• Title/Summary/Keyword: 정보 비대칭

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An Empirical Analysis of Fixed Asset Investment Smoothing Effects of Working Capital (운전자본의 고정자산투자 스무딩효과의 실증적 분석)

  • Shin, Min-Shik;Kim, Soo-Eun;Kim, Gong-Young
    • The Korean Journal of Financial Management
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    • v.25 no.4
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    • pp.25-51
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    • 2008
  • In this paper, we analyse empirically the fixed asset investment smoothing of working capital of firms listed on Korea Securities Market. The main results of this study can be summarized as follows. Firms will seek to lower long-term cost by smoothing fixed asset investment and maintaining stationary investment with working capital. Working capital is not only an important use of fund, but also a source of liquidity that should be used to smooth fixed asset investment relative to cash flow shocks if firms face financial constraints. Working capital investment is more sensitive than fixed asset investment to cash flow fluctuations. If firms face financial constraints, working capital investment will compete with fixed asset investment for the limited pool of available cash flows. So, fixed asset investment will have negative relationship with working capital investment. However, criticism that the positive correlation between cash flows and fixed asset investment could arise simply because cash flows is proxy variable for investment demand. Finally, controlling for the fixed asset investment smoothing effects of working capital results in a much larger estimate of the long run impact of financial constraints. Financial constraints is measured by dividend payout ratio and market access level. Fazzari et al. (1988), Fazzari and Petersen (1993), and Faulkender et al. (2008) emphasize that low dividend firms or market unaccessible firms are more likely to face financial constraints, and rarely make use of new equity issuing. The results from empirical analysis show that financial constraints can be better explained using 'adjustment cost' concept. Specifically, the results show that financial constraints exist and that in order to measure financial constraint effects more succinctly, fixed asset investment smoothing effects with working capital should be considered.

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An Analysis of the Dynamics between Media Coverage and Stock Market on Digital New Deal Policy: Focusing on Companies Related to the Fourth Industrial Revolution (디지털 뉴딜 정책에 대한 언론 보도량과 주식 시장의 동태적 관계 분석: 4차산업혁명 관련 기업을 중심으로)

  • Sohn, Kwonsang;Kwon, Ohbyung
    • The Journal of Society for e-Business Studies
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    • v.26 no.3
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    • pp.33-53
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    • 2021
  • In the crossroads of social change caused by the spread of the Fourth Industrial Revolution and the prolonged COVID-19, the Korean government announced the Digital New Deal policy on July 14, 2020. The Digital New Deal policy's primary goal is to create new businesses by accelerating digital transformation in the public sector and industries around data, networks, and artificial intelligence technologies. However, in a rapidly changing social environment, information asymmetry of the future benefits of technology can cause differences in the public's ability to analyze the direction and effectiveness of policies, resulting in uncertainty about the practical effects of policies. On the other hand, the media leads the formation of discourse through communicators' role to disseminate government policies to the public and provides knowledge about specific issues through the news. In other words, as the media coverage of a particular policy increases, the issue concentration increases, which also affects public decision-making. Therefore, the purpose of this study is to verify the dynamic relationship between the media coverage and the stock market on the Korean government's digital New Deal policy using Granger causality, impulse response functions, and variance decomposition analysis. To this end, the daily stock turnover ratio, daily price-earnings ratio, and EWMA volatility of digital technology-based companies related to the digital new deal policy among KOSDAQ listed companies were set as variables. As a result, keyword search volume, daily stock turnover ratio, EWMA volatility have a bi-directional Granger causal relationship with media coverage. And an increase in media coverage has a high impact on keyword search volume on digital new deal policies. Also, the impulse response analysis on media coverage showed a sharp drop in EWMA volatility. The influence gradually increased over time and played a role in mitigating stock market volatility. Based on this study's findings, the amount of media coverage of digital new deals policy has a significant dynamic relationship with the stock market.

