• The Journal of Asian Finance, Economics and Business
• /
• 제6권4호
• /
• pp.45-52
• /
• 2019

The current study aims to investigate the relationship between tax avoidance and firm risk in an emerging market called Iran. The study population consists of 400 observations and 80 companies listed on the Tehran Stock Exchange (TSE) over a five-year period during 2012 and 2016. The statistical model used in this study is a multivariate regression model; besides, the statistical technique used to test the hypotheses proposed in this research is panel data. The results showed that low effective tax rate (tax avoidance) is more consistent than the higher effective tax rate. Moreover, there is no significant relationship between tax avoidance and future tax rate volatility. The findings also proved that lower effective tax rates are positively associated with future stock price volatility. This implies that since Iranian firms have many financial problems because of economic sanctions, they have a tendency to delay the disclosure of bad news about their firms. Needless to say, when a huge number of negative news reaches its peak, they immediately will enter the market and lead to a remarkable fluctuation in stock prices.

• KDI Journal of Economic Policy
• /
• 제33권4호
• /
• pp.27-48
• /
• 2011

본 연구는 주가지수를 경제적 척도로 삼아 동아시아의 글로벌 및 역내 통합의 정도를 검토하였다. 주가에 대한 충격을 글로벌 충격, 역내 충격 및 개별 국가 충격으로 분해하고 구조적 VAR 모형을 사용하여 이들 충격이 동아시아 국가들의 주가 변동에 미친 영향을 살펴본 결과, 1997년 금융위기 이후 점차 축소되는 추세이나 개별 국가 충격이 여전히 가장 주도적인 역할을 하는 것으로 나타났다. 반면에 글로벌 및 역내 충격은 대부분의 동아시아 국가에서 그 비중이 점차 확대되는 추세이나 영향력은 그리 크지 않았다. 본고의 분석 결과는 최근의 자유화 및 역내 통합 진전에도 불구하고 동아시아 국가들은 아직까지 상호 이질적이며 유럽 국가에 비해 비대칭적인 충격에 더 크게 노출되었음을 의미한다.

• Journal of the Korean Data and Information Science Society
• /
• 제28권6호
• /
• pp.1471-1479
• /
• 2017

아파트매매 가격지수의 변동은 국가의 경제뿐만 아니라 사회, 산업, 문화 등의 전 분야에 영향을 준다. 본 연구에서는 아파트매매 가격지수를 거시경제변수로 설명하는 시계열모형을 연구하고자 한다. 설명변수로 사용한 거시경제변수는 우리나라 주택담보 대출금리, 원유수입 물가지수, 소비자 물가지수, KOSPI 주가지수, 국내총생산 (GDP), 국민총소득 (GKI)의 6가지 변수를 사용하였다. 아파트매매 가격지수와 모든 경제변수는 2001년 9월부터 2017년 5월까지 약 16년간의 월별 자료를 사용하였다. 아파트매매 가격지수 자료의 설명을 위해 시계열 모형 중 자기회귀오차 (ARE) 모형을 사용하여 분석하였다. ARE 모형 분석 결과 아파트매매 가격지수는 1개월 전 아파트매매 가격지수, 주택담보 대출금리와 KOSPI 주가지수에 의해 영향을 받는 것으로 나타났다.

• The Journal of Asian Finance, Economics and Business
• /
• 제7권12호
• /
• pp.683-692
• /
• 2020

The primary purpose of the study is to investigate the volatility spillovers from global economic policy uncertainty and macroeconomic factors to the Islamic stock market returns. The study focuses on the Islamic stock indices of emerging economies including Indonesia, Malaysia, and Turkey. The Macroeconomic factors are industrial production, consumer price index, exchange rate. EGARCH model is employed for investigation of volatility spillovers. The results show that the global economic policy uncertainty has a significant spillover effect only on the returns of Turkish Islamic stock index. Similarly, the shocks in macroeconomic factors have little influence on the volatility of Islamic indices returns. The volatility of Indonesian and the Turkish Islamic stock indices returns is not influenced from the fluctuations in macroeconomic factors. However, there is significant volatility spillover only from industrial production to the returns of Malaysian Islamic index. The results suggest that the Islamic stock markets are less likely to influence from the global economic policies and macroeconomic factors. The stability of Islamic stocks provide opportunity for diversification of portfolios, particularly in stressed market conditions. The major price factors of Islamic markets could be firms' specific factors or investors' behaviors. The findings are helpful for policy makers and investors in formulating policies and portfolios.

• The Journal of Asian Finance, Economics and Business
• /
• 제6권2호
• /
• pp.257-267
• /
• 2019

The paper aims to test long-term and short-term causality from four exchange rates, the Korean won/$US, the Korean won/Euro, the Korean won/Japanese yen, and the Korean won/Chinese yuan, to the Korea Composite Stock Price Index in the presence of several macroeconomic variables using monthly data from January 1986 to June 2018. The results of Johansen cointegration tests show that there exists at least one cointegrating equation, which indicates that long-run causality from an exchange rate to the Korean stock market will exist. The results of vector error correction estimates show that: for long-term causality, the coefficient of the error correction term is significant with a negative sign, that is, long-term causality from exchange rates to the Korean stock market is observed. For short-term causality, the coefficient of the Japanese yen exchange rate is significant with a positive sign, that is, short-term causality from the Japanese yen exchange rate to the Korean stock market is observed. The coefficient of the financial crises i.e. 1997-1999 Asian financial crisis and 2007-2008 global financial crisis on the endogenous variables in the model and the Korean economy is significant. The result indicates that the financial crises have considerably affected the Korean economy, especially a negative effect on money supply.

