• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.311-324
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• 2021

Investors have increasingly become interested in macroeconomic antecedents in order to better understand the investment environment and estimate the scope of profitable investment in equity markets. This study endeavors to examine the interdependency between the macroeconomic antecedents (international oil price (COP), Domestic gold price (GP), Rupee-dollar exchange rates (ER), Real interest rates (RIR), consumer price indices (CPI)), and the BSE Sensex and Nifty 50 index return. The data is converted into a natural logarithm for keeping it normal as well as for reducing the problem of heteroscedasticity. Monthly time series data from January 1992 to July 2019 is extracted from the Reserve Bank of India database with the application of financial Econometrics. Breusch-Godfrey serial correlation LM test for removal of autocorrelation, Breusch-Pagan-Godfrey test for removal of heteroscedasticity, Cointegration test and VECM test for testing cointegration between macroeconomic factors and market returns,] are employed to fit regression model. The Indian market returns are stable and positive but show intense volatility. When the series is stationary after the first difference, heteroskedasticity and serial correlation are not present. Different forecast accuracy measures point out macroeconomics can forecast future market returns of the Indian stock market. The step-by-step econometric tests show the long-run affiliation among macroeconomic antecedents.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.151-154
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• 2008

Dramatic price increases of fossil fuels and the economic development of emerging nations accelerates the transformation of forest lands into monocultures, e.g. for biofuel production. On this account, cost efficient methods to enable the monitoring of land resources has become a vital ambition. The application of remote sensing techniques has become an integral part of forest attribute estimation and mapping. The aim of this study was to evaluate the potentials of the kNN method by combining terrestrial with remotely sensed data for the development of a pixel-based monitoring system for the small scaled mosaic of different land use types of the off-reserve forests of the Goaso forest district in Ghana, West Africa. For this reason, occurrence and distribution of land use types like cocoa and non-timber forest resources, such as bamboo and raphia palms, were estimated, applying the kNN method to ASTER satellite data. Averaged overall accuracies, ranging from 79% for plantain, to 83% for oil palms, were found for single-attribute classifications, whereas a multi-attribute approach showed overall accuracies of up to 70%. Values of k between 3 and 6 seem appropriate for mapping bamboo. Optimisation of spectral bands improves results considerably.

• Journal of Distribution Science
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• v.13 no.5
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• pp.71-82
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• 2015

Purpose - The purpose of this study is to investigate risk price implied from the pricing kernel of Korean stock distribution market. Recently, it is considered that the quantitative easing programs of major developed countries are contributing to a reduction in global uncertainty caused by the 2007~2009 financial crisis. If true, the risk premium as compensation for global systemic risk or economic uncertainty should show a decrease. We examine whether the risk price in the Korean stock distribution market has declined in recent years, and attempt to provide practical implications for investors to manage their portfolios more efficiently, as well as academic implications. Research design, data and methodology - To estimate the risk price, we adopt a non-parametric method; the minimum norm pricing kernel method under the LOP (Law of One Price) constraint. For the estimation, we use 17 industry sorted portfolios provided by the KRX (Korea Exchange). Additionally, the monthly returns of the 17 industry sorted portfolios, from July 2000 to June 2014, are utilized as data samples. We set 120 months (10 years) as the estimation window, and estimate the risk prices from July 2010 to June 2014 by month. Moreover, we analyze correlation between any of the two industry portfolios within the 17 industry portfolios to suggest further economic implications of the risk price we estimate. Results - According to our results, the risk price in the Korean stock distribution market shows a decline over the period of July 2010 to June 2014 with statistical significance. During the period of the declining risk price, the average correlation level between any of the two industry portfolios also shows a decrease, whereas the standard deviation of the average correlation shows an increase. The results imply that the amount of systematic risk in the Korea stock distribution market has decreased, whereas the amount of industry-specific risk has increased. It is one of the well known empirical results that correlation and uncertainty are positively correlated, therefore, the declining correlation may be the result of decreased global economic uncertainty. Meanwhile, less asset correlation enables investors to build portfolios with less systematic risk, therefore the investors require lower risk premiums for the efficient portfolio, resulting in the declining risk price. Conclusions - Our results may provide evidence of reduction in global systemic risk or economic uncertainty in the Korean stock distribution market. However, to defend the argument, further analysis should be done. For instance, the change of global uncertainty could be measured with funding costs in the global money market; subsequently, the relation between global uncertainty and the price of risk might be directly observable. In addition, as time goes by, observations of the risk price could be extended, enabling us to confirm the relation between the global uncertainty and the effect of quantitative easing. These topics are beyond our scope here, therefore we reserve them for future research.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.31-36
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• 2021