A Study of the Current State of the Garden and Restoration Proposal for the Original Garden of Yi Cheon-bo's Historic House in Gapyeong (가평 이천보(李天輔) 고가(古家)의 정원 현황과 원형 복원을 위한 제안)

  • Rho, Jaehyun;Choi, Seunghee;Jang, Hyeyoung
    • Korean Journal of Heritage: History & Science
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    • v.53 no.4
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    • pp.118-135
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    • 2020
  • It is not uncommon in Korea to see the structure and function of a garden remain intact as well as its form. Yi Cheon-bo's Historic House (Gyeonggi-do Cultural Heritage Item No. 55), located in Sang-myeon, Gapyeong-gun, Gyeonggi-do, is considered an example of very valuable garden heritage, although its family history, location, and remaining buildings and natural cultural assets are not fully intact. Along with Yi Cheon-bo's Historic House, this study attempted to explore the possibility of restoration of the forest houses and gardens by highlighting the high value of Yi Cheon-bo's Historic House through research into the typical layout of private households in northern Gyeonggi Province and Gapyeong County, comparative review of aerial photographs from 1954, and interviews with those involved. The results of the study are as follows: In this study, the presence of Banggye-dongmun and Bansukam in the Banggyecheon area, where the location of the garden was well-preserved, was examined across the landscape of the outer garden, while the location of Yi Cheon-bo's Historic House, the appearance of feng shui, and the viewing axis were considered. Also, the appearance of the lost main house was inferred from the arrangement and shape of the Sarangchae and Haengrangchae that remain in the original garden, and the asymmetry of the Sarangchae Numaru and the hapgak shape on the side of the roof. In addition, the three tablets (Pyeonaeks) of Sanggodang (尙古堂), Bangyejeongsa (磻溪精舍), and Okgyeongsanbang (玉聲山房) were used to infer the landscape, use, and symbolism of the men's quarters. Also, a survey was conducted on the trees that existed or existed in the high prices. Incidentally, it was confirmed that information on boards and cultural properties of Yeonha-ri juniper (Gyeonggi-do Monument No. 61) was recorded to a much lesser extent than the actual required standard, and the juniper trees remaining in the front of Haengrangchae should also be re-evaluated after speculation. On the other hand, as a result of estimating the original shape as a way of pursuing completeness of the garden through restoration of the lost women's quarters and shrine, it is estimated that the main house was placed in the form of a '口' or a 'be warped 口' on the right (north) side of the men's quarters. By synthesizing these results, a restoration alternative for Yi Cheon-bo's Historic House was suggested.

An Empirical Analysis of Accelerator Investment Determinants: A Longitudinal Study on Investment Determinants and Investment Performance (액셀러레이터 투자결정요인 실증 분석: 투자결정요인과 투자성과에 대한 종단 연구)

  • Jin Young Joo;Jeong Min Nam
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.4
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    • pp.1-20
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    • 2023
  • This study attempted to identify the relationship between the investment determinants of accelerators and investment performance through empirical analysis. Through literature review, four dimensions and 12 measurement items were extracted for investment determinants, which are independent variables, and investment performance was adjusted to the cumulative amount of subsequent investment based on previous studies. Performance data from 594 companies selected by TIPS from 2017 to 2019, which are relatively reliable and easy to secure data, were collected, and the subsequent investment cumulative attraction amount, which is a dependent variable, was hypothesized through multiple regression analysis three years after the investment. As a result of the study, 'industrial experience years' in the characteristics of founders, 'market size', 'market growth', 'competitive strength', and 'number of patents' in the characteristics of products and services had a significant positive (+) effect. The impact of independent variables on dependent variables was most influenced by the competitive strength of market characteristics, followed by the number of years of industrial experience, the number of patents, the size of the market, and market growth. This was different from the results of previous studies conducted mainly on qualitative research methods, and in most previous studies, the characteristics of founders were the most important, but the empirical analysis results were market characteristics. As a sub-factor, the intensity of competition, which was the subordinate to the importance of previous studies, had the greatest influence in empirical analysis. The academic significance of this study is that it presented a specific methodology to collect and build 594 empirical samples in the absence of empirical research on accelerator investment determinants, and created an opportunity to expand the theoretical discussion of investment determinants through causal research. In practice, the information asymmetry and uncertainty of startups that accelerators have can help them make effective investment decisions by establishing a systematic model of experience-dependent investment determinants.

