• 한국언론정보학보
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• 제64권
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• pp.5-30
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• 2013

이 글은 오늘날 인터넷을 비롯한 정보기술문화를 비판적으로 분석하기 위한 개념틀로 이중적 플랫폼을 제안한다. 인터페이스연구와 양면시장론에 기대어 인터넷을 이중적 플랫폼으로 접근함으로써 전면에는 이용자의 공개, 공유, 참여의 광장이 펼쳐지고 이면에는 그에 대한 추적, 감시, 통제의 시장이 형성되는 복합적 양상을 분석할 수 있다. 특히 전면의 광장과 이면의 시장이 어떻게 하나의 플랫폼에서 공존하며 모순적으로 상호작용하는가에 초점을 맞추면서 인터넷의 이중적 플랫폼을 광장시장의 인터페이스로 규정할 것이다. 그에 이어 월드와이드웹의 설계구조가 바뀌고 콘텐츠에서 데이터로 정보재의 주요 상품 형태가 변천하며 이용자 추적을 위한 웹벌레의 기능을 분석하면서 웹 전체가 어떻게 이중적 플랫폼으로 기능하는지 규명한다. 마지막으로 이중적 플랫폼 개념틀의 함의와 추후 심화된 분석을 위해 필요한 과제를 제시한다.

• 전기학회논문지
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• 제60권1호
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• pp.32-35
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• 2011

The economic value of a wind farm project is influenced by various risk factors such as wind power output and electricity market price. In particular, there is uncertainty in the economic evaluation of a wind farm project due to uncertain wind power outputs, which are fluctuated by weather factors such as wind speed, and volatile electricity market prices. This paper presents a systematic method to assess the economic value and payback period of a wind farm project using Least Square Monte-Carlo (LSMC) simulation. Numerical example is presented to validate the effectiveness of the proposed economic assessment method for a wind farm project.

• Management Science and Financial Engineering
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• 제14권2호
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• pp.89-104
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• 2008

Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.

• The Journal of Asian Finance, Economics and Business
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• 제8권6호
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• pp.543-552
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• 2021

The study examines how foreign capital inflows affect stock market development in Pakistan for the period from July 2008 to June 2018. Several components of foreign capital inflows were used for empirical analysis, namely, foreign direct investment, foreign portfolio investment, and remittances. Further, market capitalization was used as a proxy for stock market development. The study uses an ARDL model for examining the long-run and short-run relationships between variables. We also analyze the bi-directional causality between the variables through the Granger causality test. Further, the presence of structural breaks was analyzed through the CUSUM and CUSUM Square test. The results suggest that in the long run, remittances have a positive and significant relationship with stock market development. However, foreign direct investment, foreign portfolio investment, and USD-PKR exchange rate do not have a significant impact on stock market development. The results also suggest that in the short run there is a negative relationship between FDI, USD-PKR exchange rate and market capitalization. Contrarily, we found a positive relationship between FPI and market capitalization. The results of Granger causality test suggest that remittances and USD-PKR exchange rate have a causal relationship with stock market development. Finally, we found no evidence of structural breaks in the dataset.

• Communications for Statistical Applications and Methods
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• 제15권1호
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• pp.117-124
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• 2008

The liquidity risk is defined as an additional risk in the market due to the timing and size of a trade. A recent work by Cetin et ai. (2003) proposes a rigorous mathematical model incorporating this liquidity risk into the arbitrage pricing theory. A practical problem arising in a real market application is an estimation problem of a liquidity cost. In this paper, we propose to estimate the liquidity cost function in the context of Cetin et al. (2003) using the constrained least square (LS) method, and illustrate it by analyzing the Kellogg company data.

