Personalized goal-based investing via multi-stage stochastic goal programming

In this paper, we propose a goal-based investment model that is suitable for personalized wealth management. The model only requires a few intuitive inputs such as size of wealth, investment amount, and consumption goals from individual investors. In particular, a priority level can be assigned to each consumption goal and the model provides a holistic solution based on a sequential approach starting with the highest priority. This allows strict prioritization by maximizing the probability of achieving higher priority goals that are not affected by goals with lower priorities. Furthermore, the proposed model is formulated as a linear program that efficiently finds the optimal financial plan. With its simplicity, flexibility, and computational efficiency, the proposed goal-based investment model provides a new framework for automated investment management services.     

Does local political support influence financial markets? A study on the impact of job approval ratings of political representatives on local stock returns

Using data on job approval ratings of governors, U.S. senators, and the president, we find that firms located in states with high approval ratings outperform firms located in states with low approval ratings by .64% per month. Furthermore, this relationship is stronger when investors are actively involved in politics, when local politicians are closer to the center of political power, for small firms that have a larger proportion of local investors, and for financially strong areas where investors are ready to execute investments in local stocks. Overall, our study shows that investors’ political sentiment is important in determining stock returns.     

South Korea’s outward direct investment and its dyadic determinants: Foreign aid,bilateral treaty and economic diplomacy

This study investigates the factors that affect South Korean outward foreign direct investment (FDI) in developing countries. Most previous studies focus on monadic factors and do not consider how and to what extent bilateral relationships between South Korea and the host countries affect the investment decisions of Korean firms. The current study finds that interstate factors such as South Korea's international investment treaties with and official development assistance to host countries have positive effects on FDI to these countries, while presidential visits have strong and statistically significant effects on FDI only in countries located in non-Asian regions, especially the African continent. The findings suggest that the effects of bilateral relations on South Korea's FDI vary depending on the geographic location of the host country.     

Industry Shock Expectations,Interindustry Linkages,and Merger Waves: Evidence from the Hospital Industry

It is well known that mergers often occur in waves, and this paper develops a new mechanism for merger waves: expectations over industry shocks. We develop a simple test of this explanation and use it to explore the role of expectations in the context of the 1990s hospital merger wave. Managed care such as Health Maintenance Organizations (HMOs) started to become popular in the late 1980s and ultimately became an important player in the health insurance market. Our empirical analysis shows that the expected increase in the popularity of HMOs was partly responsible for the hospital merger wave of the 1990s: hospitals feared that the “innovation” of managed care in the downstream insurance market would penetrate the upstream hospital market and responded to this belief by merging. Our results show the importance of incorporating expectations and interindustry linkages into the understanding of merger waves.     

Towards Assessing the Knowledge Gap in Medical Tourism

The medical tourism industry is a fast growing global niche market that generated $20 billion in income for destinations around the world. This study suggests and tests a mechanism to assess the medical tourism providers’ perceptions about the tourists’ perceived important product attributes when selecting a medical tourism destination. The results indicate that the various medical tourism providers groups do not vary in their perceptions regarding 24 important attributes of the medical tourism product and that they all agree that tourists perceive the medical variables to be more important than the tourism related variables. Using the Korean market for data collection, the study’s additional contribution is providing insights for Korean government agencies, operators of medical tourism hospitals, policymakers, and marketers.     

Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data

We utilize the Internet search data from Google Trends to provide short-term forecasts for the inflow of Japanese tourists to South Korea. We construct the Google variable in a systematic way by combining keywords to minimize mean squared or mean absolute forecasting errors. We augment the Google variable to the standard time-series forecasting models and compare their forecasting accuracies. We find that Google-augmented models perform much better than the standard time-series models in terms of short-term forecasting accuracy. In particular, Google models show better out-of-sample forecasting performance than in-sample forecasting.     

Residents’ attitudes toward future tourism development in terms of community well-being and attachment

This study explores residents’ attitudes toward future tourism development based on their community well-being (CWB) and community attachment. Focusing on the case of Gamcheon Culture Village in Busan, South Korea, which was developed during an urban regeneration project in 2009, an exploratory factor analysis was conducted. The main findings of this study are: (1) CWB is supported by five variables including income effects, social participation, safety service, infrastructure service, and environmental effect; (2) not only does CWB influence community attachment but attachment also effects residents’ attitudes; and (3) the most effective variable of CWB is income effect, and safety service for community attachment. These results can help to provide effective strategies to encourage residents to have positive attitudes about further tourism development in a community-based tourism destination.     

Value at risk forecasting for volatility index

Forecasts of values at risk (VaRs) are made for volatility indices such as the VIX for the US S&P 500 index, the VKOSPI for the KOSPI (Korea Stock Price Index) and the OVX (oil volatility index) for crude oil funds, which is the first in the literature. In the forecasts, dominant features of the volatility indices are addressed: long memory, conditional heteroscedasticity, asymmetry and fat-tails. An out-of-sample comparison of the VaR forecasts is made in terms of violation probabilities, showing better performance of the proposed method than several competing methods which consider the features differently from ours. The proposed method is composed of heterogeneous autoregressive model for the mean, GARCH model for the volatility and skew-t distribution for the error.