• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.10
• /
• pp.591-599
• /
• 2020

This study examines how the health of the banks in ASEAN-3 countries namely Indonesia, Malaysia and Thailand respond to the change in exchange rates and foreign interest rates in four large economies. The transmissions of the two external factors through domestic factors in each ASEAN-3 countries eventually affects Non-Performing Loan (NPL) of commercial banks. This study uses the monthly time series data and the renowned Structural Vector Autoregressive (VAR) model comprising five variables, namely exchange rate, foreign interest rate, domestic interest rate, money supply, and non-performing loan (NPL). The results indicate that there are different effects between ASEAN-3 countries, which can be classified as short-run effect and long-run effect. In the long run effect, external factors have a dominant role in determining NPL in ASEAN-3 countries. Yuan has the biggest effect on Malaysia's NPL, while Indonesia is more affected by European interest rates rather than the fluctuation of the US currency and China's interest rates. Among ASEAN-3 countries, Malaysia is the one that is the most vulnerable to external factors. While Thailand's NPL is affected dominantly by domestic factors. This study shows that the Fed Funds Rate (US official interest rate) is not always the dominant factor affecting the health of domestic banks in ASEAN-3.

• International Commerce and Information Review
• /
• v.10 no.2
• /
• pp.373-390
• /
• 2008

본 논문은 국내세법, 한 중 조세협약, 중국세법을 근거하여 특수목적회사(SPC), 사모펀드(PEF) 등의 간접투자 방식과 직접투자 방식에 대한 투자시뮬레이션을 활용하여 최상의 투자형태 협상전략을 제시하였다. 분석결과 중국내 고정사업장이 없는 경우 홍콩과 같은 조세회피지역에 특수목적회사를 설립하여 중국에 투자하는 형태가 직접투자 혹은 국내에 PEF 설립을 통한 투자보다 더 합리적이었다. 더욱이 특수목적회사는 국내의 여러 가지 규제에서 벗어나 자유로운 펀드운용과 새로운 투자추진시 국내과실 송금 처리절차를 거치지 않고 재투자가 가능하다는 점을 포함하여 다양한 장점을 가지고 있었다. 중국 등의 해외투자 고려시 조세회피지역에 특수목적회사를 설립하고 이를 통해 투자를 실행하는 것이 가장 효율적인 방안임을 고려하여 투자방식과 JV협상을 진행하여야 할 것이다.

• The Journal of Asian Finance, Economics and Business
• /
• v.4 no.2
• /
• pp.5-17
• /
• 2017

The main objective of the study is to measure the vulnerability of Indonesia's financial system stability in response to external shocks, including from regional economies namely three biggest Indonesia major trading partners (China, the U.S and Japan) and other external factors (oil price and the federal funds rate). Using Autoregressive Distributed Lag (ARDL) model and Orthogonalized Impulse Response Function (OIRF) with quarterly data over the period Q4 2002 - Q1 2016, results confirm that, 1) oil price response has the largest effect to Indonesia financial stability system and the effect period is the longest compared to others, represented by NPL and IHSG; 2) among those three economies, only China's economic growth has significantly positive effect to Indonesia financial stability system. Based on the findings it is better for the authorities to: 1) Diversify international trade commodities by decreasing share of oil, gas, and mining export and boosting other potential sectors such as manufacture, and fisheries; 2) Ensure the survival of Indonesia large coal exporter companies without neglecting burden of national budget; and 3) Create buffer for demand shock from specific countries by diversifying and increasing share of trading from other countries particularly from ASEAN member states.

• International Journal of Knowledge Content Development & Technology
• /
• v.11 no.3
• /
• pp.29-44
• /
• 2021

The study provides a quantitative and qualitative description of global research in the domain of quantum machine learning (QML) as a way to understand the status of global research in the subject at the global, national, institutional, and individual author level. The data for the study was sourced from the Scopus database for the period 1999-2020. The study analyzed global research output (1374 publications) and global citations (22434 citations) to measure research productivity and performance on metrics. In addition, the study carried out bibliometric mapping of the literature to visually represent network relationship between key countries, institutions, authors, and significant keyword in QML research. The study finds that the USA and China lead the world ranking in QML research, accounting for 32.46% and 22.56% share respectively in the global output. The top 25 global organizations and authors lead with 35.52% and 16.59% global share respectively. The study also tracks key research areas, key global players, most significant keywords, and most productive source journals. The study observes that QML research is gradually emerging as an interdisciplinary area of research in computer science, but the body of its literature that has appeared so far is very small and insignificant even though 22 years have passed since the appearance of its first publication. Certainly, QML as a research subject at present is at a nascent stage of its development.