• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.243-266
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• 2006

This paper tests cross hedging performance of the KOSPI 200 stock index futures to hedge the downside risk of the KOSPI, KOSPI 200 and KOSDAQ50 spot market. For this purpose we introduce the minimum variance hedge model, bivariate GARCH(1,1) and EGARCH(1,1) model as hedge models. The main results are as follows; First, we find that the direct hedge performance of KOSPI 200 index futures is better than those of indirect hedge performance. second, in case or cross hedge performance the hedge effect of KOSPI 200 stock index futures market against KOSPI 200 stock index spot market is relatively better than those of KOSPI 200 index futures against KOSPI and KOSDAQ spot position. Third, for the out-sample, hedging effectiveness of the risk-minimization with constant hedge ratios is higher than those of the time varying bivariate GARCH(1,1) and EGARCH(1,1) model. In conclusion, investors are encouraged to use simple risk-minimization model rather than the time varying hedge models like GARCH and EGARCH model to hedge the position of the Korean stock index cash markets.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.279-281
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• 2012

Hedge는 불확실한 언어의 기술로서 추측성 글이나, 자신의 생각을 표현하는 글, 또는 공손함을 나타내는 글 등에서 자주 표현되는 어휘를 말한다. 본 논문에서는 한국어 Hedge 인식률을 높이기 위해 기계학습 방법을 사용하여 실험을 하였다.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.1
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• pp.31-34
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• 2006

The experiment was conducted to determine the effects of cutting interval and cutting height on the yield and nutrient composition of hedge lucerne (Desmanthus virgatus) when grown on a sandy soil in the Northeast of Thailand. The cutting intervals compared were 30, 40 and 50 days between harvests and the cutting heights 30, 40 and 50 cm above ground level. The experiment was a $3{\times}3$ factorial layout in a randomized complete block design with 4 replications-giving a total of 36 plots each $3{\times}3m^2$. Harvested plant material was weighed, dried and the ground subsamples taken for analyses of crude protein (CP), crude fiber (CF), ash, ether extract (EE) and nitrogen-free extract (NFE). At the last harvest the hedge lucerne samples were separated to determine leaf to stem ratios and then analyzed for nutrient composition in the leaf and stem. Results showed that increasing the cutting interval (i.e. advancing age of maturity) increased dry matter and nutrient yields significantly. In terms of nutrient content, it also increased the crude fiber, ash, ether extract and nitrogen free extract percent in the plant. However, crude protein percent was markedly decreased as the cutting interval increased. Increasing cutting height had no effect on dry matter yield and yields of nutrients, but in terms of nutrient content, it increased crude protein and ash content, but decreased crude fiber content. The percent EE and NFE in the plant was unaffected by cutting height. From the results presented it is clear that cutting a stand of hedge lucerne every 40 to 50 days will achieve greater dry matter and nutrient yields than cutting more frequently, at 30 days. The cutting height at harvest, whether 30, 40 or 50 cm above ground level had no effect on dry matter or nutrient yields of hedge Lucerne. Hedge lucerne therefore offers the Thai poultry farmer a useful alternative protein supplement for poultry diets rather than relying on the more expensive soybean meal. As it can be readily and successfully grown on a range of soil types and climates throughout Thailand, hedge lucerne also offers the Thai farmer a valuable additional source of income.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1189-1198
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• 2015

For the effects of the global financial crisis cause hedge funds to have a strong influence on financial markets, it is needed to study new approach method to predict hedge fund survival. This paper proposes to organize fuzzy neural network using hedge fund data as input to predict hedge fund survival. The variables of hedge fund data are ambiguous to analyze and have internal uncertainty and these characteristics make it challenging to predict their survival from the past records. The object of this study is to evaluate the predictability of fuzzy neural network which uses grades of membership to predict survival. The results of this study show that proposed system is effective to predict the hedge funds survival and can be a desirable solution which helps investors to support decision-making.

