investment.

Keywords: Commercial-Property, Return, Risk, Stock Market

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Authors: N. Behidj-Benyounes, S. Bennaamane, F. Zohra Bissaad, N. Chebouti, H. Mohandkaci, N. Abdalaziz, S. Iddou

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In this study, we are interested in a species of the family of Asteraceae (Tagetes erecta). This family is considered as a source of antimicrobial extracts with strong capacity. The extraction of the flavonoids is carried out by the method of liquid/liquid with the use of successive solvents. Afterwards, we evaluated the biological activity of the flavonoids on five pathogenic bacterial stocks such as Escherichia coli, Bacillus subtilis, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus and two stocks of yeasts to knowing Candida albicans) and Saccharomyces cerevisiae, by employing the method of the aromatogramme starting from a solid disc. The result of the antimicrobial activity shows an action and a variable degree of sensitivity according to bacterial stocks tested. It will be noted that the flavonoids have an inhibiting effect on E. coli, B. subtilis, K. pneumoniae and S. aureus. But a resistance with respect to the extract by P. aeruginosa, C. albicans and S. cerevisiae is to be mentioned.

Keywords: Antimicrobial activity, flavonoids, microbial strains, Tagetes erecta L.

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Authors: Mojtaba Rezaei, Elham Heydari

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This paper highlights the empirical results of analyzing the correlation between accounting information and systematic risk. This association is analyzed among financial ratios and systematic risk by considering the financial statement of 39 companies listed on the Tehran Stock Exchange (TSE) for five years (2014-2018). Financial ratios have been categorized into four groups and to describe the special features, as representative of accounting information we selected: Return on Asset (ROA), Debt Ratio (Total Debt to Total Asset), Current Ratio (current assets to current debt), Asset Turnover (Net sales to Total assets), and Total Assets. The hypotheses were tested through simple and multiple linear regression and T-student test. The findings illustrate that there is no significant relationship between accounting information and market risk. This indicates that in the selected sample, historical accounting information does not fully reflect the price of stocks.

Keywords: Accounting information, market risk, systematic risk, efficient market hypothesis, EMH, Tehran Stock Exchange, TSE.

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Authors: A.R. Yari, M.R. Sadri

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For the first incumbent operator it is very important to understand how to react when the second operator comes to the market. In this paper which is prepared for preliminary study of GSM market in Iran, we have studied five MENA markets according to the similarity point of view. This paper aims at analyzing the impact of second entrants in selected markets on certain marketing key performance indicators (KPI) such as: Market shares (by operator), prepaid share, minutes of use (MoU), Price and average revenue per user (ARPU) (for total market each).

Keywords: GSM Market, Second entrant, MENA.

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Authors: Zahra Amirhosseini, Alireza Bashiri

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The aim of this study was to examine and identify the type of Iranian financial market in terms of being symmetrical or asymmetrical and to measure relationship between type of market and the market's indices. In this study, daily information on the market-s Share Price Index, Industrial Index and Top Fifty Most Active Companies during the years 1999-2010 has been used. In addition, to determine type of the financial market, rate of return on Security is taken into account. In this research, by using logistic regression analysis methods, relationship of the market type with the above mentioned indices have been examined. The results showed that the type of the financial market has a positive significant association with market share price index and Industrial Index. Index of Top Fifty Most Active Companies is significantly associated with type of financial market, however this relationship is inverse.

Keywords: All Share Price Index, Asymmetrical Market, Industrial Index, Symmetrical Market, Top Fifty Most Active Companies Index

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Authors: Satjaporn Tungsong, Gun Srijuntongsiri

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This research seeks to investigate the frequency and profitability of index arbitrage opportunities involving the SET50 futures, SET50 component stocks, and the ThaiDEX SET50 ETF (ticker symbol: TDEX). In particular, the frequency and profit of arbitrage are measured in the following three arbitrage tests: (1) SET50 futures vs. ThaiDEX SET50 ETF, (2) SET50 futures vs. SET50 component stocks, and (3) ThaiDEX SET50 ETF vs. SET50 component stocks are investigated. For tests (2) and (3), the problems involve conic optimization and quadratic programming as subproblems. This research is first to apply conic optimization and quadratic programming techniques in the context of index arbitrage and is first to investigate such index arbitrage in the Thai equity and derivatives markets. Thus, the contribution of this study is twofold. First, its results would help understand the contribution of the derivatives securities to the efficiency of the Thai markets. Second, the methodology employed in this study can be applied to other geographical markets, with minor adjustments.