As the global economy stagnated due to the Corona 19 virus from Wuhan, China, most countries, including the US Federal Reserve System, introduced policies to boost the economy by increasing the amount of money. Most of the stock investors tend to invest only by listening to the recommendations of famous YouTubers or acquaintances without analyzing the financial statements of the company, so there is a high possibility of the loss of stock investments. Therefore, in this research, I have used artificial intelligence deep learning techniques developed under the existing automatic trading conditions to analyze and predict macro-indicators that affect stock prices, giving weights on individual stock price predictions through correlations that affect stock prices. In addition, since stock prices react sensitively to real-time stock market news, a more accurate stock price prediction is made by reflecting the weight to the stock price predicted by artificial intelligence through stock market news text mining, providing stock investors with the basis for deciding to make a proper stock investment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.474-477
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• 2013

As the market-based spectrum policy is introduced, an interest in the economic value of the frequency is increasing. Research and practical applications concerning the methodology for the estimation of the economic value of the frequency and its determinants are actively engaged, which are used for setting a reserve price and bid price of spectrum auction and a spectrum clearance cost. In this study, by the analysis of the spectrum valuation methodology, we derive the changes in the factors affecting the valuation and propose to apply improved. In the model frequency value is consist of technical value, commercial value and strategic value, we find the dynamics of fluctuation factors and suggest how to apply them to spectrum policy.

• Current Photovoltaic Research
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• v.5 no.3
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• pp.100-104
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• 2017

This paper analyzes the correlation between Net Benefit Test (NBT) and System marginal price (SMP), which has a significant impact on the allocation of demand response (DR) resources in resource scheduling and commitment (RSC) process, based on the performance data of the demand resource market which has been established in 2014. Demand resources compete with generation resources in the RSC process, and it is prescribed to use demand resources only when net benefit occurs. Analysis result shows that the larger the SMP than the Net Benefit Threshold Price (NBTP), the more the winning bid of demand response resource was. It is interpreted that the introduction of NBT in DR market is justified. The demand resource market has been steadily growing. It is required to expand the scope of resources up to the small-sized DR, and to expand the functionalities of demand resources not only in the current energy market but also in the reserve market in the future. In order for that, institutional improvements are required.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2004.05a
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• pp.113-117
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• 2004

We need the contingency cost in order to deal with the uncertainty to be accompanied inevitably at the construction and an every kind risk not to forecast in advance. And also the contingency colt needed for the change order and we need it for reduction of the delay and reduce the trouble between owner and constructor. This study, through checking and analyzing the risk factor, in the step of domestic construction, suggests optimal management reserve to specific business about the contract type and the scale. The main results of this research are summarized as follow. First, I investigated the recognition about the contingency cost, grasped the risk to be happened at the construction step and found out the frequency occurrence, through making up question to engineer are carrying out their job in the domestic construction. Second, I computed optimal contingency cost rate by the statistics investigation, and proposed an improvement plan and problem when compute a contingency cost.

• Proceedings of the KIPE Conference
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• 2013.11a
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• pp.239-240
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• 2013

The increased demand for conventional energy sources, and international oil price rises are driving societies toward research and development of renewable energy. A large number of their installations and penetrations will bring an instability distribution power system. Also, load concentration problem at specific time can cause the shortage of power reserve margin. To deal with these problems, the development of energy storage systems (ESS) is required. This paper proposes the 1MW grid-connected ESS with Li-ion battery and power conditioning system (PCS). The performances of the 1MW grid-connected ESS are evaluated and verified with the PSCAD/EMTDC based simulation test.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.83-88
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• 2001

To get the items that a buyer wants in Internet auction. he must search for the items through several auction sites. When the bidding starts, he(the buyer) needs to connect to these auction sites frequently so that he can monitor the bid stats and re-bid. A reserve-price auction reduces the number of connections, but this limits the user's bidding strategy. Another problem is equity between the buyer and the seller. Both the buyer and the seller should profit together within proper limits. In this paper, we propose an auction agent system using a collaborative mobile agent and a brokering mechanism called MoCAAS (Mobile Collaborative Auction Agent System), which mediates between the buyer and the seller and executes bidding asynchronously and autonomously. This reduces connection costs. offers more intelligent bidding and solves the equity problem.

• Journal of Communications and Networks
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• v.12 no.2
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• pp.114-121
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• 2010

In this paper, an auctioning strategy is proposed for cellular networks that ensures net energy savings. The pricing scheme, in conjunction with a two dimensional bid structure, incentivizes cooperation at the terminal nodes for better interference management at receivers and for cooperative relaying. It is shown that, for the proposed auctioning strategy, network operators are guaranteed revenue gains, mobile nodes' dominant strategy is to bid their true valuation of their energy resources, and overall effective energy gains occur under the assumption of a reserve price for bidding. Simulation results show that significant energy savings can be achieved by employing this auctioning mechanism for a 3G cellular set-up.