This study investigates the problem of outlier detection based on discrete wavelet transform in the context of time series data where the identification and treatment of outliers constitute an important component. An outlier is defined as a data point that deviates so much from the rest of observations within a data sample. In this work we focus on the application of the traditional method suggested by Tukey (1977) for detecting outliers in the closed price series of the Saudi Arabia stock market (Tadawul) between Oct. 2011 and Dec. 2019. The method is applied to the details obtained from the MODWT (Maximal-Overlap Discrete Wavelet Transform) of the original series. The result show that the suggested methodology was successful in detecting all of the outliers in the series. The findings of this study suggest that we can model and forecast the volatility of returns from the reconstructed series without outliers using GARCH models. The estimated GARCH volatility model was compared to other asymmetric GARCH models using standard forecast error metrics. It is found that the performance of the standard GARCH model were as good as that of the gjrGARCH model over the out-of-sample forecasts for returns among other GARCH specifications.

This study examines the factors that affect firm’s liquidity in manufacturing companies listed in Vietnam. Factors studied include the board size, the board independence, the firm size, the firm age, and its return. We use different metrics to measure firm’s solvency status, including the cash ratio, the quick ratio, and the cash conversion cycle. Accordingly, three econometric models are built to test hypotheses proposed by researchers in order to explain the relationship between the five factors above and liquidity’s measures. The study used the data set of manufacturing companies listed on the Ho Chi Minh City Stock Exchange in the period from 2015 to 2019. The final sample group comprises 139 firms with 633 observations. The results show that in manufacturing firms, while the cash ratio and the quick ratio are positively associated to the board size, the board independence, and the firm’s profitability, the net operating cycle is negatively correlated to the board size, the firm size, the board independence, and the profitability. Therefore, larger firms with larger board size and more independent members can help to improve capital management efficiency.There is no evidence for the relationship between the firm age and solvency measurements, between cash conversion cycle and firm’s profitability.

This study investigates the dynamic effects of economic development, international cooperation, electricity consumption, and political risk on the escalation of CO2 emission in Vietnam. We adopted autoregressive distributed lag model and Granger causality method to examine the interaction between CO2 and various economic and political factors, including foreign direct investment, trade openness, economic growth, manufacture, electricity consumption, and political risk in Vietnam since the economic revolution in 1986. The findings reflect opposite influence between these factors and the level of CO2 in the intermediate and long-term durations. Accordingly, foreign direct investment and CO2 emission have a bidirectional relationship, in which foreign direct investment accelerates short-term CO2 emission, but reduces it in the long run through an interactive mechanism. Moreover, economic development increases the volume of CO2 emission in both short and long run. There was also evidence that political risk has a negative effect on the environment. Overall, the findings confirm lasting negative environmental effects of economic growth, trade liberalization, and increased electricity consumption. These factors, with Granger causality, mutually affect the escalation of CO2 in Vietnam. In order to control the level of CO2, more efforts are required to improve administrative transparency, attract high-quality foreign investment, and decouple the environment from economic development.

The neoclassical economic supporters have suggested that foreign direct investment and raw material (e.g., coal, electricity, gas, and oil) are critical economic growth inputs. Few previous studies have analyzed the relationship between foreign direct investment and energy consumption on economic growth. However, existing studies usually have applied the frequentist inference. The limitation of the frequentist inference is that, if the coefficient of the independent variable is not yet significant, then conclusions might be unreliable. By applying the Bayesian approach, the main aim of this study is to revisit the impact of foreign direct investment, electricity consumption, and urbanization on economic growth in six ASEAN countries from 1980 to 2016. The obtained outcome shows that the impact of electricity consumption is evident and positive on economic growth in both frequentist and Bayesian inferences. However, the influence of foreign direct investment is not identified by frequentist inference, while Bayesian inference provides evidence that foreign direct investment is a moderately positive impact on economic growth. The empirical result from Bayesian inference contributes to the literature on foreign direct investment modeling and could be of significant importance for a more efficient foreign direct investment attracting and achieve sustainability in the long-term.

This paper examines how macroeconomic variables, such as interest rate differences, inflation, exchange rates, economic growth and external debt growth, affect capital flight in the ASEAN-8 countries. We apply a panel data model with fixed effect estimation for the data for eight countries from the period 1994 to 2018. We use the residual approach used by the World Bank to measure the value of capital flight. The results show that the interest rate differences, exchange rates, economic growth and foreign debt growth had a positive and significant effect on outward capital flight. A further implication of this finding is that the interest rate differences, exchange rate, economic growth and foreign debt growth are factors that trigger an increase in capital outflow in the ASEAN-8 countries. Nonetheless, inflation rate is not considered to be the main factor influencing capital flight, as average inflation in the ASEAN-8 countries remains relatively stable. This paper will be beneficial for policymakers in the ASEAN-8 countries and encourage them to constantly pay attention to these four variables, as they significantly influence capital flight, whereas they can disregard the impact of the inflation variable that is not significant in influencing capital flight.