• 통상정보연구
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• 제10권1호
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• pp.259-277
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• 2008

This paper empirically analyzes the influence of export insurance on export promotion using panel data for the Korean case during the sample period from 2003 to 2006. We use the Korean export's share in trading partners' imports as a weight for the weighted least square (WLS) estimation to measure the effect of export insurance on the export promotion. Our main finding is that export insurance subsidy seems to enhance the export performance when the Korean export takes greater share in other countries' markets. On the other hand, under weaker monopoly power of the Korean export, export risk and trading partners' GDP growth rate has more influence on the export promotion rather than export insurance subsidy. Our finding implies that policy makers and practitioners should discern the Korean exports' monopoly power differential across trading countries for better performing export insuarnce policy.

• The Journal of Asian Finance, Economics and Business
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• 제5권1호
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• pp.11-16
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• 2018

This research examines the alternative ways of estimating the coefficient of non-diversifiable risk, namely beta coefficient, in Capital Asset Pricing Model (CAPM) introduced by Sharpe (1964) that is an essential element of assessing the value of diverse assets. The non-parametric methods used in this research are the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator). The Jackknife, the resampling technique, is also employed to validate the results. According to finance literature and common practices, these coecients have often been estimated using Ordinary Least Square (LS) regression method and monthly return data set. The empirical results of this research pointed out that the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) performed much better than Ordinary Least Square (LS) in terms of eciency for large-cap stocks trading actively in the United States markets. Interestingly, the empirical results also showed that daily return data would give more accurate estimation than monthly return data in both Ordinary Least Square (LS) and robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) regressions.

• 한국경영과학회지
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• 제38권1호
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• pp.45-59
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• 2013

A long-term forecasting method for a new product in early stage of diffusion is proposed. The method includes a constrained non-linear least square estimation with the logistic diffusion model. The constraints would be critical market informations such as market potential, peak point, and take-off. Findings on 20 cases having almost full life cycle are that (i) combining any market information improves the forecasting accuracy, (ii) market potential is the most stable information, and (iii) peak point and take-off information have negative effect in case of overestimation.

• 응용통계연구
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• 제25권1호
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• pp.15-27
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• 2012

본 논문에서는 KOSPI 시가총액기준 상위 4종목(삼성전자, 현대차, 현대모비스, POSCO)의 고빈도 거래 데이터를 바탕으로 일중 수익률의 실현변동성과 시장미시구조잡음에 대해 연구한다. Volatility signature plot을 통해 실현변동성(Realized Variance; RV)과 편의수정 실현변동성($RV_{AC_1}$)의 편의를 확인하고 시장미시구조 잡음의 특징을 실증적으로 파악한다. 또한, 잡음 대 신호비(Noise-to-Signal Ratio; NSR)를 사용하여, 평균제곱오차(Mean Square Error; MSE) 기준의 실현변동성(RV)과 편의수정 실현변동성($RV_{AC_1}$)의 최적 추출 빈도수를 추정해본다.

• 대한수학회지
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• 제61권5호
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• pp.875-898
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• 2024

This study estimates the true price of an asset and finds the optimal bid/ask prices for market makers. We provide a novel state-space model based on the exponential Ornstein-Uhlenbeck volatility and the Heston models with Gaussian noise, where the traded price and volume are available, but the true price is not observable. An objective of this study is to use Bayesian filtering to estimate the posterior distribution of the true price, given the traded price and volume. Because the posterior density is intractable, we employ the guided particle filtering algorithm, with which adaptive rejection metropolis sampling is used to generate samples from the density function of an unknown distribution. Given a simulated sample path, the posterior expectation of the true price outperforms the traded price in estimating the true price in terms of both the mean absolute error and root-mean-square error metrics. Another objective is to determine the optimal bid/ask prices for a market maker. The profit-and-loss of the market maker is the difference between the true price and its bid/ask prices multiplied by the traded volume or bid/ask size of the market maker. The market maker maximizes the expected utility of the PnL under the posterior distribution. We numerically calculate the optimal bid/ask prices using the Monte Carlo method, finding that its spread widens as the market maker becomes more risk-averse, and the bid/ask size and the level of uncertainty increase.