• Title/Summary/Keyword: volatility model

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The Analysis and Comparison of the Hedging Effectiveness for Currency Futures Markets : Emerging Currency versus Advanced Currency (통화선물시장의 헤징유효성 비교 : 신흥통화 대 선진통화)

  • Kang, Seok-Kyu
    • The Korean Journal of Financial Management
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    • v.26 no.2
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    • pp.155-180
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    • 2009
  • This study is to estimate and compare hedging effectiveness in emerging currency and advanced currency futures markets. Emerging currency futures includes Korea won, Mexico peso, and Brazil real and advanced currency futures is Europe euro, British pound, and Japan yen. Hedging effectiveness is measured by comparing hedging performance of the naive hedge model, OLS model, error correction model and constant condintional correlation bivariate GARCH(1, 1) hedge model based on rolling windows. Analysis data is used daily spot and futures rates from January, 2, 2001 to March. 10, 2006. The empirical results are summarized as follows : First, irrespective of hedging period and model, hedging using Korea won/dollar futures reduces spot rate's volatility risk by 97%. Second, Korea won/dollar futures market produces the best hedging performance in emerging and advanced currency futures markets, i.e. Mexico peso, Brazil real, Europe euro, British pound, and Japan yen. Third, there are no difference of hedging effectiveness among hedging models.

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A study on the estimation of onion's bulb weight using multi-level model (다층모형을 활용한 양파 구중 추정 연구)

  • Kim, Junki;Choi, Seung-cheon;Kim, Jaehwi;Seo, Hong-Seok
    • The Korean Journal of Applied Statistics
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    • v.33 no.6
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    • pp.763-776
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    • 2020
  • Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.

A Comparative study on smoothing techniques for performance improvement of LSTM learning model

  • Tae-Jin, Park;Gab-Sig, Sim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.1
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    • pp.17-26
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    • 2023
  • In this paper, we propose a several smoothing techniques are compared and applied to increase the application of the LSTM-based learning model and its effectiveness. The applied smoothing technique is Savitky-Golay, exponential smoothing, and weighted moving average. Through this study, the LSTM algorithm with the Savitky-Golay filter applied in the preprocessing process showed significant best results in prediction performance than the result value shown when applying the LSTM model to Bitcoin data. To confirm the predictive performance results, the learning loss rate and verification loss rate according to the Savitzky-Golay LSTM model were compared with the case of LSTM used to remove complex factors from Bitcoin price prediction, and experimented with an average value of 20 times to increase its reliability. As a result, values of (3.0556, 0.00005) and (1.4659, 0.00002) could be obtained. As a result, since crypto-currencies such as Bitcoin have more volatility than stocks, noise was removed by applying the Savitzky-Golay in the data preprocessing process, and the data after preprocessing were obtained the most-significant to increase the Bitcoin prediction rate through LSTM neural network learning.

A Study on Risks and Returns Using A Housing Capital Asset Pricing Model (CAPM): the Case of Three Gangnam Districts Apartment Market in Seoul (주택 자본자산가격결정모형(Capital Asset Pricing Model)을 활용한 위험과 수익 분석: 서울 강남 3개구 아파트시장의 경우)

  • Lee, Jong-Ah;Jeong, Jun-Ho
    • Journal of the Economic Geographical Society of Korea
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    • v.13 no.2
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    • pp.234-252
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    • 2010
  • This paper examines the tendency of housing assets to become increasingly quasi-financial assets by analyzing the relationships between risks and returns in three Gangnam districts (Gangnam-gu, Seocho-gu and Songpa-gu) apartment markets in Seoul, especially for the apartments to be reconstructed, capitalizing upon some capital asset pricing models (CAPM). A single factor CAPM model shows positive relationships between risks and returns regardless of the types of apartments in three Gangnam districts. Multi-factors CAPM models also confirm that the market and SMB (small minus big) factors are positively related to the rate of returns regardless of the types of apartments. However, the unsystematic risk factor is found to be statistically positive especially for the apartments to be reconstructed, while the momentum factor is dependent upon the regression models used. An analysis on some portfolios classified by the size of apartments and price volatility and/or beta values suggests that there are the positive linear relationships between risks and returns and the SMB factor is clearly found to be significant in determining the rate of returns. In particular, housing assets are highly highlighted as investment goods and/or quasi financial assets for the apartments to be constructed in the Gangnam housing.

