• Title/Summary/Keyword: Stock index by industry

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Improvement of Paper Bulk and Stiffness by Using Drying Shrinkage Analysis (건조수축 해석을 통한 종이의 벌크 및 강직성 향상)

  • Lee, Jin-Ho;Park, Jong-Moon
    • Journal of Korea Technical Association of The Pulp and Paper Industry
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    • v.43 no.4
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    • pp.49-58
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    • 2011
  • The maximum drying shrinkage velocity was proposed to verify bulk and stiffness improvement mechanism during drying according to papermaking parameters. It was based on the wet-web shrinkage behavior without the restraint of wet-web during drying, so intact drying impact could be measured. Bulking agent reduced the drying shrinkage and the maximum drying shrinkage velocity, so paper bulk increased and paper strength decreased. When adding cationic starch to stock with the bulking agent for strengthening, the bulk was increased further with additional decreasing of the drying shrinkage and the maximum drying shrinkage velocity. Paper strength also increased except tensile stiffness index with decreasing the drying shrinkage and the maximum drying shrinkage velocity. When using additional strength additives for strengthening of fiber interfaces extended by bulking agent and cationic starch, amphoteric strength additive increased paper stiffness without loss of paper bulk. It was considered that the added amphoteric strength additives were cross-linked to the stretched cationic starch and this cross-linking increased elasticity of fiber-polymer-fiber interfaces without changing the drying behavior. Paper bulk could be increased with decreasing the maximum drying shrinkage velocity. The drying shrinkage of paper also could be controlled by fiber-to-fiber bonding interfaces by the bulking agent. In this case, paper strength including stiffness was decreased by reducing fiber-to-fiber bonding but it could be improved by strengthening fiber-to-fiber interfaces with polymer complex without loss of bulk.

Conflict of Interests and Analysts' Forecast (이해상충과 애널리스트 예측)

  • Park, Chang-Gyun;Youn, Taehoon
    • KDI Journal of Economic Policy
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    • v.31 no.1
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    • pp.239-276
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    • 2009
  • The paper investigates the possible relationship between earnings prediction by security analysts and special ownership ties that link security companies those analysts belong to and firms under analysis. "Security analysts" are known best for their role as information producers in stock markets where imperfect information is prevalent and transaction costs are high. In such a market, changes in the fundamental value of a company are not spontaneously reflected in the stock price, and the security analysts actively produce and distribute the relevant information crucial for the price mechanism to operate efficiently. Therefore, securing the fairness and accuracy of information they provide is very important for efficiencyof resource allocation as well as protection of investors who are excluded from the special relationship. Evidence of systematic distortion of information by the special tie naturally calls for regulatory intervention, if found. However, one cannot presuppose the existence of distorted information based on the common ownership between the appraiser and the appraisee. Reputation effect is especially cherished by security firms and among analysts as indispensable intangible asset in the industry, and the incentive to maintain good reputation by providing accurate earnings prediction may overweigh the incentive to offer favorable rating or stock recommendation for the firms that are affiliated by common ownership. This study shares the theme of existing literature concerning the effect of conflict of interests on the accuracy of analyst's predictions. This study, however, focuses on the potential conflict of interest situation that may originate from the Korea-specific ownership structure of large conglomerates. Utilizing an extensive database of analysts' reports provided by WiseFn(R) in Korea, we perform empirical analysis of potential relationship between earnings prediction and common ownership. We first analyzed the prediction bias index which tells how optimistic or friendly the analyst's prediction is compared to the realized earnings. It is shown that there exists no statistically significant relationship between the prediction bias and common ownership. This is a rather surprising result since it is observed that the frequency of positive prediction bias is higher with such ownership tie. Next, we analyzed the prediction accuracy index which shows how accurate the analyst's prediction is compared to the realized earnings regardless of its sign. It is also concluded that there is no significant association between the accuracy ofearnings prediction and special relationship. We interpret the results implying that market discipline based on reputation effect is working in Korean stock market in the sense that security companies do not seem to be influenced by an incentive to offer distorted information on affiliated firms. While many of the existing studies confirm the relationship between the ability of the analystand the accuracy of the analyst's prediction, these factors cannot be controlled in the above analysis due to the lack of relevant data. As an indirect way to examine the possibility that such relationship might have distorted the result, we perform an additional but identical analysis based on a sub-sample consisting only of reports by best analysts. The result also confirms the earlier conclusion that the common ownership structure does not affect the accuracy and bias of earnings prediction by the analyst.

