• Journal of Distribution Research
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• v.17 no.5
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• pp.39-57
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• 2012

The unabated influx of micro businesses has turned the Korean retailing market to a rat race, which causes severe financial distress for micro business owners due to heavy competition. The woes of these micro business owner's are exacerbated by the presence of large scale distributors such as Super Supermarket(SSM) and large discount stores. In summary, the Korean retail market is overburdened an uneconomically viable. Retailing has low barriers to entry which attracts unskilled labor or those with little capital. These start-ups have low opportunity costs since they would make low wages elsewhere in the economy. Thus, these owners are content with relatively low returns on their investment. These 'subsistence ventures' are maintained for economical viability rather than economic growth. These 'subsistence ventures' intensifies competition among small-scale businesses. The presence of large retail corporations also aggravates the situation. The recent stagnation of the economy has worsened the retail market in Korea. The overwhelming competition solidifies the coarse structural system and the prolonged economic sluggishness has increased the risk of insolvency for micro business owners. As the economy continues to stagnate, the imminent risk in retailing market will rise up to surface threatening economic stability. More systematic inflows and outflows of retailers are required in order to redress this structural problem. It has been empirically shown that the self-employment rate is high in Korea compared to other OECD countries. To draw the comparison of self-employment rate by industry, Korea shows high rates among transportation, whole sale, retail, education, lodging, and restaurants. In the case of the transportation and education service sectors, this high rate can be explained by the idiosyncratic nature of Korean culture. In the transportation sector, political policies favor private cap service and private freight carriers. In the education service sector, Koreans put particular emphasis on education that leads to many private institutions that outnumber other OECD countries. For these singular reasons, Korea maintains high micro business, self-employed rates particularly in retailing. A comparable nation is Japan, with its similar social, economic, cultural environment among OECD countries. Unlike Korea, Japan has much lower rates of micro business which continues to decrease. Also Korean retailers are much more destitute than Japanese. The fundamental problem of Korean retailing is the involuntary exit of these 'subsistence ventures,' micro businesses with low margins, in which a small drop in demand can lead to financial difficulties for the owner. This problem will be exacerbated when Korean babyboomers retire and join the micro business ventures. The first priority in order to cope with the severity of oversupply in retailing is to provide better opportunities for the potential self-employers. There should be viable alternatives to subsistent ventures. Strengthening the retirement program, scrutiny of exit process, reconfiguration of policy funds are the recommendations.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.5-16
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• 2009

Against the backdrop of the increasing trend towards economic globalisation, many international firms are indicating that decisions on how to enter foreign markets remains one of the key strategic challenges confronting them. Despite the rich body of literature on the topic, the fact that these challenges have continued to dominate global marketing strategy discourses point to someevident lacunae. Accordingly, this paper considers the variables, categorised in terms of firm contexts (standardisation, market research, competition, structure, competitive advantage) and host country-contexts (economic development, cultural differences, regulation and political risk), which influence the degree of involvement of UK companies in overseas markets. Following hypotheses were drawn from literature review: H1: The greater the level of competition, the higher the degree of involvement in the overseas market. H2: The more centralised the firm's organisation structure, the higher the degree of involvement in the overseas market. H3a: The adoption of a low cost-approach to competitive advantage will lead to a higher degree of involvement. H3b: The adoption of an innovation-approach to competitive advantage will lead to a higher degree of involvement. H3c: The adoption of a market research approach to competitive advantages will lead to a higher degree of involvement. H3d: The adoption of a breadth of strategic target-approach to competitive advantage will lead to a lower degree of involvement. H4: The higher the degree of standardisation of the international marketing mix the higher the degree of involvement. H5: The greater the degree of economic development in the host market, the higher the degree of involvement. H6: The greater the cultural differences between home and host countries, the lower the degree of involvement. H7: The greater the difference in regulations between the home country and the host country, the lower the degree of involvement. H8: The higher the political risk in the host country, the lower the degree of involvement. A questionnaire instrument was constructed using, wherever possible, validated measures of the concepts to serve the aims of this study. Following two sets of mailings, 112 usable completed questionnaires were returned. Correlation analysis and multiple regression analysis were used to analyze data. Statistically, the paper suggests that factors relating to the level of competition, competitive advantages and economic development are strong in influencing foreign market involvements. On the other hand, unexpectedly, cultural factors (especially individualism/collectivism and low and high power distance dimensions) proved to have weak moderating effects. The reason for this, in part, is due to the pervading forces of globalisation and the attendant effect on global marketing. This paper has contributed to the general literature in a way that point to two mainimplications. First, with respect to research on national systems, the study may hold out some important lessons especially for developing nations. Most of these nations are known to be actively seeking to understand what it takes to attract foreign direct investment, expand domestic market and move their economies from the margin to the mainstream global economy. Second, it should be realised that competitive conditions remain in constant flux (even in mature industries and mature economies). This implies that a range of home country factors may be as important as host country factors in explaining firms' strategic moves and the degree of foreign market involvement. Further research can consider the impact of the home country environment on foreign market involvement decisions. Such an investigation will potentially provide further perspectives not only on the influence of national origin but also how home country effects are confounded with industry effects.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.39-59
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• 2007

