Search results

This paper investigates how various strategies for combining forecasts, both simple and optimised approaches, are compared with popular individual risk models in estimating value-at-risk (VaR) and expected shortfall (ES) in emerging market at alternative risk levels.

Using the case study of the Vietnamese stock market, the author produced one-day-ahead VaR and ES forecast from seven individual risk models and ten alternative forecast combinations. Next, the author employed a battery of backtesting procedures and alternative loss functions to evaluate the global predictive accuracy of the different methods. Finally, the author investigated the relative performance over time of VaR and ES forecasts using fluctuation test.

The empirical results indicate that, although combined forecasts have reasonable predictive abilities, they are often outperformed by one individual risk model. Furthermore, the author showed that the complex combining methods with optimised weighting functions do not perform better than simple combining methods. The fluctuation test suggests that the poor performance of combined forecasts is mainly due to their inability to cope with periods of instability.

This study reveals the limitation of combining strategies in the one-day-ahead VaR and ES forecasts in emerging markets. A possible direction for further research is to investigate whether this finding holds for multi-day ahead forecasts. Moreover, the inferior performance of combined forecasts during periods of instability motivates further research on the combining strategies that take into account for potential structure breaks in the performance of individual risk models. A potential approach is to improve the individual risk models with macroeconomic variables using a mixed-data sampling approach.

First, the authors contribute to the literature on the forecasting combinations for VaR and ES measures. Second, the author explored a wide range of alternative risk models to forecast both VaR and ES with recent data including periods of the COVID-19 pandemic. Although forecast combination strategies have been providing several good results in several fields, the literature of forecast combination in the VaR and ES context is surprisingly limited, especially for emerging market returns. To the best of the author’s knowledge, this is the first study investigating predictive power of combining methods for VaR and ES in an emerging market.

Employers often claim that the lack of employee competence is a limitation in their enterprises’ success and viability. Consequently, employers are important stakeholders in considerations for workforce continuing education and training (CET) policies and practices. Hence, the authors undertook an exploratory investigation to understand how employers perceive provisions of CET offered through tertiary education institutions and how they might be improved.

Overall, 40 employers from a range of industry sectors in Singapore were surveyed and interviewed about effective CET for their employees.

These employers reported preferring one-on-one training in the workplace and being willing to invest in their employees’ training so long employees remained committed to their companies. They value online education, but prefer that it is combined with workplace or face-to-face learning experiences. They proposed effective CET trainers as those with relevant industry knowledge and teaching skills and effective CET learners as those who were self-motivated, goal oriented and open-minded.

A study of such nature that focusses on the perspectives of employers, as opposed to employees and educators, has not been undertaken before in Singapore. Given Singapore’s increasing emphasis on lifelong learning and the workplace as a vital site for that learning, the lessons learnt here transcend national boundaries and may serve as a useful reference for other countries that seek to provide inclusive and equitable quality education and lifelong learning for all.

Employee satisfaction is critical in any workplace. Research suggests that the environment that people work in can contribute greatly to levels of satisfaction as well as productivity. Limited research exists, however, on how the aesthetics of a workplace impact both employee satisfaction and well-being. This paper aims to identify whether the aesthetics in a workplace environment at one university influences employee satisfaction and well-being.

This paper shares data from a survey that determined whether the workplace environment at one university in Queensland, Australia supports its workers’ job satisfaction and well-being. The survey was distributed amongst all staff at three campuses with a total of 73 usable responses.

Findings showed that there is a strong need for an aesthetically pleasing workplace and its positive impacts on employees. In addition, an aesthetically pleasing workplace was perceived to have a positive impact on the respondents’ likelihood of spending more time at work, hence, a greater sense of satisfaction. The respondents indicated a moderate level of satisfaction with the aesthetics of their workspace and environment including feeling safe.

Implications show that further improvements could be attained in the workplace through the addition of natural lighting, plants and artwork. The employees also indicated they would like more control over the aesthetics of the work environment.

This research is original as it was not known whether aesthetics in the workplace influenced worker satisfaction and/or well-being.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

The authors provide a comprehensive study on systemic risk of the banking sectors in the ASEAN-6 countries. In particular, they investigate the systemic risk dynamics and determinants of 49 listed banks in the region over the 2000–2018 period.

The authors employ the market-based SRISK measure of Brownlees and Engle (2017) to investigate the systemic risk of the ASEAN-6's banking sectors.

The authors find that the regional systemic risk fluctuates significantly and currently at par or higher level than that of the recent global financial crisis. Systemic risk is generally associated with banks that have bigger size, more traditional business models, lower quality in their loan portfolios, less profitable and with lower market-to-book values. However, these relationships vary significantly between ASEAN countries.