The COVID 19 pandemic has led to a new global recession and is still causing a lot of issues because of the delays in the employment of people. This scenario has severe consequences for many countries’ labor markets in the world. This problem’s complexity and importance requires an integrated method of subjective and objective evaluation rather than intuitive decisions. This research aims to investigate sustainable indexes for assessing the unemployment problem by using a Multi-Criteria Decision-Making Model (MCDM). Grey theory and Decision Making Trial and Evaluation Laboratory (GDEMATEL) are deployed to transform the experts’ opinions into quantitative data. The analysis based on 20 crucial criteria is employed to determine the weights of sustainability of unemployment problems. The results revealed that the top ten of determinants are Economic growth, Industrialization, Foreign direct investment, Real GDP per capita, Education level, Trade Openness, Capacity Utilization Rate, Urbanization, Employability skills, Education system expansion, which have the most significant effects on the unemployment rate under COVID 19 impacts. Furthermore, GDEMATEL could effectively assess the sustainable indicators for unemployment problems in “deep and wide” aspects. The study proposes the Grey MCDM model, contributes to the literature, provides future research directions, and helps policymakers and researchers achieve the best solutions to the unemployment problems under “economic shocks.”

Shadow banking in China has been growing rapidly; banks use wealth management products aggressively to evade regulatory constraints. The loan-to-deposit ratio or LDR targets both sides of the balance sheet; loans in terms of asset-side, and deposits in terms of liabilitiesside; banks needed to control and maintain both sides. Regulators restricted Chinese banks to maintain a 75% limit for their loan-depositratio. Banks’ needed to either lower their loans or increase the deposits; WMPs helped banks to evade this limit. Banks issue more WMPs to control and manage a 75% statutory ceiling LDR. This WMPs-LDR positive association disappeared post-2015 period. This study empirically examined how Chinese banks use WMPs issuance to avoid regulatory constraints. Quarterly panel data for 30 top Chinese banks were used by analyzing pre-2015 (during the 75% LDR limit) and post-2015 (after removal of the LDR limit). This study also performed fixed-effects model as recommended by the Hausman specification test, with feasible generalized least squares FGLS estimation technique. The results of this study show that for the pre-2015 period, Chinese banks use issuance of WMPs aggressively to manage their LDR limit; this WMPs-LDR relationship disappeared post-2015 period. Moreover, SMBs use WMPs more eagerly as compare to Big4 banks.

The study aims to investigate the dual effects of corruption control on economic growth in relationship with the stock market and trade openness in developing countries. The study used difference S-GMM method on the dynamic panel data model in the period (2002-2017) with data collected from the World Bank. The study discovers the dominant impacts of corruption control in the relationship with the stock market on economic growth. At the same time, the study also confirms the overwhelming impact of corruption control in the relationship between trade openness and economic growth in the developing countries. In addition, the study shows that inefficient stock markets in developing countries will not promote economic growth. Meanwhile, the long-standing credit market has a positive impact on economic growth. With the strong development of stock market and trade openness in the period (2002-2017), control on corruption in developing countries does not get better in time with the increase in demand. The findings of this study suggest a number of solutions to strengthen corruption control, leading to the increased efficiency on the stock market and as well as encouraging the positive effects of trade openness to contribute to promoting economic growth in developing countries.

This study aimed to explore the impact of macroeconomic (Real GDP growth (GDPG), Inflation rate (INF)) and bank –specific variables (profitability (ROA), capital adequacy (CADEQ), non-performing loans (NPL), deposit growth (DEPG)) on the liquidity (lIQ) of 13 listed Jordanian commercial banks for the period 2011-2018. Panel data analysis, Pooled least square, fixed effects model and random effects model, Lagrange multiplier test, and Hausman test were used. The random effects model output shows that, macroeconomic variables have a significant impact on Jordanian commercial banks liquidity since inflation has a positive impact while GDPG has a negative impact on banks (LIQ). On the other hand among the bank-specific variables capital adequacy and deposit growth have a positive significant impact on banks (LIQ), while (NPL) and (SIZE) have a negative significant impact on Jordanian commercial banks liquidity. But ROA has a negative insignificant impact on (LIQ). The findings of the study suggest that commercial banks departments need to pay attention to the economic and internal variables of banks in order to maintain acceptable levels of liquidity.

