• The Journal of Asian Finance, Economics and Business
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• 제8권11호
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• pp.11-19
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• 2021

The aim of this paper is to evaluate the impact of the COVID-19 pandemic on the stock prices of the companies traded on the UAE financial markets (Abu Dhabi Securities Exchange and Dubai Financial Market). The time series regressions have been applied to estimate the impact of COVID-19 data on the companies' stock prices movements. The data cover the period between January 29^th, 2020, and January 5^th, 2021. The data was collected from the website of the Federal Competitiveness and Statistics Centre of the UAE. The empirical results of this study show that the stock prices are negatively and significantly affected by the number of COVID-19 positive cases and the number of death while they are positively and significantly affected by the number of recoveries. The results vary from one industry to another. These results would be important to the policymakers and financial regulators in developing the needed policies to improve the stock markets' resilience and maintain financial and economic stability. In addition, the findings would be useful to the investors and portfolio managers in taking the most appropriate investment decisions and managing more efficiently their portfolios. This paper will shed light on the responsiveness of the UAE financial market to the COVID-19 pandemic.

• 재무관리연구
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• 제26권1호
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• pp.165-188
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• 2009

본 연구는 개별 자산의 수익률 분포에 대한 가정 없이 평균-VaR 기준에서의 프론티어 포트폴리오를 구하고, 수익률 분포의 고차 적률에 대한 투자자의 선호가 반영된 최적 포트폴리오를 선택하는 방법을 제시하였다. 프론티어 포트폴리오를 구하기 위해 수익률 분포에 대한 가정이 필요하지 않은 그리드와 랭크 방법을 제시하였고 최적 포트폴리오를 선택하기 위해 수익률 분포의 4차 적률까지 고려된 효용함수를 사용하였다. 제시한 방법론을 실제 자료에 적용해 보기위해 모건 스탠리에서 제공하는 선진국 지수, 개발도상국 지수, KOSPI 지수의 주별 수익률 자료를 사용하였다. 평균-VaR 기준과 평균-분산 기준에서의 프론티어 포트폴리오를 구하고 각 기준에서의 최적 포트폴리오를 선택해 서로 비교하였다. 표준편차의 차이뿐만 아니라 효용함수의 수준과 주별 기대수익률로 표현되는 확실성 등가의 차이를 살펴봄으로써 두 기준 간의 경제적 의미 차이에 대해서도 살펴보았다. 또한 부트스트래핑을 이용한 역사적 시뮬레이션의 방법을 사용해 두 기준 간 발생한 차이가 통계적으로 유의한 지를 본 연구에서 적용한 자료에서는 평균-VaR 기준의 투자자가 평균-분산 기준의 투자자에 비해 더 큰 표준편차를 지닌 최적 포트폴리오를 선택하고 위험 회피도가 큰 투자자일수록 평균-VaR 기준에서의 효용이 크고 확실성 등가도 더 크게 나타나는 경향이 나타났다. 그러나 두 기준 간 발생한 차이가 통계적으로 유의하지 않게 나타나 표준편차의 차이와 경제적인 의미 차이가 크지 않다는 사실을 확인하였다.

• 충청수학회지
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• 제26권2호
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• pp.343-349
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• 2013

The optimal portfolio selection problem under inflation risk is considered in this paper. There are three assets the economic agent can invest, which are a risk free bond, an index bond and a risky asset. By applying the martingale method, the optimal consumption rate and the optimal portfolios for each asset are obtained explicitly.

• Communications for Statistical Applications and Methods
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• 제25권6호
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• pp.605-618
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• 2018

Risk management has been a crucial part of the daily operations of the financial industry over the past two decades. Value at Risk (VaR), a quantitative measure introduced by JP Morgan in 1995, is the most popular and simplest quantitative measure of risk. VaR has been widely applied to the risk evaluation over all types of financial activities, including portfolio management and asset allocation. This paper uses the implementations of multivariate GARCH models and copula methods to illustrate the performance of a one-day-ahead VaR prediction modeling process for high-dimensional portfolios. Many factors, such as the interaction among included assets, are included in the modeling process. Additionally, empirical data analyses and backtesting results are demonstrated through a rolling analysis, which help capture the instability of parameter estimates. We find that our way of modeling is relatively robust and flexible.

• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.59-72
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• 2020

This paper examines whether lending structure can lower credit risk by employing econometric techniques of panel data for the Vietnamese banking system at the bank level used by economic sectors from 2011 to 2016. New light is being shed on assessing the impact of each industry's debt outstanding on credit risk. Adopting findings from previous studies, we assess credit risk from two different sources, including loan loss provision and non-performing loan. Moreover, we also focus on observing lending structure in many different aspects, from concentrative levels to the short-term and long-term stability levels of lending structure. The Generalized Method of Moments (GMM) estimator was applied to analyze the relationship between concentration and banking risks. In general, the results show that lending concentration may decrease credit risk. It is interesting to observe that the Vietnamese commercial bank lending portfolios have, on average, higher levels of diversity across different sectors. In particular, the increase in hotel and restaurant lending contributes to decrease credit risk while the lending portfolios of banks in agriculture, electricity, gas and water increase credit risk. This study suggests the need for further analysis and research about portfolio risks in lending activities for maintaining efficiency and stability in the commercial banking system.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.717-729
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• 2021

This paper examines the efficacy of the default risk factor in an emerging market context using the Fama-French five-factor model. Our aim is to test whether the Fama-French five-factor model augmented with a default risk factor improves the predictability of returns of portfolios sorted on the firm's characteristics as well as on industry. The default risk factor is constructed by estimating the probability of default using a hybrid version of dynamic panel probit and artificial neural network (ANN) to proxy default risk. This study also provides evidence on the temporal stability of risk premiums obtained using the Fama-MacBeth approach. Using a sample of 3,806 firm-year observations on non-financial listed companies of Pakistan over 2006-2015 we found that the augmented model performed better when tested across size-investment-default sorted portfolios. The investment factor contains some default-related information, but default risk is independently priced and bears a significantly positive risk premium. The risk premiums are also found temporally stable over the full sample and more recent sample period 2010-2015 as evidence by the Fama-MacBeth regressions. The finding suggests that the default risk factor is not a useless factor and due to mispricing, default risk anomaly prevails in the Pakistani equity market.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.79-95
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• 2020

The globalization of financial markets has broadened investment opportunities. International investors' investment portfolios consist of financial instruments from various countries; consequently, the risks associated with economic dependence among countries should be carefully considered. Step-down equity-linked securities (ELS) are a structured financial product that have recently become popular among Korean investors. Payoffs are based on two or three stock indices from different regions; therefore, dependence between the indices should be reflected in the risk analysis. In this study, we consider a regime-switching copula model to describe the joint behavior of two stock indices- the Eurostoxx50 and the Hang Seng China Enterprises Index (HSCEI). These indices are commonly used as underlying assets of step-down ELS. Using historical data, we analyze the risk associated with step-down ELS through the probabilities of early redemption. A regime-switching copula model can accommodate complicated dependence. Thus, it should be considered in the risk analysis of step-down ELS.

• 산업경영시스템학회지
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• 제41권4호
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• pp.81-90
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• 2018

Modern investment theory has empirically proved that stock returns can be explained by several factors such as market risk, firm size, and book-to-market ratio. Other unknown factors affecting stock returns are also believed to still exist yet to be found. We believe that one of such factors is the operational efficiency of firms in transforming inputs to outputs, considering the fact that operations is a fundamental and primary function of any type of businesses. To support this belief, this study intends to empirically study the relationship between firm efficiency and stock price performance. Firm efficiency is measured using data envelopment analysis (DEA) with inputs and outputs obtained from financial statements. We employ cross-efficiency evaluation to enhance the discrimination power of DEA with a secondary objective function of aggressive formulation. Using the CAPM-based performance regression model, we test the performance of equally weighted portfolios of different sizes selected based upon DEA cross-efficiency scores along with a buy & hold trading strategy. For the empirical test, we collect financial data of domestic firms listed in KOSPI over the period of 2000~2016 from well-known financial databases. As a result, we find that the porfolios with highly efficient firms included outperform the benchmark market portfolio after controlling for the market risk, which indicates that firm efficiency plays a important role in explaining stock returns.

• 한국산업융합학회 논문집
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• 제25권3호
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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.

• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.287-295
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• 2017

2016년 3월 구글 (Google)의 바둑인공지능 알파고 (AlphaGo)가 이세돌 9단과의 바둑대결에서 승리한 이후 다양한 분야에서 인공지능 사용에 대한 관심이 높아지고 있는 가운데 금융투자 분야에서도 인공지능과 투자자문 전문가의 합성어인 로보어드바이저 (Robo-Advisor)에 대한 관심이 높아지고 있다. 인공지능 (artificial intelligence)기반의 의사결정은 비용 절감은 물론 효과적인 의사결정을 가능하게 한다는 점에서 큰 장점이 있다. 본 연구에서는 기술적 분석 (technical analysis) 지표와 딥러닝 (deep learning) 모형을 결합하여 한국 코스피 지수를 예측하는 모형을 개발하고 제시한 모형들의 예측력을 비교, 분석한다. 분석 결과 기술적 분석 지표에 딥러닝 알고리즘을 결합한 모형이 주가지수 방향성 예측 문제에 응용될 수 있음을 확인하였다. 향후 본 연구에서 제안된 기술적 분석 지표와 딥러닝모형을 결합한 기법은 로보어드바이저서비스에 응용할 수 있는 일반화 가능성을 보여준다.