Keywords: Conic optimization, Equity index arbitrage, Executionlags, Quadratic programming, SET50 index futures, ThaiDEX SET50ETF, Transaction costs

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Authors: Honorata Howaniec

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Brand loyalty is a strategic asset of the company. In the era of competition to have loyal customers decides on the market superiority of enterprises. Creating the loyalty of buyers, however, is a lengthy process and requires the appropriate business strategy, preceded by the proper market research. The purpose of the paper is to present the concept of brand loyalty, the creation of loyalty of customers, the benefits and determinants of loyalty on the example of brewery market in Poland.

Keywords: brand, brand loyalty, brewery market

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Authors: Noor Azryani Auzairy, Rubi Ahmad

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To strengthen the capital market, there is a need to integrate the capital markets within the region by removing legal or informal restriction, specifically, stock market liberalization. Thus the paper is to investigate the effects of the subsequent stock market liberalization on stock market integration in 4 ASEAN countries (Malaysia, Indonesia, Thailand, Singapore) and Korea from 1997 to 2007. The correlation between stock market liberalization and stock market integration are to be examined by analyzing the stock prices and returns within the region and in comparison with the world MSCI index. Event study method is to be used with windows of ±12 months and T-7 + T. The results show that the subsequent stock market liberalization generally, gives minor positive effects to stock returns, except for one or two countries. The subsequent liberalization also integrates the markets short-run and long-run.

Keywords: ASEAN, event method, stock market integration, stock market liberalization.

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Authors: B. K. Yeoh, Z. Arsad, C. W. Hooy

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This paper tests the level of market integration between Malaysia and Singapore stock markets with the world market. Kalman Filter (KF) methodology is used on the International Capital Asset Pricing Model (ICAPM) and the pricing errors estimated within the framework of ICAPM are used as a measure of market integration or segmentation. The advantage of the KF technique is that it allows for time-varying coefficients in estimating ICAPM and hence able to capture the varying degree of market integration. Empirical results show clear evidence of varying degree of market integration for both case of Malaysia and Singapore. Furthermore, the results show that the changes in the level of market integration are found to coincide with certain economic events that have taken placed. The findings certainly provide evidence on the practicability of the KF technique to estimate stock markets integration. In the comparison between Malaysia and Singapore stock market, the result shows that the trends of the market integration indices for Malaysia and Singapore look similar through time but the magnitude is notably different with the Malaysia stock market showing greater degree of market integration. Finally, significant evidence of varying degree of market integration shows the inappropriate use of OLS in estimating the level of market integration.

Keywords: ICAPM, Kalman filter, stock market integration.

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Authors: Ehigiamusoe, Uyi Kizito

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The paper examines the impact of money market on economic growth in Nigeria using data for the period 1980-2012. Econometrics techniques such as Ordinary Least Squares Method, Johanson’s Co-integration Test and Vector Error Correction Model were used to examine both the long-run and short-run relationship. Evidence from the study suggest that though a long-run relationship exists between money market and economic growth, but the present state of the Nigerian money market is significantly and negatively related to economic growth. The link between the money market and the real sector of the economy remains very weak. This implies that the market is not yet developed enough to produce the needed growth that will propel the Nigerian economy because of several challenges. It was therefore recommended that government should create the appropriate macroeconomic policies, legal framework and sustain the present reforms with a view to developing the market so as to promote productive activities, investments, and ultimately economic growth.

Keywords: Economic Growth, Investments, Money Market, Money Market Challenges, Money Market Instruments.

