• Asian Journal of Business Environment
• /
• 제11권4호
• /
• pp.17-29
• /
• 2021

Purpose: The aim of this study is to explore the dynamic linkage between conditional stock market volatility and macroeconomic uncertainty of Bangladesh. Research design, data, and methodology: This study uses monthly data covering the time period from January 2005 to December 2018. A comprehensive set of macroeconomic variables, namely industrial production index (IP), consumer price index (CPI), broad money supply (M2), 91-day treasury bill rate (TB), treasury bond yield (GB), exchange rate (EX), inflow of foreign remittance (RT) and stock market index of DSEX are used for analysis. Symmetric and asymmetric univariate GARCH family of models and multivariate VAR model, along with block exogeneity and impulse response functions, are implemented on conditional volatility series to discover the possible interactions and causal relations between macroeconomic forces and stock return. Results: The analysis of the study exhibits time-varying volatility and volatility persistence in all the variables of interest. Moreover, the asymmetric effect is found significant in the stock return and most of the growth series of macroeconomic fundamentals. Results from the multivariate VAR model indicate that only short-term interest rate significantly influence the stock market volatility, while conditional stock return volatility is significant in explaining the volatility of industrial production, inflation, and treasury bill rate. Conclusion: The findings suggest an increasing interdependence between the money market and equity market as well as the macroeconomic fundamentals of Bangladesh.

• The Journal of Asian Finance, Economics and Business
• /
• 제8권9호
• /
• pp.143-154
• /
• 2021

This study aims to explore the dynamic conditional correlation (DCC) between ten Asian stock indexes, the US stock index, and Bitcoin by using the dynamic conditional correlation model. The time span of the daily data is between January 2015 to May 2021, the total observation is 1,116. DCC(1,1)-EGARCH(1,1) with multivariate t and normal distributions for the DCC and EGARCH models, respectively, outperforms other models by the goodness of fit values. Except for Bitcoin, we discovered that the majority of the securities' volatilities have a very high volatility persistence. Furthermore, the negative shocks/news have more impact on the volatilities than positive shocks/news in most of the cases, except the stock index of China and Bitcoin. Most of the correlation pairs exhibit higher correlation during the COVID-19 pandemic compared to the pre-COVID-19, except Hong Kong-The US and Malaysia-Indonesia. Moreover, the correlation between Asian stock indexes during the COVID-19 pandemic is statistically higher than the pre-COVID-19 pandemic. However, there are a few instances where the Hong Kong stock index and a few countries are identical. The result of correlation size shows the connectedness between Asian stock markets, which are well-connected within the region, especially with South Korea, Singapore, and Hong Kong.

• Communications for Statistical Applications and Methods
• /
• 제20권3호
• /
• pp.169-174
• /
• 2013

The ROC curve is drawn with two conditional cumulative distribution functions (or survival functions) of the univariate random variable. In this work, we consider joint cumulative distribution functions of k random variables, and suggest a ROC curve for multivariate random variables. With regard to the values on the line, which passes through two mean vectors of dichotomous states, a joint cumulative distribution function can be regarded as a function of the univariate variable. After this function is modified to satisfy the properties of the cumulative distribution function, a ROC curve might be derived; moreover, some illustrative examples are demonstrated.

• Journal of the Korean Statistical Society
• /
• 제28권4호
• /
• pp.399-413
• /
• 1999

• 응용통계연구
• /
• 제23권4호
• /
• pp.651-668
• /
• 2010

금융 포트폴리오의 두 위험측도인 VaR와 ES에 대한 여러 추정방법을 1일 후와 10일 후의 경우로 나누어 각각 비교하였다. 2008년 미국발 세계 금융위기 기간을 포함한 KOSPI 자료와 해외 5개국의 종합주가지수 자료를 이용하여 실증적으로 비교하였다. 손실 분포의 두터운 꼬리와 조건부 이분산성을 동시에 고려하는 방법을 중심으로 여러 방법을 추가적으로 고려하였고, 국내 자료에 어떤 방법이 적절하며 종합적인 성능은 어떤가를 살펴보았다.

• 한국지반공학회지:지반
• /
• 제4권2호
• /
• pp.5-14
• /
• 1988

균질토 사면에서 진행성 파괴에 대한 확를론적 모델이 제시되었다. 파괴면 위의 어떤 절편에 대한 국부적인 Safety Margin은 정규분포차 가정하였다. 파괴면을 따라 존재하는 전단강도의 불확실성은 1차원 Random Field Models로 표현되었다. 이 연구에서는 파괴가 Toe에서 시작되어 사면 정상까지 진행되는 경우만을 고려하였다. 파괴면위의 어느 두 인접 절편의 Safety Margin의 Joint Distribution은 Bivariate Normal로 가정하였다. 활동파괴의 전체적인 파괴확률은 일련의 Conditional events의 급으로 표현되었다. 최종적으로 개발된 절차가 절취사면의 신뢰도를 얻기 위하여 한 예에 적용되었다.

