• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.15-25
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• 2020

This empirical research aims to identify the relationship between fiscal and financial macroeconomic fundamentals and the volatility of government bonds' borrowing cost in an emerging country - Vietnam. The study covers the period from July 2006 to December 2019 and it is based on a sample of 1-year, 3-year, and 5-year government bonds, which represent short-term, medium-term and long-term sovereign bonds in Vietnam, respectively. The Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model and its derivatives such as EGARCH and TGARCH are applied on monthly dataset to examine and suggest a significant effect of fiscal and financial determinants of bond yield volatility. The findings of this study indicate that the variation of Vietnam government bond yields is in compliance with the theories of term structure of interest rate. The results also show that a proportion of the variation in the yields on Vietnam government bonds is attributed to the interest rate itself in the previous period, base rate, foreign interest rate, return of the stock market, fiscal deficit, public debt, and current account balance. Our results could be helpful in the macroeconomic policy formulation for policy-makers and in the investment practice for investors regarding the prediction of bond yield volatility.

• The Journal of Asian Finance, Economics and Business
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• 제7권11호
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• pp.251-257
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• 2020

The study investigates the role of commodity prices and tax purpose recognition on bitcoin prices. Since the introduction of bitcoin in 2008, emphasis has focused on economists, policy-makers and analysts drastically increasing bitcoin's accessibility and commodity values (Dumitrescu & Firică, 2014). This study employs GARCH and EGARCH from ARCH/GARCH family on daily nature data. We measure the volatile behavior of bitcoin by employing auto-regressive conditional heteroscedasticity model with the aim to explore the relationship between major commodities and bitcoin volatility. We focus on major commodities like gold, silver, platinum, and crude oil to be regressed with bitcoin. The daily prices of commodities were retrieved from www.investing.com and bitcoin prices from www.coindesk.com for the period from 29April 2013 to 16 October 2018. Results confirmed the currency's long-term volatile behavior, which is due to its composition and market dynamics, whereas the existence of asymmetric information effect is not confirmed. Tax recognition by other countries may in future help in controlling the volatility as bitcoin is not a country-specific security. But, only silver impacts on volatility in comparison to oil prices and platinum, which is due to its similar features with gold. Eventually, bitcoin can be used for risk diversification and money making.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1999년도 추계학술대회 논문집
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• pp.63-69
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• 1999

The research trend of the simulation optimization has been focused on exploring continuous decision variables. Yet, the research in discrete decision variable area has not been fully studied. A new research trend for optimizing discrete decision variables ha just appeared recently. This study, therefore, deals with a discrete simulation method to get the system evaluation criteria required for designing a complex probabilistic discrete event system and to search the effective and reliable alternatives to satisfy the objective values of the given system through a on-line, single run with the short time period. Finding the alternative, we construct an algorithm which changes values of decision variables and a design alternative by using the stopping algorithm which ends the simulation in a steady state of system. To avoid the loss of data while analyzing the acquired design alternative in the steady state, we provide background for estimation of an auto-regressive model and mean and confidence interval for evaluating correctly the objective function obtained by small amount of output data through simulation with the short time period. In numerical experiment we applied the proposed algorithm to (s, S) inventory system problem with varying Δt value. In case of the (s, S) inventory system, we obtained good design alternative when Δt value is larger than 100.

• The Journal of Asian Finance, Economics and Business
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• 제6권1호
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• pp.121-128
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• 2019

This study analyses the relationship between the real estate market and economic growth in Vietnam, a country with a fledgling real estate market. Research data included economic growth rate and growth rate of the real estate market in Vietnam. The research used quarterly data for the period from 2005: Q1 to 2018: Q1. With the characteristics of Vietnam, there has been no real estate index up to now; therefore, the research used data on growth rates of the real estate market. In addition, the real estate market in Vietnam is still young, so the data series is very short, which is a limitation of this research. With qualitative and quantitative methods especially with the Vector Auto Regressive (VAR) model; the results of the study indicate new findings, unlike previous studies, including: (1) The real estate market positively impacts Vietnam's economic growth, most noticeably in the second quarter lag and the fourth quarter lag, and then its trend impacts inversely; (2) The real estate market and economic growth in Vietnam have fluctuated over time with many risks that are affected by the past shocks of these factors. From these findings, we proposed some managerial implications for managing the real estate market with economic growth in Vietnam sustainably.