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Dynamic Limit and Predatory Pricing Under Uncertainty (불확실성하(不確實性下)의 동태적(動態的) 진입제한(進入制限) 및 약탈가격(掠奪價格) 책정(策定))

  • Yoo, Yoon-ha
    • KDI Journal of Economic Policy
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    • v.13 no.1
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    • pp.151-166
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    • 1991
  • In this paper, a simple game-theoretic entry deterrence model is developed that integrates both limit pricing and predatory pricing. While there have been extensive studies which have dealt with predation and limit pricing separately, no study so far has analyzed these closely related practices in a unified framework. Treating each practice as if it were an independent phenomenon is, of course, an analytical necessity to abstract from complex realities. However, welfare analysis based on such a model may give misleading policy implications. By analyzing limit and predatory pricing within a single framework, this paper attempts to shed some light on the effects of interactions between these two frequently cited tactics of entry deterrence. Another distinctive feature of the paper is that limit and predatory pricing emerge, in equilibrium, as rational, profit maximizing strategies in the model. Until recently, the only conclusion from formal analyses of predatory pricing was that predation is unlikely to take place if every economic agent is assumed to be rational. This conclusion rests upon the argument that predation is costly; that is, it inflicts more losses upon the predator than upon the rival producer, and, therefore, is unlikely to succeed in driving out the rival, who understands that the price cutting, if it ever takes place, must be temporary. Recently several attempts have been made to overcome this modelling difficulty by Kreps and Wilson, Milgram and Roberts, Benoit, Fudenberg and Tirole, and Roberts. With the exception of Roberts, however, these studies, though successful in preserving the rationality of players, still share one serious weakness in that they resort to ad hoc, external constraints in order to generate profit maximizing predation. The present paper uses a highly stylized model of Cournot duopoly and derives the equilibrium predatory strategy without invoking external constraints except the assumption of asymmetrically distributed information. The underlying intuition behind the model can be summarized as follows. Imagine a firm that is considering entry into a monopolist's market but is uncertain about the incumbent firm's cost structure. If the monopolist has low cost, the rival would rather not enter because it would be difficult to compete with an efficient, low-cost firm. If the monopolist has high costs, however, the rival will definitely enter the market because it can make positive profits. In this situation, if the incumbent firm unwittingly produces its monopoly output, the entrant can infer the nature of the monopolist's cost by observing the monopolist's price. Knowing this, the high cost monopolist increases its output level up to what would have been produced by a low cost firm in an effort to conceal its cost condition. This constitutes limit pricing. The same logic applies when there is a rival competitor in the market. Producing a high cost duopoly output is self-revealing and thus to be avoided. Therefore, the firm chooses to produce the low cost duopoly output, consequently inflicting losses to the entrant or rival producer, thus acting in a predatory manner. The policy implications of the analysis are rather mixed. Contrary to the widely accepted hypothesis that predation is, at best, a negative sum game, and thus, a strategy that is unlikely to be played from the outset, this paper concludes that predation can be real occurence by showing that it can arise as an effective profit maximizing strategy. This conclusion alone may imply that the government can play a role in increasing the consumer welfare, say, by banning predation or limit pricing. However, the problem is that it is rather difficult to ascribe any welfare losses to these kinds of entry deterring practices. This difficulty arises from the fact that if the same practices have been adopted by a low cost firm, they could not be called entry-deterring. Moreover, the high cost incumbent in the model is doing exactly what the low cost firm would have done to keep the market to itself. All in all, this paper suggests that a government injunction of limit and predatory pricing should be applied with great care, evaluating each case on its own basis. Hasty generalization may work to the detriment, rather than the enhancement of consumer welfare.

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Estimation of GARCH Models and Performance Analysis of Volatility Trading System using Support Vector Regression (Support Vector Regression을 이용한 GARCH 모형의 추정과 투자전략의 성과분석)

  • Kim, Sun Woong;Choi, Heung Sik
    • Journal of Intelligence and Information Systems
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    • v.23 no.2
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    • pp.107-122
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    • 2017
  • Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.