This work studies the variability of flatfish sales revenue. The theoretical analysis draws functions for equilibrium price and quantity using expectation hypotheses. The functions include unpredictable phenomenon with dummy variable and GARCH. The equilibrium function, using adaptive expectation hypothesis, contains the independent variables of supply and demand, while the equilibrium function, embodying rational expectation hypothesis, includes only the independent variables of supply side, because the demand side disappears by the information extraction process theoretically, if economic subjects build the expectation rational. The empirical analysis shows: the variability of flatfish production has a spillover effect on the variability of revenue with the adaptive expectation hypothesis. In the case when the model has a rational expectation hypothesis, the variability of flatfish production has a spillover effect on the revenue (the mean equation of GARCH model). This study indicates that there is the variability in flatfish production and sales revenue, and the spillover effect between them. The result can help to build of the rational system for the fishery income stability.

본 연구는 국제원유시장과 아시아 주식시장(한국, 중국, 일본, 인도, 인도네시아, 필리핀, 말레이시아, 태국, 대만, 싱가포르, 베트남)간의 상관관계를 국면전환 관점에서 분석한다. 이를 위해 유가와 주가지수 간의 시간가 변 상관계수를 DCC-GARCH(1,1) 모형으로 추정하였고, 비선형 시계열 분석기법인 Smooth Transition Regression(STR) 모형을 활용해 구조적 변화의 비선형 특성과 상관관계의 강도를 파악하였다. 2002년 1월부 터 2016년 3월까지의 자료를 토대로 한 분석 결과, 국제유가와 아시아 주가지수간의 상관관계는 시간의 흐름에 따라 그리고 국가별로 상이한 움직임을 나타냈다. 또한 상관관계의 국면간 전환점과 전환속도를 측정하는 모수가 일부 국가에서 유의하게 추정되었다. 이러한 결과는 원유와 아시아 국가 주식으로 포트폴리오를 구성할 경우 상 관계수의 추정과정에서 비선형성과 강도를 고려해야 할 필요가 있음을 시사한다. 이에 본 논문은 방법론적으로 기존의 국제재무 문헌의 확장에 기여하며 주식시장과 원유시장의 관계자들에게도 포트폴리오 구성 및 시장예측과 관련한 실무적 시사점도 제공한다.

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 29 April 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.

In this paper, we propose the new time-varying coefficient GARCH-in-Mean model. The benefit of our model is to allow the risk-return parameter in the mean equation to vary over time. At the end of 2019 to the beginning of 2020, the world witnessed two shocking events: COVID-19 pandemic and 2020 oil price war. So, we decide to use the daily data from December 2, 2019 to May 29, 2020, which cover these two major events. The purpose of this study is to find the dynamic movement between risk and return in four major oil markets: Brent, West Texas Intermediate, Dubai, and Singapore Exchange, during COVID-19 pandemic and 2020 oil price war. For the European oil market, our model found a significant and positive risk-return relationship in Brent during March 26-April 21, 2020. For the North America oil market, our model found a significant positive risk return relationship in West Texas Intermediate (WTI) during March 12-May 8, 2020. For the Middle East oil market, we found a significant and positive risk-return relationship in Dubai during March 12-April 14, 2020. Lastly, for the South East Asia oil market, we found a significant positive risk return relationship in Singapore Exchange (SGX) from March 9-May 29, 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.

This study examines the behaviour of staple food price using Multivariate BEKK-GARCH Model. Understanding of staple food price behaviour is important for determining the unpredictability of staple food market and also for policy making. In this paper, we focus on the commodity prices of sugar, rice, soybean and wheat to examine the volatility behaviour of those commodities. The empirical results show that the own-volatility spillover are relatively significant for all food prices. The own-volatility spillover effect for sugar price is relatively large compared with the volatility spillover of other staple food commodities. The findings also highlight that the price volatility of wheat increases during food crisis more than it does when the condition is stable. Also, the own-volatility of rice and wheat in the period of the food crisis is significant and higher compared to the period before food crisis indicates that the past own-volatility effects during food crisis are relatively more difficult to predict because of the uncertainty and high price volatility. Policy recommendations that can be proposed based on the findings are: (1) a better trade agreement in food commodity trade, (2) Indonesia should not depend on wheat importation, and (3) early warning system to minimize food price volatility risks.