• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.503-519
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• 2005

Cointegration test is usually performed under the assumption that the cointegrating vector is constant for the whole sample period. Most previous studies have used conventional cointegration methods in testing for a stable long-run equilibrium relation among related variables. However they have overlooked that the long-run equilibrium may not the unique and the stable relation may not be guaranteed. This study develops the additional statistical tests for the stability of the estimated cointegrating vector. Three tests for the parameter stability of a cointegrated regression model are utilized and applied to identify the types of variations in the long-run relation between the domestic unemployment and the rotated macroeconomic variables of interest. The present paper finds that, there exists a stable but, time-varying long-run relation between those. The observed variation in cointegrating relations is generally characterized by a discrete one-time shift, rather than a gradually evolving random walk process which is attributable to the IMF financial and economic crisis.

• Journal of the Korean Geotechnical Society
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• v.25 no.2
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• pp.25-35
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• 2009

Slope failures are one of the significant disasters which causes lots of human casualties and huge financial losses every year. Previous researches on the slope failure have indicated that most accidents are closely related to the pore water pressure in the slope due to rainfall during the rainy seasons or stormy weather conditions. It would be therefore appropriate to consider the effect of pore water pressure in the design of slopes. As the existing slopes are generally reinforced by plants and other slope protecting measures, their boundary conditions are highly complicated. In this paper an attempt to develop a new modeling and analysis technique of slopes is proposed by including pore water pressure and adopting the coupled finite element method. Non-reinforced and reinforced slope models are considered. Representative analysis showed that the numerical modeling considering pore water pressure is appropriate in slope stability analysis. Flow behavior in the slopes is identified for various hydraulic boundary conditions. It is also shown that the effect of pore water pressure on slope stability is significant.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.519-526
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• 2018

Recently, interest in virtual money has been growing. There is also a view that it is safe to pursue traditional assets, and some wealth experts are expecting positive changes in the financial society that can be diversified due to virtual money. Since the virtual money market is an immature situation and the stability of the virtual money is not yet secured, the potential risk of the transaction of the virtual money is highly likely to occur. In this study, we try to derive important priorities by deriving the evaluation factors that can contribute to the stabilization of the virtual currency in the market transaction. The main evaluation factors were selected from the viewpoint of the transaction environment, the technical viewpoint, and the profit viewpoint, and the importance of the subordinate factors was analyzed by applying AHP.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.251-261
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• 2020

The paper examines the role of some determinants of economics, politics and institutions on the budget deficit volatility in some countries of the Association of South East Asian Nations (ASEAN) such as Indonesia, Thailand and Vietnam. The paper uses the fixed effects model (FEM) and the random effects model (REM) to investigate panel data of these countries in the period of 1990-2018. Moreover, the study also explores ordinary least square (OLS) to analyze time-series data for each country in the same period to make comparison among them. The economic data is collected from international financial statistics and world development indicators. The data on political variables are collected from International Country Risk Data Guide (ICRG). The empirical results both confirm that corruption and political stability are important indicators of budget deficit. Besides, the paper suggests authorities should pay more attention on improving the institutional setup of the economy in order to avoid high and unstable deficit. The findings offer new insight on the budget deficit in essence and suggest that the most important thing need to be done ahead is to strongly implement anti-corruption actions. By doing so, the status of budget deficit would be remarkably improved immediately.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.772-775
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• 2008

As the wireless communication technology developed, the Electric Commerce using a mobile was activated. WPKI was developed in order to guarantee the stability of the Electric Commerce but it is difficult to be ensured for the safe PKI service which is the same at the wire communication in the technical because of restriction of the mobile terminal. In this paper, we propose the authentication system for the electronic financial service which is safe and is effective in consideration of the restrictive characteristic of the mobile terminal. Moreover, the encryption algorithm for the safe electronic signature is proposed. In WPKI, this makes the cross certification of each certificate authority possible. Moreover, a stability was enhanced through the signature authentication using KCDSA and SEED algorithm.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.59-72
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• 2020