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Authors: A. Badri

Abstract:

Restructured electricity markets may provide opportunities for producers to exercise market power maintaining prices in excess of competitive levels. In this paper an oligopolistic market is presented that all Generation Companies (GenCos) bid in a Cournot model. Genetic algorithm (GA) is applied to obtain generation scheduling of each GenCo as well as hourly market clearing prices (MCP). In order to consider network constraints a multiperiod framework is presented to simulate market clearing mechanism in which the behaviors of market participants are modelled through piecewise block curves. A mixed integer linear programming (MILP) is employed to solve the problem. Impacts of market clearing process on participants- characteristic and final market prices are presented. Consequently, a novel multi-objective model is addressed for security constrained optimal bidding strategy of GenCos. The capability of price-maker GenCos to alter MCP is evaluated through introducing an effective-supply curve. In addition, the impact of exercising market power on the variation of market characteristics as well as GenCos scheduling is studied.

Keywords: Optimal bidding strategy, Cournot equilibrium, market power, network constraints, market auction mechanism

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Authors: Alexander Efremov

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A system for market identification (SMI) is presented. The resulting representations are multivariable dynamic demand models. The market specifics are analyzed. Appropriate models and identification techniques are chosen. Multivariate static and dynamic models are used to represent the market behavior. The steps of the first stage of SMI, named data preprocessing, are mentioned. Next, the second stage, which is the model estimation, is considered in more details. Stepwise linear regression (SWR) is used to determine the significant cross-effects and the orders of the model polynomials. The estimates of the model parameters are obtained by a numerically stable estimator. Real market data is used to analyze SMI performance. The main conclusion is related to the applicability of multivariate dynamic models for representation of market systems.

Keywords: market identification, dynamic models, stepwise regression.

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Authors: Susmita Ghosh, Bhaskar Bhowmick

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Market is an important factor for start-ups to look into during decision-making in product development and related areas. Emerging country markets are more uncertain in terms of information availability and institutional supports. The literature review of market uncertainty reveals the need for identifying factors representing the market uncertainty. This paper identifies factors for market uncertainty using Exploratory Factor Analysis (EFA) and confirmed the number of factor retention using an alternative factor retention criterion ‘Parallel Analysis’. 500 entrepreneurs, engaged in start-ups from all over India participated in the study. This paper concludes with the factor structure of ‘market uncertainty’ having dimensions of uncertainty in industry orientation, uncertainty in customer orientation and uncertainty in marketing orientation.

Keywords: Uncertainty, market, orientation, competitor, demand.

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Authors: H. Zarei, M. H. Fazel Zarandi, M. Karbasian

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A Decision Support System/Expert System for stock portfolio selection presented where at first step, both technical and fundamental data used to estimate technical and fundamental return and risk (1st phase); Then, the estimated values are aggregated with the investor preferences (2nd phase) to produce convenient stock portfolio. In the 1st phase, there are two expert systems, each of which is responsible for technical or fundamental estimation. In the technical expert system, for each stock, twenty seven candidates are identified and with using rough sets-based clustering method (RC) the effective variables have been selected. Next, for each stock two fuzzy rulebases are developed with fuzzy C-Mean method and Takai-Sugeno- Kang (TSK) approach; one for return estimation and the other for risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation method. In parallel, for fundamental expert systems, fuzzy rule-bases have been identified in the form of “IF-THEN" rules through brainstorming with the stock market experts and the input data have been derived from financial statements; as a result two fuzzy rule-bases have been generated for all the stocks, one for return and the other for risk. In the 2nd phase, user preferences represented by four criteria and are obtained by questionnaire. Using an expert system, four estimated values of return and risk have been aggregated with the respective values of user preference. At last, a fuzzy rule base having four rules, treats these values and produce a ranking score for each stock which will lead to a satisfactory portfolio for the user. The stocks of six manufacturing companies and the period of 2003-2006 selected for data gathering.

Keywords: Stock Portfolio Selection, Fuzzy Rule-Base ExpertSystems, Financial Decision Support Systems, Technical Analysis, Fundamental Analysis.

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