• 대한수학회논문집
• /
• 제17권3호
• /
• pp.535-540
• /
• 2002

Let X$_1$, X$_2$‥‥,X$\_$n/ be n independent and identically distributed random variables with continuous cumulative distribution function F(x). Let us rearrange the X's in the increasing order X$\_$1:n/ $\leq$ X$\_$2:n/ $\leq$ ‥‥ $\leq$ X$\_$n:n/. We call X$\_$k:n/ the k-th order statistic. Then X$\_$n:n/ - X$\_$n-1:n/ and X$\_$n-1:n/ are independent if and only if f(x) = 1-e(equation omitted) with some c > 0. And X$\_$j/ is an upper record value of this sequence lf X$\_$j/ > max(X$_1$, X$_2$,¨¨ ,X$\_$j-1/). We define u(n) = min(j|j > u(n-1),X$\_$j/ > X$\_$u(n-1)/, n $\geq$ 2) with u(1) = 1. Then F(x) = 1 - e(equation omitted), x > 0 if and only if E[X$\_$u(n+3)/ - X$\_$u(n)/ | X$\_$u(m)/ = y] = 3c, or E[X$\_$u(n+4)/ - X$\_$u(n)/|X$\_$u(m)/ = y] = 4c, n m+1.

• Journal of the Korean Data and Information Science Society
• /
• 제25권5호
• /
• pp.1079-1094
• /
• 2014

상호정보 (mutual information)를 이용한 변수 선택법은 반응변수와 설명변수간의 선형적인 연관성뿐만 아니라 비선형적인 연관성을 감지하며, 설명변수 사이의 연관성도 고려하는 좋은 변수선택 방법이다. 하지만 고차원 자료에서 상호정보를 추정하기가 쉽지 않아 이에 대한 연구가 필요하다. Cai 등 (2009)은 조건부 상호정보를 이용한 전진선택법과 가지치기법을 이용하여 이러한 문제를 해결하였으며, 마이크로어레이 자료와 같은 고차원 자료에서 조건부 상호정보를 이용한 변수 선택법으로 선택된 변수들로 구성된 SVM의 분류 성능이 SVM-RFE 및 기존의 필터링 방법으로 선택된 변수들로 구성된 SVM의 분류 성능보다 뛰어남을 보였다. 하지만 조건부 상호정보를 추정할 때 사용된 Parzen window 방법은 변수의 수가 많아질수록 변수 선택 시간이 길어지는 단점으로 인해 이에 대한 보완이 필요하다. 본 논문에서는 조건부 상호정보 계산 시 필요한 설명변수의 분포를 다변량 정규분포로 가정함으로써 변수선택을 위한 계산시간을 단축시키며 동시에 변수선택의 성능을 향상시키고자 한다. 반면, 설명변수의 분포를 다변량 정규분포로 가정한다는 것은 강한 제약이 될 수 있으므로 이를 완화시킨 Edgeworth 근사를 이용한 조건부 상호정보 기반의 변수 선택법을 제안한다. 실증분석을 통해 본 논문에서 제안한 방법의 효율성을 살펴보았으며, 기존의 조건부 상호정보 기반 변수 선택법에 비해 계산 속도나 분류 성능 면에서 우수함을 보였다.

• The Journal of Asian Finance, Economics and Business
• /
• 제8권5호
• /
• pp.533-542
• /
• 2021

The main objective of this article is to investigate the existence of the lunar effect during the full moon period (FM period) and the new moon period (NM period) on the selected Islamic stock market returns and volatilities. For this purpose, the Ordinary Least Squares model, Autoregressive Conditional Heteroscedasticity model, Generalised Autoregressive Conditional Heteroscedasticity model and Generalised Autoregressive Conditional Heteroscedasticity-in-Mean model are employed using the mean daily returns data between January 2010 and December 2019. Next, the log-likelihood, Akaike Information Criterion and Schwarz Information Criterion value are analyzed to determine the best models for explaining the returns and volatility of returns. The empirical results have deduced that, during the NM period, excluding Malaysia, the total mean daily returns for all of the selected countries have increased mean daily returns in contrast to the mean daily returns during the FM period. The volatility shocks are intense and conditional volatility is persistent in all countries. Subsequently, the volatility behavior tends to have lower volatility during the FM period and NM period in the Islamic stock market, except Malaysia. This article also concluded that the ARCH (1) model is the preferred model for stock returns whereas GARCH-M (1, 1) is preferred for the volatility of returns.

• Journal of the Korean Data and Information Science Society
• /
• 제23권4호
• /
• pp.797-805
• /
• 2012

Many circular distributions are known to be not only asymmetric but also bimodal. Hidden truncation method of generating asymmetric distribution is applied to a bivariate circular distribution to generate an asymmetric circular distribution. While many other existing asymmetric circular distributions can only model an asymmetric data, this new circular model has great flexibility in terms of asymmetry and bi-modality. Some properties of the new model, such as the trigonometric moment generating function, and asymptotic inference about the truncation parameter are presented. Simulation and real data examples are provided at the end to demonstrate the utility of the novel distribution.