• 한국측량학회지
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• 제39권5호
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• pp.289-295
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• 2021

Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.165-170
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• 2021

This paper examines the long-run relationship between financial development and economic growth. The effective function of financial development is crucial to promote the economic development of the country. To achieve the objective, this study used Gross Domestic Product as a dependent variable and Credit to The Private Sector, Ratio of the Gross Fixed Capital Formation to GDP, Trade, Consumer Price Index and Labour Force as an independent variable. Augmented Dickey-Fuller test statistic (ADF) to check the stationary. Bounds test for cointegration and Auto-Regressive Distributed Lag Models (ARDL) are used to check cointegrating relationship amongst the variables and causality between financial development and economic growth. Moreover, the Model selection method is Akaike Info Criterion (AIC). This result demonstrates that the labor force and trade hold a significantly negative relationship with economic growth. Nevertheless, inflation, Credit to The Private Sector, and Ratio of the Gross Fixed Capital Formation to GDP show a significantly positive relationship with economic growth. Therefore, there is a statistically significant relationship between Financial Development and Economic growth in Sri Lanka and the Sri Lankan government should reform its trade policies.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.111-122
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• 2021

The main purpose of the present research is to analyze the effects of trade, financial globalization, and technological progress on income inequality in the Indian economy over the period from 1982 to 2018. For this purpose, the study uses economic growth, financial globalization, trade openness, technological development, and economic inequality variables with appropriate proxies. The study employs the Auto Regressive Distributed Lag (ARDL) approach to co-integration and VECM based Granger causality approach to estimate both the short-run and long-run relationship and causality among variables. Using the ARDL bounds test, the study finds a long-run co-integrating relationship existing among the variables in the model. The study confirms the existence of a positive and significant impact of technological progress on income inequality. Further, globalization's limited impact reflects two offsetting tendencies; trade globalization is associated with a reduction in income inequality, while financial globalization is related to an increase in inequality. The results of VECM based Granger causality approach further confirm that technological progress, trade, and financial globalization causes income inequality both directly and indirectly through economic growth and inflation. In case of India, the results of this research can significantly facilitate stakeholders and policymakers in devising policies towards effective globalization and technological innovation for inclusive growth.

• The Journal of Asian Finance, Economics and Business
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• 제8권4호
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• pp.113-124
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• 2021

The study investigates how financial markets respond to a shock to tone and semantic similarity of the Bank of Thailand press releases. The techniques in natural language processing are employed to quantify the tone and the semantic similarity of 69 press releases from 2010 to 2018. The corpus of the press releases is accessible to the general public. Stock market returns and bond yields are measured by logged return on SET50 and short-term and long-term government bonds, respectively. Data are daily from January 4, 2010, to August 8, 2019. The study uses the Structural Vector Auto Regressive model (SVAR) to analyze the effects of unanticipated and temporary shocks to the tone and the semantic similarity on bond yields and stock market returns. Impulse response functions are also constructed for the analysis. The results show that 1-month, 3-month, 6-month and 1-year bond yields significantly increase in response to a positive shock to the tone of press releases and 1-month, 3-month, 6-month, 1-year and 25-year bond yields significantly increase in response to a positive shock to the semantic similarity. Interestingly, stock market returns obtained from the SET50 index insignificantly respond to the shocks from the tone and the semantic similarity of the press releases.

• 한국전산구조공학회논문집
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• 제25권4호
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• pp.331-338
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• 2012

현재 국내에서 EM-120에 의해 검측된 틀림 데이터는 매우 불규칙적인 형태를 나타내며 데이터 분석 시 다양한 문제점을 가지고 있다. 본 연구에서는 궤도의 효율적인 유지관리를 위해 검측된 틀림데이터의 특징과 문제점을 분석하고, 이를 보완할 수 있는 효율적인 처리 기법을 개발하였으며, 정제된 데이터의 ARIMA 분석을 통해 검측데이터와 계절 변화의 상관관계 분석을 수행하였다. 또한 회귀모형, 지수평활법, ARIMA 모형 등 다양한 예측 모델의 적용을 통해 검측 데이터의 시계열 분석을 수행하고, 궤도 틀림 데이터의 예측 모델에 적합한 최적 모델 선정과 관련한 연구를 수행하였다.

• 한국소음진동공학회논문집
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• 제24권4호
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• pp.348-356
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• 2014

To understand the relationship between road-traffic noise and urban components such as population, building, road-traffic and land-use, the city of Cheongju that already has road-traffic noise maps of daytime and nighttime was selected for this study. The whole area of the city is divided into square cells of a uniform size and for each cell, the urban components are estimated. A spatial representative noise level for each cell is determined by averaging out population-weighted facade noise levels for noise exposure population within the cell during nighttime. The relationship between the representative noise level and the urban components is statistically modeled at the cell level. Specially, we introduce a spatial auto regressive model and a spatial error model that turns out to explain above 85 % of the noise level. These findings and modeling methods can be used as a preliminary tool for environmental planning and urban design in modern cities in consideration of noise exposure.