• Title/Summary/Keyword: Financial market

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Determinants of Intention to Borrow Consumer Credit in Vietnam: Application and Extension of Technology Acceptance Model

  • HOANG, Van Hai;NGUYEN, Phuong Mai;LUU, Thi Minh Ngoc;VU, Thi Minh Hien
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.4
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    • pp.885-895
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    • 2021
  • The purpose of this study is to examine the determinants of intention to borrow consumer credit of Vietnamese people by applying the Technology Acceptance Model (TAM) and extending it with several variables, including anxiety, perceived trust, and perceived financial costs extracted and adapted from the existing literature. A questionnaire survey was administered in the big cities of Vietnam to a total of 602 consumers. Structural equation modeling (SEM) techniques have been employed to investigate the relationship among intention determinants to borrow. Findings show that perceived usefulness mediates the impact of subjective norms on the intention to borrow consumer credit. At the same time, subjective norms also directly influence the intention to borrow. Notably, anxiety, perceived trust, perceived financial cost, perceived ease of use have no significant influence on intention to borrow. Meanwhile, education level is confirmed to have a moderate influence on intention to borrow consumer credit of Vietnamese people. However, there is not enough statistical evidence about the influence of gender and marital status on the intention to borrow consumer credit in Vietnam. Based on the findings of the Vietnamese consumer credit market, we proposed some suggestions to promote the growth of the market in the future.

The Impact of Capital Requirement on Bank Performance: Empirical Evidence from Vietnamese Commercial Banks

  • LE, Trung Hai;NGUYEN, Ngan Bich;NGUYEN, Duong Thuy
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.6
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    • pp.23-32
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    • 2022
  • This paper examines the effects of regulatory capital on a bank's profitability and risk. We employ annual data from Vietnamese commercial banks from 2005 to 2020 and use the dynamic GMM regression method to address the potential endogeneity issue, more suitable for panel data with relatively low time dimensions. Our panel regressions indicate that higher regulatory capital would significantly improve the bank's profitability and lower the bank risks. In particular, a one percent increase in the regulatory capital would significantly increase the bank's return on assets by 1.9%. We further explore the heterogeneous impacts of regulatory capital on the Vietnamese bank's performance across bank characteristics. We find that smaller, non-state-owned and non-listed banks would benefit from stringent regulatory capital requirements. The improvements in bank performance are mainly driven by reductions in the risk premium of the banks, resulting in lower funding costs and higher profitability. These findings are essential since Vietnam, as an emerging market, has only implemented the Basel II reform recently on a stable and fast-growing background rather than as a reaction to the global financial crisis. Thus, our empirical results support stringent regulatory capital in emerging countries to ensure a stable banking sector and boost economic growth.

A Study on the Portfolio Performance Evaluation using Actor-Critic Reinforcement Learning Algorithms (액터-크리틱 모형기반 포트폴리오 연구)

  • Lee, Woo Sik
    • Journal of the Korean Society of Industry Convergence
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    • v.25 no.3
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    • pp.467-476
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    • 2022
  • The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

Policy-based Loans to Korean SME Exporters and the Intensive Margin of Exports

  • Whang, Unjung;Koo, Kyong Hyun
    • East Asian Economic Review
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    • v.26 no.3
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    • pp.179-204
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    • 2022
  • This study examines the extent to which policy-based loans to SME exporters affect their export performance (the intensive margin of exports). We also investigate the heterogeneous export effects of policy-based loans that may depend on firm- and industry-specific characteristics, such as credit ratings, debt-to-assets ratios, firm size and age. To do so, we conduct a survey, of 1,000 Korean SMEs, that collect information on firm-level exports and policy-based loans. The main empirical findings strongly support that SMEs that receive policy-based loans tend to increase their export volumes. However, these loans' positive impact on exports are only valid for SME exporters with credit scores of 12 or greater (that is, SMEs that have difficulty accessing the external financial market). The estimation results with respect to SMEs' dependence on external financing imply that policy-based loans for SMEs in sectors that are heavily dependent on external finance are effective in that they are instrumental in increasing these firms' exports. These empirical findings emphasize the importance of the external financial market to SME exporters who face various up-front investments that are related to their exporting activities.

Investigating the Impacts of IT Strategy on IT Investment and Management Performance in SCM Companies (SCM 기업들의 IT전략이 IT투자와 경영성광에 미치는 영향)

  • Kim, Jong-Weon;Kim, Eun-Jung
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.2
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    • pp.59-71
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    • 2009
  • A great number of companies continue to invest heavily in information technology such as SCM The reasons for this investment vary, but the principal belief is that they will use the technology to gain competitive advantage in today's highly dynamic and changing business market. In order to identify the SCM management performance, this study investigates the impacts of information technology strategy(operation-oriented and market-oriented) on the information technology investment direction(internal system orientation and external system orientation), process innovation level and management performance(non-financial performance and financial performance). This study collected data on-line and off-line from enterprises which implement the supply chain management. The 82 responses were used for the statistical analysis.