The study investigates the asymmetric effect of exchange rate changes on stock prices in Vietnam. We use the nonlinear autoregressivedistributed lag (ARDL) analysis for monthly data from 2001:01 to 2018:05, based on VN-Index stock price collected from Ho Chi Minh Stock Exchange (HOSE); the nominal exchange rate is separated into currency depreciation and appreciation through a partial sum decomposition process. Asymmetry is estimated both in the long-run relationship and the short-run error correction mechanism. The research results show that the effect of exchange rate changes on stock prices is asymmetrical, both in the short run and in long run. Accordingly, the stock prices react to different levels to depreciation and appreciation. However, the currency appreciation affects a stronger transmission of stock prices when compared to the long-run currency depreciation. In the absence of asymmetry, the exchange rate only has a short-run impact on stock prices. This implies a symmetrical assumption that underestimates the impact of exchange rate changes on stock prices in Vietnam. This study points to an important implication for regulators in Vietnam. They should consider the relationship between exchange rate changes and stock prices in both the long run and the short run to manage the stock and foreign exchange market.

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia’s growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.

This study aims to investigate the effects of restrictions in economic activity on the spread of COVID-19 in the Philippines. This research employs daily time-series data of confirmed new COVID-19 cases, Apple mobility trends (i.e., use of public transport to destinations, volume of people driving, and amount of walking to destinations) and Google community mobility (i.e., visits to transit stations, visits to workplaces, and staying-at-home) indicators covering the period February 17 to September 11, 2020. The analysis starts by establishing the correlation pattern of new confirmed COVID-19 daily infections to each independent variable. The results show negative linear correlation of the number of new COVID-19 daily infections with less visit to transit station, increase stay-at-home, less use of public transport, and less amount of walking to destinations. Interestingly, the number of new COVID-19 daily infections indicates some form of positive linear correlation with visits to workplaces and volume of people driving. Moreover, employing robust least square regression via the method of MM-estimation, major findings reveal that across mobility measures, staying-at-home has the highest impact on reducing the spread of COVID-19, followed by visiting transit stations less, less use of public transport, less amount of walking, and less workplace visits.

This scholarly work is an effort to capture the effects of oil prices on the actual exchange rate between dollar and rupee. This is done with reference to the U.S. dollar as oil prices are marked in USD (U.S. Dollar) in the international market, and India is among the top five importers of oil. Using monthly data from January 2001 to May 2020. The study used the real GDP, money supply, short-term interest rate difference between two countries, and inflation apart from the crude oil prices per barrel as the factors that help define the exchange rate. The analysis, through cointegration and vector error correction method (VECM), suggests long and short-run causality amid prices of oil and the rate of exchange fluctuations. Oil prices are found to be negatively related to the exchange rate in the long term but positively related in the short term. The result of the Wald test also indicates the short-run causation from the short-term interest rate and the prices of crude oil towards the exchange rate. The present study shows that oil prices are evidence of the existence of short-term and long-term driving associations with short-term interest rates and exchange rates.

In accordance with huge demand for capital to meet the expansion of steel production, there are more and more steel companies who have officially listed their stocks in HOSE and HNX. One of the key issues in successful initial public offerings and seasonal offerings for these companies is how to make stocks of steel companies become more attractive in the eyes of investors. The purpose of this research is to analyze the determinants of share prices of listed steel companies in Vietnam. This study utilized macro-economic variables, ratios and indicators representing characteristics of steel industry collected from Quarter 1/2006 to Quarter 4/2019 in association with the panel data and the feasible generalized least square (FGLS) model to evaluate the degree of these factors on the share prices. The results of the research show that ROE, Cons_rate, and CO2_rate are three main factors affecting the share prices of listed steel companies. Among which, ROE and Cons_rate have a positive effect, while CO2_rate has a negative effect on the share prices of listed steel companies. It also confirms the relationship between the environmental factor, construction industry factor and the stock prices. This lays foundations for recommendations for the future policies towards environmental protection and sustainable development.

The domain of entrepreneurship has been dotted across various paradigms. Identifying and examining entrepreneurial intention and propensity to it spontaneously require the insight from the lens of psychological approach. The aim of this study is to examine the influence and impact of psychological factors on entrepreneurial intention; as it is found that in Bangladeshi context several entrepreneurship studies are undertaken, still the exploratory research on interplay between the psychological factors (i.e., self-confidence, locus of control, need for achievement, and tolerance for ambiguity) and entrepreneurial intention has been merely found. The study has chosen Bangladeshi university students as the unit of analysis and the ultimate sample size in this research is n=265. The current paper is a quantitative study where sampling method is followed by convenience sampling technique, and study data is collected through survey questionnaire. Data has been compiled into SPSS whereas, for hypotheses assessment, Smart PLS software is applied. The results reflect that self-confidence, locus of control, and need for achievement are revealed as contributory determinants of entrepreneurial intention while tolerance for ambiguity is found as an insignificant predictor. The current research is expected to offer an in-depth understanding about the significance of psychological factors in examining entrepreneurial intention.