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Antecedents of Disclosure on Internal Control and Earnings Management

  • ZULFIKAR, Rudi;MILLATINA, Firda;MUKHTAR, Mukhtar;ASTUTI, Kurniasih Dwi;ISMAIL, Tubagus;MEUTIA, Meutia;FAZRI, Edward
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.3
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    • pp.391-397
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    • 2021
  • This study examines the effect of independent commissioners and the Audit Committee on internal control disclosure and its implications for earnings management in the banking industry listed on the Indonesia Stock Exchange for the period 2016-2018. In this study, a purposive sampling technique was used, combined with two multiple regression analysis models. The final sample for this study comprised 30 companies over the three years of observation, such that there were 90 observations in total. This study indicates that independent commissioners, as measured by their composition, do not affect the disclosure of internal control. However, as measured by the number of members, the Audit Committee had a positive effect on internal control disclosures. This study also indicates that the disclosure of internal control as measured by the Internal Control Disclosure index affects reducing the negative practice of earnings management. This study proves that the Audit Committee's role is very dominant in assisting the Board of Commissioners in supervising internal control. This has implications for reducing earnings management practices. However, the Independent Commissioner's role in the Indonesian banking industry has not been optimal in carrying out the supervisory function in this study.

Fund Flow and Market Risk (펀드플로우와 시장위험)

  • Chung, Hyo-Youn;Park, Jong-Won
    • The Korean Journal of Financial Management
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    • v.27 no.2
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    • pp.169-204
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    • 2010
  • This paper examines the dynamic relationship between fund flow and market risk at the aggregate level and explores whether sudden sharp changes in fund flow (fund run) can cause a systemic risk in the Korean financial markets. We use daily and weekly data and regression and VAR analysis. Main results of the paper are as follows: First, in the stock market, a concurrent and a lagged unexpected fund flows have a positive relationship with market volatility. A positive shock in fund flow predicts an increase in stock market volatility. In the bond market, an unexpected fund flow has a negative relationship with the default risk premium, but a positive relationship with the term premium. And an unexpected fund flow of the money market fund has a negative relationship with the liquidy risk, but the explanatory power is very low. Second, for examining whether changes in fund flow induce a systemic risk, we construct a spillover index based on the forecast error variance decomposition of VAR model. A spillover index represents that how much the shock in fund flow can explain the change of market risk in a market. In general, explanatory powers from spillover indexes are so fluctuant and low. In the stock market, the impact of shocks in fund flow on market risk is relatively high and persistent during the period from the end of 2007 to 2008, which is the subprime-mortgage crisis period. In bond market, since the end of 2008, the impact of shocks in fund flow spreads to default risk continually, while in the money market, such a systematic effect doesn't take place. The persistent patterns of spillover effect appearing around a certain period in the stock market and the bond market suggest that the shock to the unexpected fund flow may increase the market risk and can be a cause of systemic risk in the financial markets. However, summarizing the results of regression and VAR model analysis, and considering the very low explanatory power of spillover index analysis, we can conclude that changes in fund flow have a very limited power in explaining changes in market risk and it is not very likely to induce the systemic risk by a fund run in the Korean financial markets.

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Dynamic Glide Path using Retirement Target Date and Forecast Volatility (은퇴 시점과 예측 변동성을 고려한 동적 Glide Path)

  • Kim, Sun Woong
    • Journal of Convergence for Information Technology
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    • v.11 no.2
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    • pp.82-89
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    • 2021
  • The objective of this study is to propose a new Glide Path that dynamically adjusts the risky asset inclusion ratio of the Target Date Fund by simultaneously considering the market's forecast volatility as well as the time of investor retirement, and to compare the investment performance with the traditional Target Date Fund. Forecasts of market volatility utilize historical volatility, time series model GARCH volatility, and the volatility index VKOSPI. The investment performance of the new dynamic Glide Path, which considers stock market volatility has been shown to be excellent during the analysis period from 2003 to 2020. In all three volatility prediction models, Sharpe Ratio, an investment performance indicator, is improved with higher returns and lower risks than traditional static Glide Path, which considers only retirement date. The empirical results of this study present the potential for the utilization of the suggested Glide Path in the Target Date Fund management industry as well as retirees.