The international involvement of a firm has been described as a gradual development process "a process in which the enterprise gradually increases its international involvement in many studies. This process evolves in the interplay between the development of knowledge about foreign markets and operations on one hand and increasing commitment of resources to foreign markets on the other." On the basis of Uppsala internationalization model, many studies strengthen strong theoretical and empirical support. According to the predictions of the classic stages theory, the internationalization process of firms have been recognized and characterized gradual evolution to foreign markets, so called stage theory: indirect & direct export, strategic alliance and foreign direct investment. However, termed "international new ventures" (McDougall, Shane, and Oviatt 1994), "born globals" (Knight 1997; Knight and Cavusgil 1996; Madsen and Servais 1997), "instant internationals" (Preece, Miles, and Baetz 1999), or "global startups" (Oviatt and McDougall 1994) have been used and come into spotlight in internationalization study of technology intensity venture companies. Recent researches focused on venture company have suggested the phenomenons of 'born global' firms as a contradiction to the stages theory. Especially the article by Oviatt and McDougall threw the spotlight on international entrepreneurs, on international new ventures, and on their importance in the globalising world economy. Since venture companies have, by definition. lack of economies of scale, lack of resources (financial and knowledge), and aversion to risk taking, they have a difficulty in expanding their market to abroad and pursue internalization gradually and step by step. However many venture companies have pursued 'Born Global Strategy', which is different from process strategy, because corporate's environment has been rapidly changing to globalization. The existing studies investigate that (1) why the ventures enter into overseas market in those early stage, even in infancy, (2) what make the different international strategy among ventures and the born global strategy is better to the infant ventures. However, as for venture's performance(growth and profitability), the existing results do not correspond each other. They also, don't include marketing strategy (differentiation, low price, market breadth and market pioneer) that is important factors in studying of BGV's performance. In this paper I aim to delineate the appearance of international new ventures and the phenomenons of venture companies' internationalization strategy. In order to verify research problems, I develop a resource-based model and marketing strategies for analyzing the effects of the born global venture firms. In this paper, I suggested 3 research problems. First, do the korean venture companies take some advantages in the aspects of corporate's performances (growth, profitability and overall market performances) when they pursue internationalization from inception? Second, do the korean BGV have firm specific assets (foreign experiences, foreign orientation, organizational absorptive capacity)? Third, What are the marketing strategies of korean BGV and is it different from others? Under these problems, I test then (1) whether the BGV that a firm started its internationalization activity almost from inception, has more intangible resources(foreign experience of corporate members, foreign orientation, technological competences and absorptive capacity) than any other venture firms(Non_BGV) and (2) also whether the BGV's marketing strategies-differentiation, low price, market diversification and preemption strategy are different from Non_BGV. Above all, the main purpose of this research is that results achieved by BGV are indeed better than those obtained by Non_BGV firms with respect to firm's growth rate and efficiency. To do this research, I surveyed venture companies located in Seoul and Deajeon in Korea during November to December, 2005. I gather the data from 200 venture companies and then selected 84 samples, which have been founded during 1999${\sim}$2000. To compare BGV's characteristics with those of Non_BGV, I also had to classify BGV by export intensity over 50% among five or six aged venture firms. Many other researches tried to classify BGV and Non_BGV, but there were various criterion as many as researchers studied on this topic. Some of them use time gap, which is time difference of establishment and it's first internationalization experience and others use export intensity, ration of export sales amount divided by total sales amount. Although using a mixed criterion of prior research in my case, I do think this kinds of criterion is subjective and arbitrary rather than objective, so I do mention my research has some critical limitation in the classification of BGV and Non_BGV. The first purpose of research is the test of difference of performance between BGV and Non_BGV. As a result of t-test, the research show that there are statistically efficient difference not only in the growth rate (sales growth rate compared to competitors and 3 years averaged sales growth rate) but also in general market performance of BGV. But in case of profitability performance, the hypothesis that is BGV is more profit (return on investment(ROI) compared to competitors and 3 years averaged ROI) than Non-BGV was not supported. From these results, this paper concludes that BGV grows rapidly and gets a high market performance (in aspect of market share and customer loyalty) but there is no profitability difference between BGV and Non_BGV. The second result is that BGV have more absorptive capacity especially, knowledge competence, and entrepreneur's international experience than Non_BGV. And this paper also found BGV search for product differentiation, exemption strategy and market diversification strategy while Non_BGV search for low price strategy. These results have never been dealt with other existing studies. This research has some limitations. First limitation is concerned about the definition of BGV, as I mentioned above. Conceptually speaking, BGV is defined as company pursue internationalization from inception, but in empirical study, it's very difficult to classify between BGV and Non_BGV. I tried to classify on the basis of time difference and export intensity, this criterions are so subjective and arbitrary that the results are not robust if the criterion were changed. Second limitation is concerned about sample used in this research. I surveyed venture companies just located in Seoul and Daejeon and also use only 84 samples which more or less provoke sample bias problem and generalization of results. I think the more following studies that focus on ventures located in other region, the better to verify the results of this paper.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Korean Society of Forest Science
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• v.52 no.1
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• pp.37-49
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• 1981