In the accounting information system implementation, the users should consider the benefits and advantages of the system. This paper examines the effect of the Enterprise Resources Planning based (ERP-based) accounting information system implementation on user impact and organizational impact. The population in this study is companies listed on the Indonesian Stock Exchange, especially companies based in Riau, Indonesia. These companies currently use the ERP-based accounting information system. Research samples are employees who use the ERP-based accounting information system. For data analysis, we use structural equation modeling (SEM). Based on data analysis, high-quality information system implementation generate high-quality information that can give satisfaction to the user. Moreover, the information system is related to user skill, satisfaction, and knowledge sharing which improve personal skills; enhanced personal skill contributes to organizational performance. On the other hand, there is no effect of training on personal skills and there is no effect of information quality on perceived usefulness. This research gives implication to the organization for implementing a high-quality ERP-based accounting information system that positively impacts organizational performance. Future research is expected to examine information system implementation in different research objects and conditions.

The cryptocurrency market has received immense consideration in media and academia since the beginning of 2013 because of its huge price fluctuation. This study focuses on Arab investors who invest in the cryptocurrency market by investigating the influence of behavioral finance factors on investment decisions in the cryptocurrency market. A quantitative approach was used by employing a snowball sampling method through 112 questionnaires. The results show that herding theory, prospect theory, and heuristic theory have a significant effect on investors’ investment decisions in the cryptocurrency market. This emphasizes the significant role of the proposed behavioral factors as determinants of the investors’ investment decisions. This study contributes to the existing research by consolidating the results of different researches in this study. It also contributes to the investors’ understanding of the dynamics of the cryptocurrency market and it enhances the ability to make informed decisions based on their understanding. The implication of the findings will prepare hit and run investors to be progressively prepared to stay in the cryptocurrency market and develop their abilities on the most proficient method to settle on sound venture choices. Furthermore, the findings of this study will encourage financial specialists to realize that information on the traditional finance theory is not adequate to excel in the cryptocurrency market.

This study examines the drivers and implementation of intrapreneurship strategy in a property service company. Using a qualitative case study approach, the study interviewed four managers involved in related intrapreneurship initiatives. The data was validated by an expert and a practitioner from a different company. The implementation of the company’s intrapreneurship strategy is limited to improving new ways of working and developing products and services. However, business development and the creation of new business models are still limited. From several intrapreneurship driving factors, it was observed that the company practices are considered adequate with regard to top management support, leadership, flexibility in carrying out work, as well as in fairly harmonious arrangements for ongoing business relationships with the intrapreneurship projects. On the other hand, human resources with entrepreneurial behavior are still minimal. Similarly, the driving factors in reward and training that promote entrepreneurial behavior are also considered to be insufficient. The application of intrapreneurship as a strategy requires understanding and commitment from all parties in the organization. This study provides insight into the Indonesian context and proposes that intrapreneurship initiatives are less likely to succeed if they are not supported by developing a more systematic entrepreneurial mindset, behavior, and culture.

This study examines the relationship between gender diversity (women on the board and women on the audit committee) and a firm’s financial stability. The ordinary least square analysis was used to determine the relationship. To measure the financial stability of Malaysian suspect firms, i.e., firms with the lowest positive earnings, the Altman (1993) Z-Score measurement was utilized. The results indicate that women on the board are significantly and negatively associated with the firm’s financial stability. That is, they are related to low financial stability, which contradicts the agency and resource dependence theories. Regarding women directors on the audit committee, there is no significant relationship with financial stability, meaning that they cannot protect the company against financial distress. These results are robust and do not change when using different measurements of gender diversity, one-year lag of independent variables, and other methods of analysis, namely random effect panel data. This study is the first to alert policymakers, stakeholders, researchers, and society in general to the need to re-evaluate and strengthen the role of women directors in improving firms’ financial stability, particularly in emerging economies like Malaysia.

This study describes the structure of the capital markets for small- and medium-sized enterprises (SMEs) and startup companies in Korea, which is an emerging market that has experienced drastic changes. The overall capital market can be divided into private and public capital markets. In the private capital market, most of the demand for capital comes from non-listed private firms, including startups and SMEs. In the case of SMEs and startups, the KOSDAQ, the Korea New Exchange (KONEX), and primary collateralized bond obligations (P-CBOs) are part of the public capital market. SMEs and startups are generally incapable of raising sufficient capital owing to their low credit ratings, and they largely have limited access to primary markets to issue shares and borrow money. The Korean government has developed a systematic financial aid program to provide funds to these companies. The fund for SMEs has significantly contributed to the development of the venture capital market. Many Korean banks provide substantial lending to SMEs, but this lending is available only because of the Korean government’s loan recovery guarantee. Furthermore, SMEs can issue corporate debt in the form of primary collateralized bond obligations through government guarantees, but such debt issuances have placed increasing pressure on public guarantee institutions.