This paper examines whether lending structure can lower credit risk by employing econometric techniques of panel data for the Vietnamese banking system at the bank level used by economic sectors from 2011 to 2016. New light is being shed on assessing the impact of each industry's debt outstanding on credit risk. Adopting findings from previous studies, we assess credit risk from two different sources, including loan loss provision and non-performing loan. Moreover, we also focus on observing lending structure in many different aspects, from concentrative levels to the short-term and long-term stability levels of lending structure. The Generalized Method of Moments (GMM) estimator was applied to analyze the relationship between concentration and banking risks. In general, the results show that lending concentration may decrease credit risk. It is interesting to observe that the Vietnamese commercial bank lending portfolios have, on average, higher levels of diversity across different sectors. In particular, the increase in hotel and restaurant lending contributes to decrease credit risk while the lending portfolios of banks in agriculture, electricity, gas and water increase credit risk. This study suggests the need for further analysis and research about portfolio risks in lending activities for maintaining efficiency and stability in the commercial banking system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.1-9
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• 2017

Recently, Bitcoin which is digital currency and cryptocurrency is getting worldwide attention since Bitcoin has an ability to replace legal tender unlike other existing cyber currency. Especially, most Bitcoin trading is done between two traders such as P2P method and it does not require a third-party to make sure reliability and it records every transaction details, so it is more transparent then traditional financial trade, so the number of users is increasing. However, Bitcoin, which has been recognized for transparency, confidentiality and stability among traders has recently been threatened by illegal transactions such as money laundering and the attack on the exchange. These threats to Bitcoin are becoming social problems. At first, it seems that most of the digital currency is difficult to get hacked due to the Blockchain technology. However, threats such as digital money leaks by user account hacking and paralyzing the servers are increasing. In this paper, it will examine the features of the Bitcoin and the threatening elements to secure marketability of digital currency such as Bitcoin and receive more interest from public in domestic. The paper will examine the problems of Blockchain technology on speculative transactions and fraudulent behavior by analyzing the problems of Bitcoin transaction. Lastly, it will propose ways to make transparent and secure digital currency transactions.

• Earthquakes and Structures
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• v.17 no.3
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• pp.307-315
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• 2019

Building prediction and control theory have been drawing the attention of many scientists over the past few years because design and control efficiency consumes the most financial and energy. In the literature, many methods have been proposed to achieve this goal by trying different control theorems, but all of these methods face some problems in correctly solving the problem. The Evolutionary Bat (EB) Algorithm is one of the recently introduced optimization methods and providing researchers to solve different types of optimization problems. This paper applies EB to the optimization of building control design. The optimized parameter is the input to the fuzzy controller, which gives the status response as an output, which in turn changes the state of the associated actuator. The novel control criterion for guarantee of the stability of the system is also derived for the demonstration in the analysis. This systematic and simplified controller design approach is the contribution for solving complex dynamic engineering system subjected to external disturbances. The experimental results show that the method achieves effective results in the design of closed-loop system. Therefore, by establishing the stability of the closed-loop system, the behavior of the closed-loop building system can be precisely predicted and stabilized.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1-10
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• 2021

This study examines the dynamic pattern of the exchange rate volatilities of the ASEAN-5 currencies from January 2006 to August 2020. The exchange rates applied in this study comprise bilateral and effective exchange rates in order to investigate the influence of the US dollar on the stability of the ASEAN-5 currencies. Since a volatility model employed in this study is a natural cubic spline volatility model, the Monte Carlo simulation is consequently conducted to determine an appropriate criterion to select a number of quantile knots for this model. The simulation results reveal that, among four candidate criteria, Generalized Cross-Validation is a suitable criterion for modeling the ASEAN-5 exchange rate volatilities. The estimated volatilities showed the inconstant dynamic patterns reflecting the uncertain exchange rate risk arising in international transactions. The bilateral exchange rate volatilities of the ASEAN-5 currencies to the US dollar are more variable than their corresponding effective exchange rate volatilities, indicating the influence of the US dollar on the stability of the ASEAN-5 currencies. The findings of this study suggest that the natural cubic spline volatility model with the quantile knots selected by Generalized Cross-Validation is practical and can be used to examine the dynamic patterns of the financial volatility.