IMPACTS OF DESIGN-BUILD DELIVERY SYSTEM ON THE CONSTRUCTION INDUSTRY IN TAIWAN

  • Min-Ren Yan;Wei Lo;Chien-Liang Lin
    • International conference on construction engineering and project management
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    • 2005.10a
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    • pp.1007-1012
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    • 2005
  • Although the design-build (DB) delivery system has been taking great strides in the world and relevant researches have also been quite abundant, few studies have dealt with its potential impacts on the construction industry as a whole. This research first identified the potential entry barrier factors, which may hinder the market access, based on the theory of industrial economics and characteristics of DB project. Then through a nation-wide questionnaire survey involving 103 construction contractors and engineering consultants, the influences of each factor on company's competitiveness and corporate strategies were scrutinized, and consequently, the evolution of the construction industry was examined. It is found that as opposed to the traditional design-bid-build delivery system, the DB delivery system elevates competitive advantages of large organizations in terms of the financial capability, working experience, human resource, and administrative strength, and among them, the financial strength was concluded to be the most significant force in differentiating corporate strategies and widening the gap of competitiveness between companies. It is inferred if the government extensively adopts DB delivery system, large organizations that already possess the competitive advantage tend to obtain both design and construction abilities, and dominate the DB market. Small and medium sized companies will find little room to maneuver and be forced to become specialty sub-contractors.

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A Study on the Feasibility of Win-Win Growth in Wholesale Market

  • WON, Jong-Moon
    • The Journal of Industrial Distribution & Business
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    • v.11 no.4
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    • pp.31-38
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    • 2020
  • Purpose: At a time when the distribution industry is dominated by capital and technology, win-win growth among businesses groups (BGs) in wholesale market is becoming a social issue. Therefore, through analysis of market growth, market concentration (MC) and market power (MP), we want to identify the structure of the wholesale market and the competitiveness of the BGs in terms of market share (MS), sales-profit ratio (SPR), and labor productivity (LP) to explore the possibility of win-win growth. Market situation: Wholesale and Retail sales ratio (W/S) continues to increase, which also means inefficiency in distribution channels or opportunities in wholesale markets. Wholesale sales have grown 8.3 percent annually over the past 15 years, while the number of companies and workers has declined since 2017, which is why some restructuring is believed to begin in the wholesale industry. In terms of MC and MP, the growth potential of SBG can be found in FCB, ARM, FBT and CME BTs. Methodology and data: Through ANOVA and Regression Analysis, the 2015 Economic Census Data of KOSTAT was analyzed. Results: The results of ANOVA show that statistically significant SBG has a larger MS than LBG. The SPR was not different among BGs. LP is higher for LBG than for other BGs. Regression results show that the employment weight (EW) and the company size (SC) have positive effects on the MS, but the company weight (CW) and employment size (SE) have negative effects. In the case of SPR, the CW is positive and the EW is negative. In addition, LP appears to be more positive as SC in the BGs is larger. Conclusions: Although there is sufficient potential for SBG in the wholesale market, there is a problem that needs to increase LP. Therefore, the SBG needs to restructure in terms of number of companies and SC to improve the efficiency of employment. In terms of MC and MP, the SBG looks for possibilities in FCB, ARM, FBT and CME BTs. In addition, SBG that seeks higher returns with human services rather than simple sales is found to be competitive in the HHG, MES and CME BTs.

On Parameter Estimation of Growth Curves for Technological Forecasting by Using Non-linear Least Squares

  • Ko, Young-Hyun;Hong, Seung-Pyo;Jun, Chi-Hyuck
    • Management Science and Financial Engineering
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    • v.14 no.2
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    • pp.89-104
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    • 2008
  • Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.

Implied Volatility Function Approximation with Korean ELWs (Equity-Linked Warrants) via Gaussian Processes

  • Han, Gyu-Sik
    • Management Science and Financial Engineering
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    • v.20 no.1
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    • pp.21-26
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    • 2014
  • A lot of researches have been conducted to estimate the volatility smile effect shown in the option market. This paper proposes a method to approximate an implied volatility function, given noisy real market option data. To construct an implied volatility function, we use Gaussian Processes (GPs). Their output values are implied volatilities while moneyness values (the ratios of strike price to underlying asset price) and time to maturities are as their input values. To show the performances of our proposed method, we conduct experimental simulations with Korean Equity-Linked Warrant (ELW) market data as well as toy data.

THE RELATIVE ENTROPY UNDER THE R-CGMY PROCESSES

  • Kwon, YongHoon;Lee, Younhee
    • Journal of the Chungcheong Mathematical Society
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    • v.28 no.1
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    • pp.109-117
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    • 2015
  • We consider the relative entropy for two R-CGMY processes, which are CGMY processes with Y equal to 1, to choose an equivalent martingale measure (EMM) when the underlying asset of a derivative follows a R-CGMY process in the financial market. Since the R-CGMY process leads to an incomplete market, we have to use a proper technique to choose an EMM among a variety of EMMs. In this paper, we derive the closed form expression of the relative entropy for R-CGMY processes.