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VaR and ES as Tail-Related Risk Measures for Heteroscedastic Financial Series (이분산성 및 두꺼운 꼬리분포를 가진 금융시계열의 위험추정 : VaR와 ES를 중심으로)

  • Moon, Seong-Ju;Yang, Sung-Kuk
    • The Korean Journal of Financial Management
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    • v.23 no.2
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    • pp.189-208
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    • 2006
  • In this paper we are concerned with estimation of tail related risk measures for heteroscedastic financial time series and VaR limits that VaR tells us nothing about the potential size of the loss given. So we use GARCH-EVT model describing the tail of the conditional distribution for heteroscedastic financial series and adopt Expected Shortfall to overcome VaR limits. The main results can be summarized as follows. First, the distribution of stock return series is not normal but fat tail and heteroscedastic. When we calculate VaR under normal distribution we can ignore the heavy tails of the innovations or the stochastic nature of the volatility. Second, GARCH-EVT model is vindicated by the very satisfying overall performance in various backtesting experiments. Third, we founded the expected shortfall as an alternative risk measures.

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Trend/Cycle Decomposition Using DSGE Models (DSGE 모형을 이용한 추세와 경기순환변동분의 분해)

  • Hwang, Youngjin
    • KDI Journal of Economic Policy
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    • v.34 no.4
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    • pp.117-156
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    • 2012
  • This paper decomposes and estimates trend/cyclical components of some key macro variables-GDP, inflation, and interest rate, using a simple DSGE model along with flexible trend specification. The extracted cyclical components of output and interest rate are similar to HP-filtered counterparts, despite some differences in persistence and volatility, while inflation resembles that from BK filtering. This implies that the usual practice of applying a single filtering method to the data of interest may be problematic. When the baseline model is extended to incorporate consumption habit and price indexation, habit turns out to be important in explaining the persistence of business cycles. Comparison of several alternative models shows that the usual practice of estimation of DSGE model using filtered data leads to biased results. Finally, various sensitivity analyses illustrate that (1) allowing for correlation between structural cyclical shocks and trend shocks and (2) including irregular components (in inflation rate) may deliver interesting/important implication for gap estimates.

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Estimating Profitability of Private Finance Investment Using Real Option : Quantifying Value of Overturn Share Ratio and Minimum Revenue Guarantee (실물옵션에 의한 민간투자사업 사업타당성 평가 : 초과수익분배비율 및 최소수입보장비율 가치 정량화)

  • Jung, Woo-Yong;Koo, Bon-Sang;Han, Seung-Heon
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2008.11a
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    • pp.606-609
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    • 2008
  • Traditionally, the feasibility of the private investment is determined by NPV(Net Presented Value) based on DCF(Discounted Cash Flow) and the volume of government's subsidiary without quantifying the effect of overturn share ratio and MRG(Minimum Revenue Guarantee), these variables which can seriously effect on the economic feasibility. One of the most important reasons why these variables are not underestimated is that the quantifying methods are insufficiently or so complicatedly studied to apply practically the real project. Therefore, this study suggests the modified binominal option model to estimate the overturn share ratio and MRG and estimates how much these variables impact the private investment. Also, these results are helpful to estimate how much the government's subsidiary can be reduced.