• Journal of the Korean Data and Information Science Society
• /
• 제23권2호
• /
• pp.271-283
• /
• 2012

본 연구에서는 모든 산업을 총합한 종합주가지수 예측을 다루는 기존의 연구들과는 달리 11개의 대표 산업별 주가지수의 상승 및 하락을 예측하였다. 해외경제상황에 큰 영향을 받는 우리나라 주식 시장을 고려하여 국내 경제지표뿐만 아니라 미국, 일본, 중국, 유럽의 주요 경제지표를 예측변수로 사용하였다. 2001년부터 2011년까지 총 132개의 월별 자료에 대하여 로지스틱 회귀모형과 신경망모형에 의한 분석은 대체로 60% 내외의 정확도를 보였다.

• The Journal of Asian Finance, Economics and Business
• /
• 제6권4호
• /
• pp.37-43
• /
• 2019

The research aims to study the relationship between export performance and stock return of Vietnamese fishery companies. To conduct this study, quarterly data was collected for period from 2010-2018 of 13 fishery companies listing in Ho Chi Minh Stock Exchange (HOSE) and Ha Noi Stock Exchange (HNX). The export performance was measured by export intensity, export growth and export market coverage. In addition, interest rate, exchange rate, GDP, firm size, profitability, and financial leverage were considered as the control variables in the research model. Panel data analysis with Generalized Least Squares model was employed to estimate the predictive regression. The findings indicated that export intensity and export growth have a significant and positive relationship with stock returns. However, export market coverage has not a significant relationship with stock return at the 0.05 level. Profitability, financial leverage, and exchange rate have a positive relationship, while interest rate and GDP have no relation to stock return at the 0.05 significance level. The findings imply that investors should consider the export intensity instead of export growth and export market coverage as selecting stock of fishery exports firms to invest; managers should increase export intensity to increase company's stock price or firm market value.

• 한국정보통신학회논문지
• /
• 제25권1호
• /
• pp.1-7
• /
• 2021

최근 코로나 19발생과 동시에 소셜 미디어의 투자자 정서가 증시 가격 움직임을 주도해 관심을 모으고 있다. 본 연구는 행동금융 이론 기반 빅 데이터 분석을 활용하여 소셜 미디어에서 추출한 정서가 중국 증시의 실시간 및 단기적 가격 모멘텀을 예측하는데 활용될 수 있는 기법을 제안한다. 이를 위해, COVID-19와 관련 200만 건 이상의 시나 웨이보 빅 데이터를 키워드 방식으로 수집 및 분석하고 시간이 따른 영향력이 높은 감정 요인을 추출한다. 최종 결과 도출을 위해 다양한 지도 및 비지도 학습 모델을 다 각도에서 구현 및 성능평가를 비교 분석 후, BiLSTM mdoel이 최적의 결과를 낼 수 있음을 증명했다. 또한, 제안하는 기법을 통해 주가변동과 심리요인 간에도 비슷한 움직임을 보이고 있음을 제안했고 소셜미디어에서 추출한 공공분위기가 어느 정도 투자자들의 심리를 대변할 수 있고, 주식시장에 영향을 미칠 수 있는 특수행사에 몰두할 때 증시변동에 차이를 만들 수 있음을 증명했다.

• 한국수학교육학회지시리즈B:순수및응용수학
• /
• 제21권4호
• /
• pp.295-305
• /
• 2014

Yan & Hanson [8] and Makate & Sattayatham [6] extended Bates' model to the stochastic volatility model with jumps in both the stock price and the variance processes. As the solution processes of finding the characteristic function, they sought such a function f satisfying $$f({\ell},{\nu},t;k,T)=exp\;(g({\tau})+{\nu}h({\tau})+ix{\ell})$$. We add the term of order ${\nu}^{1/2}$ to the exponent in the above equation and seek the explicit solution of f.

• Communications for Statistical Applications and Methods
• /
• 제28권1호
• /
• pp.39-57
• /
• 2021

Time series prediction is an area of great interest to many people. Algorithms for time series prediction are widely used in many fields such as stock price, temperature, energy and weather forecast; in addtion, classical models as well as recurrent neural networks (RNNs) have been actively developed. After introducing the attention mechanism to neural network models, many new models with improved performance have been developed; in addition, models using attention twice have also recently been proposed, resulting in further performance improvements. In this paper, we consider time series prediction by introducing attention twice to an RNN model. The proposed model is a method that introduces H-attention and T-attention for output value and time step information to select useful information. We conduct experiments on stock price, temperature and energy data and confirm that the proposed model outperforms existing models.