The research focuses on the systemic risk of ASEAN-6 countries. Therefore, the research results may lack generalizability to other countries.

The authors’ empirical evidence advocates the use of capital surcharges on the systemically important financial institutions. Although the region has been pushing to higher financial integration in recent years, the authors encourage the regional regulators to account for the idiosyncratic characteristics of their banking sectors in designing effective macroprudential policy to contain systemic risk.

This paper provides the first study on the systemic risk of the ASEAN-6 region. The empirical evidence on the drivers of systemic risk would be of interest to the regional regulators.

COVID-19 hits every country’s health-care system and economy. There is a trend toward using automation technology in response to the COVID-19 crisis not only in developed countries but also in those with lower levels of technology development. However, current studies mainly focus on the world level, and only a few ones report deployments at the country level. The purpose of this paper is to investigate the use of automation solutions in Vietnam with locally available materials mainly in the first wave from January to July 2020.

The authors collected COVID-related automation solutions during the first wave of COVID-19 in Vietnam from January to July 2020 through a search process. The analysis and insights of a panel consisting of various disciplines (i.e. academia, health care, government, entrepreneur and media) aim at providing a clear picture of how and to what extent these solutions have been deployed.

The authors found seven groups of solutions from low to high research and development (R&D) levels deployed across the country with various funding sources. Low R&D solutions were widely spread owing to simplicity and affordability. High R&D solutions were mainly deployed in big cities. Most of the solutions were deployed during the first phases when international supply chains were limited with a significant contribution of the media. Higher R&D solutions have opportunities to be deployed in the reopening phase. However, challenges can be listed as limited interdisciplinary research teams, market demand, the local supporting industry, end-user validation and social-ethical issues.

To the authors’ best knowledge, this is the first study analyzing the use of automation technology in response to COVID-19 in Vietnam and also in a country in Southeast Asia. Lessons learned from these current deployments are useful for future emerging infectious diseases. The reality of Vietnam’s automation solutions in response to COVID-19 might be a reference for other developing countries with similar social-economic circumstances and contributes to the global picture of how different countries adopt technology to combat COVID-19.

This paper aims to facilitate the joint assessment of issues related to the agricultural systems, i.e. agriculture, aquaculture and climate change (CC) response strategies, in the coastal districts with a panel of stakeholders; and to evaluate the level of agreement on the topics under consideration and potentially identify the most promising approaches to assessing CC affecting agricultural systems in the area and identify relevant and adequate response strategies.

Stakeholder Delphi technique – its assessment is an interactive method of qualitative research used to facilitate the interactive participation of varied and conceivably hierarchical and antagonistic stakeholder groups.

The most important result for the province is that the impact of climate change on agro-ecological landscapes (poverty and near river areas) is the duration of cold weather, more frequent and extreme. Moreover, Kendall’s W test gave a score of 0.547, which indicates a “strong” stakeholder agreement and the “confidence in ranks” being “high” in Thai Binh (Vietnam).

The scientific results in this study are intended to serve as relevant knowledge-inputs and direct contributions to capacity-building for the local partners (stakeholders and local authorities). These local partners are engaged in policy-making and effective planning and implementation of climate response measures in the districts in the province of Thai Binh.

The purpose of this paper is to present a low-cost, highly mobile system for performing street-level imaging. Street-level imaging and geo-location-based services are rapidly growing in both popularity and coverage. Google Street View and Bing StreetSide are two of the free, online services which allow users to search location-based information on interactive maps. In addition, these services also provide software developers and researchers a rich source of street-level images for different purposes – from identifying traffic routes to augmented reality applications. Currently, coverage for Street View and StreetSide is limited to more affluent Western countries with sparse coverage throughout south-east Asia and Africa. In this paper, we present a low-cost system to perform street-level imaging targeted towards the congested, motorcycle-dominant south-east Asian countries. The proposed system uses a catadioptric imaging system to capture 360-degree panoramic images which are geo-located using an on-board GPS. The system is mounted on the back of a motorcycle to provide maximum mobility and access to narrow roads. An innovative backwards remapping technique for flattening the images is discussed along with some results from the first 150 km which have been captured from Southern Vietnam.

The design was a low-cost prototype design using low-cost off-the-shelf hardware with custom software and assembly to facilitate functionality.

The system was shown to work well as a low-cost omnidirectional mapping solution targeted toward sea-of-motorbike road conditions.

Some of the pictures returned by the system were unclear. These could be improved by having artificial lighting (currently only ambient light is used), a gyroscope-stabilised imaging platform and a higher resolution camera.

This paper discusses a design which facilitates low-cost, street-level imaging for a sea-of-motorcycle environment. The system uses a catadioptric imaging approach to give a wide field of view without excessive image storage requirements using dozens of cameras.