The purpose of the study is to find out the objective method of valuation on the forest stands through the analysis of logging costs that is positively related to timber production. The two forest (Amgog, Whangryoung), located nereby, but forest type, logging and skidding conditions being slightly different, were slected to carry out the study. The objective timber stumpage value were determined by investigating the appropriate timber production costs and profits of logging operations. The main result obtained in this study are as follows: 1. The rate of logging cost in consisting of timber market price is 13.15% in the area of Amgog logging place and 19.48% in Whangryoung. 2. The rate of the other production cost excluding logging cost is 15.36% in the area of Amgog logging place and 28.85% in Whangryoung. 3. The total rate of timber production cost in consisting of the market price is more than 28.51% in the area of Amgog logging place and 48.33% in Whangryoung, 4. Though the productivity of forest land is affected by the selection of tree species, tending, treatments and effective management of forest land, the more important problem is improvement of logging condition. 5. The rate of production cost in timber price is so high that we should endeavore to improve the productivity of labour and its quality, and minimize the difference of piece work per day in accordance to the various site condition. 6. Although the profit of forest industry is related to the period of recapturing investment, it is more closely related to the working condition, risk of investment and continuous change of social investment interest. 7. If the right variables which are related to the timber market, are objectively obtained, the stumpage value of mature forests can be objectively caculated by applying straight line discounting method or compound discounting method in caculating the stump to market price.

• The Journal of Small Business Innovation
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• v.19 no.2
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.87-92
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• 2010

Purpose: In 2003, we decided to buy a PET/CT, at the time, it was the latest cancer diagnostic medical equipment. Equipment company was offered the marketing of collaboration operation because the highly cost of PET/CT. However, this hospital's choice was own purchase way. In this study we evaluated the collaboration operation way by post-mortem analysis to the current situation. Materials and Methods: From 2004 until 2008, five years, we investigate the revenue analysis the number of PET/CT cases about own purchase way and collaboration operation way according (ABC costing). Results: The year 2004, own purchase way is 4 billion 9 thousand 2 hundred million won in deficit, the collaboration operation way is 1 billion 1 thousand 7 hundred million won in deficit. The year 2005, own purchase way is 1 billion 5 hundred million won in deficit, collaboration operation way is 8 thousand 7 hundred million won in deficit. However, the year 2006, own purchase way is 5 billion 1thousand 3 hundred million won in surplus, collaboration operation way is 9 thousand 9 hundred million won in deficits. The year 2007 and 2008, revenue of own purchase way is more increased but the collaboration operation way is more decreased. From the year 2004 to 2008, subtotal of own purchase way is 10 billion 8 thousand 8 hundred won in surplus, sub-total of collaboration operation way is 6 billion 7 thousand million won in deficit. Conclusion: Own purchase way has been a big benefit occurs and to reflect the equipment price, the collaboration operation way became to deficit continues. In other words, the problem of collaboration operation way showed us. When you buy the high cost Equipment, consideration will be risk and economic analysis of variance, the appropriate of the initial investment cost, clinical diagnostic needs and etc.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Management & Information Systems Review
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• v.29 no.2
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• pp.1-25
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• 2010

This study attempted to empirically test the determinants of stock returns in Korean stock market applying multi-factor model proposed by Haugen and Baker(1996). Regression models were developed using 16 variables related to liquidity, risk, historical price, price level, and profitability as independent variables and 690 stock monthly returns as dependent variable. For the statistical analysis, the data were collected from the Kis Value database and the tests of forecasting power in this study minimized various possible bias discussed in the literature as possible. The statistical results indicated that: 1) Liquidity, one-month excess return, three-month excess return, PER, ROE, and volatility of total return affect stock returns simultaneously. 2) Liquidity, one-month excess return, three-month excess return, six-month excess return, PSR, PBR, ROE, and EPS have an antecedent influence on stock returns. Meanwhile, realized returns of decile portfolios increase in proportion to predicted returns. This results supported previous study by Haugen and Baker(1996) and indicated that firm-characteristic model can better predict stock returns than CAPM. 3) The firm-characteristic model has better predictive power than Fama-French three-factor model, which indicates that a portfolio constructed based on this model can achieve excess return. This study found that expected return factor models are accurate, which is consistent with other countries' results. There exists a surprising degree of commonality in the factors that are most important in determining the expected returns among different stocks.