Assessment and Prediction of Stand Yield in Cryptomeria japonica Stands (삼나무 임분수확량 평가 및 예측)

  • Son, Yeong Mo;Kang, Jin Taek;Hwang, Jeong Sun;Park, Hyun;Lee, Kang Su
    • Journal of Korean Society of Forest Science
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    • v.104 no.3
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    • pp.421-426
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    • 2015
  • The objective of this paper is to look into the growth of Cryptomeria japonica stand in South Korea along with the evaluation on their yields, followed by their carbon stocks and removals. A total of 106 sample plots were selected from Jeonnam, Gyeongnam, and Jeju, where the groups of standard are grown. We only used 92 plots data except outlier. As part of the analysis, the Weibull diameter distribution was applied. In order to estimate the diameter distribution, the growth estimation equation for each of the growth factors including the height, the diameter at breast height, and the basal area was drafted out and the verification for each equation was examined. The site index for figuring out the forest productivity of Cryptomeria japonica stand for each district was also developed as a Schumacher model and 30yr was used as a reference age for the estimation of the site index. It was found that the site index for Cryptomeria japonica stand in South Korea ranges from 10 to 16 and this result was used as a standard for developing the stand yield table. According to the site 14 in the stand yield table, the mean annual increment (MAI) of the Cryptomeria japonica reaches $7.6m^3/ha$ on its 25yr and its growing stock is estimated to be at $190.1m^3/ha$. This volume is about $20m^3$ as high as that of the Chamaesyparis obtusa. Furthermore, the annual carbon absorptions for a Cryptomeria japonica stand reached the peak at 25yr, which is 2.14 tC/ha/yr, $7.83tCO_2/ha/yr$. When compared to the other conifers, this rate is slightly higher than that of a Chamaecyparis obtusa ($7.5tCO_2/ha/yr$) but lower than that of the Pinus koraiensis ($10.4tCO_2/ha/yr$) and Larix kaempferi ($11.2tCO_2/ha/yr$). With such research result as a base, it is necessary to come up with the ways to enhance the utilization of Cryptomeria japonica as timbers, besides making use of their growth data.

A Study on Industries's Leading at the Stock Market in Korea - Gradual Diffusion of Information and Cross-Asset Return Predictability- (산업의 주식시장 선행성에 관한 실증분석 - 자산간 수익률 예측 가능성 -)

  • Kim Jong-Kwon
    • Proceedings of the Safety Management and Science Conference
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    • 2004.11a
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    • pp.355-380
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    • 2004
  • I test the hypothesis that the gradual diffusion of information across asset markets leads to cross-asset return predictability in Korea. Using thirty-six industry portfolios and the broad market index as our test assets, I establish several key results. First, a number of industries such as semiconductor, electronics, metal, and petroleum lead the stock market by up to one month. In contrast, the market, which is widely followed, only leads a few industries. Importantly, an industry's ability to lead the market is correlated with its propensity to forecast various indicators of economic activity such as industrial production growth. Consistent with our hypothesis, these findings indicate that the market reacts with a delay to information in industry returns about its fundamentals because information diffuses only gradually across asset markets. Traditional theories of asset pricing assume that investors have unlimited information-processing capacity. However, this assumption does not hold for many traders, even the most sophisticated ones. Many economists recognize that investors are better characterized as being only boundedly rational(see Shiller(2000), Sims(2201)). Even from casual observation, few traders can pay attention to all sources of information much less understand their impact on the prices of assets that they trade. Indeed, a large literature in psychology documents the extent to which even attention is a precious cognitive resource(see, eg., Kahneman(1973), Nisbett and Ross(1980), Fiske and Taylor(1991)). A number of papers have explored the implications of limited information- processing capacity for asset prices. I will review this literature in Section II. For instance, Merton(1987) develops a static model of multiple stocks in which investors only have information about a limited number of stocks and only trade those that they have information about. Related models of limited market participation include brennan(1975) and Allen and Gale(1994). As a result, stocks that are less recognized by investors have a smaller investor base(neglected stocks) and trade at a greater discount because of limited risk sharing. More recently, Hong and Stein(1999) develop a dynamic model of a single asset in which information gradually diffuses across the investment public and investors are unable to perform the rational expectations trick of extracting information from prices. Hong and Stein(1999). My hypothesis is that the gradual diffusion of information across asset markets leads to cross-asset return predictability. This hypothesis relies on two key assumptions. The first is that valuable information that originates in one asset reaches investors in other markets only with a lag, i.e. news travels slowly across markets. The second assumption is that because of limited information-processing capacity, many (though not necessarily all) investors may not pay attention or be able to extract the information from the asset prices of markets that they do not participate in. These two assumptions taken together leads to cross-asset return predictability. My hypothesis would appear to be a very plausible one for a few reasons. To begin with, as pointed out by Merton(1987) and the subsequent literature on segmented markets and limited market participation, few investors trade all assets. Put another way, limited participation is a pervasive feature of financial markets. Indeed, even among equity money managers, there is specialization along industries such as sector or market timing funds. Some reasons for this limited market participation include tax, regulatory or liquidity constraints. More plausibly, investors have to specialize because they have their hands full trying to understand the markets that they do participate in