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Investigation of the Optical and Cloud Forming Properties of Pollution, Biomass Burning, and Mineral Dust Aerosol

  • Lee Yong-Seop
    • Proceedings of the Korea Air Pollution Research Association Conference
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    • 2006.04a
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    • pp.55-56
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    • 2006
  • This thesis describes the use of measured aerosol size distributions and size-resolved hygroscopic growth to examine the physical and chemical properties of several particle classes. The primary objective of this work was to investigate the optical and cloud forming properties of a range of ambient aerosol types measured in a number of different locations. The tool used for most of these analyses is a differential mobility analyzer / tandem differential mobility analyzer (DMA / TDMA) system developed in our research group. To collect the data described in two of the chapters of this thesis, an aircraft-based version of the DMA / TDMA was deployed to Japan and California. The data described in two other chapters were conveniently collected during a period when the aerosol of interest came to us. The unique aspect of this analysis is the use of these data to isolate the size distributions of distinct aerosol types in order to quantify their optical and cloud forming properties. I used collected data during the Asian Aerosol Characterization Experiment (ACE-Asia) to examine the composition and homogeneity of a complex aerosol generated in the deserts and urban regions of China and other Asian countries. An aircraft-based tandem differential mobility analyzer was used for the first time during this campaign to examine the size-resolved hygroscopic properties of particles having diameters between 40 and 586 nm. Asian Dust Above Monterey (ADAM-2003) study was designed both to evaluate the degree to which models can predict the long-range transport of Asian dust, and to examine the physical and optical properties of that aged dust upon reaching the California coast. Aerosol size distributions and hygroscopic growth are measured in College Station, TX to investigate the cloud nucleating and optical properties of a biomass burning aerosol generated from fires on the Yucatan Peninsula. Measured aerosol size distributions and size-resolved hygroscopicity and volatility were used to infer critical supersaturation distributions of the distinct particle types that were observed during this period. The predicted CCN concentrations were used in a cloud model to determine the impact of the different aerosol types on the expected cloud droplet concentration. RH-dependent aerosol extinction coefficients are calculated at a wavelength of 550 nm.

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Generation of Corporate risk Contents using Financial Data (국제경쟁력 강화를 위한 중소규모기업 부실예측 콘텐츠)

  • Kim, Young-Sook
    • Proceedings of the Korea Contents Association Conference
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    • 2007.11a
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    • pp.951-953
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    • 2007
  • Generation of Corporate risk Contents using Financial Data The purpose of this paper is to capture risk profiles of smaller-sized Korean firms vis-$\grave{a}$-vis larger-sized firms during the Asian financial crisis. For this purpose, risk profiles are provided by estimating expected default risks and by tracking how these have changed during this period with respect to their magnitude, volatility, and sensitivity measures. Methodology used in this study employs the Black-Scholes-Merton model for producing estimates of default risks. And the conventional trans-log function is utilized for obtaining sensitivity measures of the estimated default risks. According to empirical evidence obtained here, it is revealed that contractions of corporate loans associated with IMF austerity policy was the main factor responsible for the drastic change in the default risk profile of Korean firms after occurrence of the Asian financial crisis.

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Application to the Stochastic Modelling of Risk Measurement in Bunker Price and Foreign Exchange Rate on the Maritime Industry (확률변동성 모형을 적용한 해운산업의 벙커가격과 환율 리스크 추정)

  • Kim, Hyunsok
    • Journal of Korea Port Economic Association
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    • v.34 no.1
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    • pp.99-110
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    • 2018
  • This study empirically examines simple methodology to quantify the risk resulted from the uncertainty of bunker price and foreign exchange rate, which cause main resources of the cost in shipping industry during the periods between $1^{st}$ of January 2010 and $31^{st}$ of January 2018. To shed light on the risk measurement in cash flows we tested GBM(Geometric Brownian Motion) frameworks such as the model with conditional heteroskedasticity and jump diffusion process. The main contribution based on empirical results are summarized as following three: first, the risk analysis, which is dependent on a single variable such as freight yield, is extended to analyze the effects of multiple factors such as bunker price and exchange rate return volatility. Second, at the individual firm level, the need for risk management in bunker price and exchange rate is presented as cash flow. Finally, based on the scale of the risk presented by the analysis results, the shipping companies are required that there is a need to consider what is appropriate as a means of risk management.