• Korean System Dynamics Review
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• v.15 no.2
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• pp.97-131
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• 2014

The purpose of this study is to analyze Foreign Exchange(FX) exposure and FX hedge strategy based on the systems thinking perspective using causal loop diagrams. FX exposure has been a critical issue on a business management. Many studies in Korea have researches on variables which make effects to the company value. This study displays causal loop diagrams(CLDs) on these issues. In order to make CLD more objective, most causalities are articulated from recent 72 studies (1998~2013) of domestic top journals. This approach is valuable in that it is the first try to draw all the causalities from various literature review regarding FX exposure and FX hedge strategy. This study is expected to make a useful and basic material to research the financial issues of corporate, as the first research to dynamically understand FX exposure and FX hedge strategy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.3
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• pp.133-146
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• 2015

This study is to investigate the causal relationship between exchange hedge and the net income of the shipbuilder through the unit root test and co-integration and vector autoregressive model(Vector Autoregressive Model: VAR). First, quarter net income of shipbuilders to order a unit root tests from 2000 to 2013 was used as a value after the Johnson transformation. In the same period, the return on bond futures(KTBF), three years bond yield(KTB3Y), America-Korea exchange differences are weekly data for each quarterly difference in value was converted by utilization, shipbuilding shares after log transformation which it was used. Also, structural change point investigation analysis to verify that looked to take advantage of the structural changes occur in the exchange hedge strategies affecting net income in the shipbuilding industry. Between the exchange hedge and net income of shipbuilders in structural change points detection and analysis showed that structural changes occur starting in 2004. In other words, strategy of shipbuilders about exchange hedge has occurred from "passive exchange hedge" to "active exchange hedge". The exchange hedge of the Korea shipbuilders through the estimation of the VAR was able to grasp that affect the profitability of mutual shipbuilders. Macroeconomic variables and stock prices could also check to see that affected the net income of the shipbuilding industry.

• The Journal of Information Systems
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• v.28 no.4
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• pp.333-358
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• 2019

Purpose The study aims to develop a data-based decision model for private bankers when recommending hedge funds to their customers in financial institutions. Design/methodology/approach The independent variables are set in two groups. The independent variables of the first group are aggressive investors, active investors, and risk-neutral type investors. In the second group, variables considered by private bankers include customer propensity to invest, reliability, product subscription experience, professionalism, intimacy, and product understanding. A decision-making variable for a private banker is in recommending a first-rate general private fund composed of foreign and domestic FinTech products. These contain dependent variables that include target return rate(%), fund period (months), safeguard existence, underlying asset, and hedge fund name. Findings Based on the research results, there is a 94.4% accuracy in decision-making when the independent variables (customer rating, reliability, intimacy, product subscription experience, professionalism and product understanding) are used according to the following order of relevant dependent variables: step 1 on safeguard existence, step 2 on target return rate, step 3 on fund period, and step 4 on hedge fund name. Next, a 93.7% accuracy is expected when decision-making uses the following order of dependent variables: step 1 on safeguard existence, step 2 on target return rate, step 3 on underlying asset, and step 4 on fund period. In conclusion, a private banker conducts a decision making stage when recommending hedge funds to their customers. When examining a private banker's recommendations of hedge funds to a customer, independent variables influencing dependent variables are intimacy, product comprehension, and product subscription experience according to a categorical regression model and artificial neural network analysis model.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1449-1466
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• 2014

In this paper, we consider a hedge portfolio based on futures of underlying asset. A classical way to estimate a hedge ratio for a hedge portfolio of a spot and futures is a regression analysis. However, a regression analysis is not capable of reflecting long-run equilibrium between a spot and futures and volatility clustering in the conditional variance of financial time series. In order to overcome such defects, we analyzed KOSPI200 index and futures using VECM-CC-GARCH model and computed a hedge ratio from the estimated conditional covariance-variance matrix. In real data analysis, we compared a regression and VECM-CC-GARCH models in terms of hedge effectiveness based on variance, value at risk and expected shortfall of log-returns of hedge portfolio. The empirical results show that the multivariate GARCH models significantly outperform a regression analysis and improve hedging effectiveness in the period of high volatility.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.827-832
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• 2001

In this paper, we propose a sequentially optimization method for fuzzy inference system using fuzzy equalization and linguistic hedge. The fuzzy equalization does not require the usual learning step for generating fuzy rules. However, it is too sensitive for the given input-output data set. So, we adopt a sequential scheme which sequentially optimizes the fuzzy inference system. Here, the parameters of fuzzy membership function obtained from the fuzzy equalization are optimized by the genetic algorithm, and then they are also modified to increase the performance index using the linguistic hedge. Finally, we applied it to rice taste data and got better results than previous ones.

• International Commerce and Information Review
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• v.9 no.3
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• pp.151-160
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• 2007

The purpose of this study is to estimate the risk premium hedge ratio in foreign exchange risk of the foreign exchange rate insurance. The applicants of exchange rate insurance and Korea Export Insurance Corporation will be facing the risk in change of currency and guaranteed currency’s swap point upon contract being made. Also upon making decision of hedging exchange rate insurance, the company will need to be aware of the risk causing due to change in swap point.