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Analysis of Intrinsic Patterns of Time Series Based on Chaos Theory: Focusing on Roulette and KOSPI200 Index Future (카오스 이론 기반 시계열의 내재적 패턴분석: 룰렛과 KOSPI200 지수선물 데이터 대상)

  • Lee, HeeChul;Kim, HongGon;Kim, Hee-Woong
    • Knowledge Management Research
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    • v.22 no.4
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    • pp.119-133
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    • 2021
  • As a large amount of data is produced in each industry, a number of time series pattern prediction studies are being conducted to make quick business decisions. However, there is a limit to predicting specific patterns in nonlinear time series data due to the uncertainty inherent in the data, and there are difficulties in making strategic decisions in corporate management. In addition, in recent decades, various studies have been conducted on data such as demand/supply and financial markets that are suitable for industrial purposes to predict time series data of irregular random walk models, but predict specific rules and achieve sustainable corporate objectives There are difficulties. In this study, the prediction results were compared and analyzed using the Chaos analysis method for roulette data and financial market data, and meaningful results were derived. And, this study confirmed that chaos analysis is useful for finding a new method in analyzing time series data. By comparing and analyzing the characteristics of roulette games with the time series of Korean stock index future, it was derived that predictive power can be improved if the trend is confirmed, and it is meaningful in determining whether nonlinear time series data with high uncertainty have a specific pattern.

Rough Set Analysis for Stock Market Timing (러프집합분석을 이용한 매매시점 결정)

  • Huh, Jin-Nyung;Kim, Kyoung-Jae;Han, In-Goo
    • Journal of Intelligence and Information Systems
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    • v.16 no.3
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    • pp.77-97
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    • 2010
  • Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

The Effects of Compliance Timing on Multinational Enterprises' Corporate Performance in China: An Application of Institutional Perspectives

  • Yang, Woo-Young;Han, Byoung-Sop
    • Journal of Korea Trade
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    • v.24 no.4
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    • pp.71-94
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    • 2020
  • Purpose - Multi-National Enterprises (MNEs) tend to face a high level of institutional pressures in regions with high institutional development level. When complying with institutional pressures, firms try to make decisions to maximize profit while minimizing the risks to them. The purpose of this study is to investigate the influence of the institutional development level on institutional compliance timing by MNEs and the relationship between compliance speed and corporate performance. Design/methodology - The research focuses on three main variables, which are the institutional development level (as a determination of the institutional pressure level), the firm's compliance speed (as a determination of the compliance timing), and the firm's financial performance (as a determination of the corporate performance). We collected 19,869 firm-level data from CSMAR (the China Stock Market and Accounting Research), 6,922 CSR data from RKS (the Rankins CSR Ratings), and province and city-level data from the NERIM (National Economic Research Institute Index of Marketization) and NBSC (National Bureau of Statistics of China). The firms in China were chosen for analysis, and the analysis period was from 2008 to 2017. Random Effects GLS Regression was used to test the relationships among the variables. Findings - This study examined the effect of the institutional development level on the firm's compliance speed, together with the effect of compliance speed on the firm's financial performance of the MNEs in China. We found that the institutional development level positively influenced firms' financial performances, which means the firms' financial performances are better in the region with a high institutional development level. The compliance speed of institutional practice by firms was faster in the higher level of institutional development. However, the firm's delayed compliance led to better financial performance. Originality/value - Studies in the resource dependence view of Institutional Theory often fall short in understanding the theory by overlooking the firm's active decision-making. Thus, the findings do not present a full scope of corporate performance in this regard. This study not only found a way to test the role of a firm's independent decision-making (i.e., compliance timing) when facing the institutional pressure but also prove the significant role of the compliance timing on corporate performance. Also, we were able to test the effect of institutional development level, controlling location-specific variables because we used CSR performance data for MNEs operating in China. Lastly, by doing the above, the findings of this study suggest practical implications to the industry practitioners in MNEs.