내재변동성(Implied Volatility)이 주가지수 변동성 예측에 미치는 효과

이준규(Jun-Kyu Lee),한희준(Hee-joon Han) 한국무역연구원 2014 무역연구 Vol.10 No.2

This paper compares GARCH(1.1) model and GARCH-X models using realized kernel and implied volatility. We consider stock index returns of FTSE, CAC and DAX. It is shown that, for the within-sample fitting, most GARCH-X models are better than GARCH(1.1) model. Comparing implied volatility and realized kernel in the GARCH-X model, the GARCH-X model using realized kernel is generally better than the GARCH-X model using implied volatility in the within-sample fitting. However, for out-of-sample forecasting, GARCH-X models using properly powered implied volatility outperform the GARCH-X model using realized kernel.

GARCH-X(1, 1) model allowing a non-linear function of the variance to follow an AR(1) process

Nugroho Didit B,Wicaksono Bernadus AA,Larwuy Lennox 한국통계학회 2023 Communications for statistical applications and me Vol.30 No.2

GARCH-X(1,1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo–Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCH-X(1,1) model. In general, based on the Akaike information criterion, the GARCH-X(1,1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen’s independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.

담배 소비량 데이터에 대한 시계열 모형 적합 및 비교분석

박서영 성균관대학교 응용통계연구소 2020 통계연구 Vol.21 No.-

본 연구에서는 1990년 1월부터 2017년 12월까지 총 28년간의 월별 국내 담배소비량의 시계열 자료를 활용하여 통계적 특성을 확인하고 향후 담배소비량 예측에 적합한 모형을 도출하고자 한다. 시계열 분석 모형들 가운데 정상시계열인 ARMA와 변동성을 포함한 시계열 모형인 GARCH, GJR-GARCH 모형을 사용하고자 한다. 또한 담배 가격을 새로운 변수로 설정하여 ARMAX 모형과 GARCH-X 모형을 적합시켰다. 최종적으로 선택된 모형을 바탕으로 향후 2년간의 월별 담배소비량을 예측하였다.

Some limiting properties for GARCH(p; q)-X processes

Oesook Lee 한국데이터정보과학회 2017 한국데이터정보과학회지 Vol.28 No.3

In this paper, we propose a modified GARCH(p; q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p; q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1; 1)-X model studied by Han (2015) to various GARCH(p; q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1; 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p; q) model combined with proper additional covariate.

Some limiting properties for GARCH(p; q)-X processes

이외숙 한국데이터정보과학회 2017 한국데이터정보과학회지 Vol.28 No.3

In this paper, we propose a modified GARCH(p; q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p; q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1; 1)-X model studied by Han (2015) to various GARCH(p; q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1; 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p; q) model combined with proper additional covariate.

Some limiting properties for GARCH(p, q)-X processes

Lee, Oesook The Korean Data and Information Science Society 2017 한국데이터정보과학회지 Vol.28 No.3

In this paper, we propose a modified GARCH(p, q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p, q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1, 1)-X model studied by Han (2015) to various GARCH(p, q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1, 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p, q) model combined with proper additional covariate.

유가와 주식변동성의 관계

김명현(Myeong-Hyeon Kim) 대한경영학회 2017 대한경영학회 학술발표대회 발표논문집 Vol.2017 No.2

유가와 주식변동성의 관계: 유가하락기를 중심으로

김명현 한국상업교육학회 2018 상업교육연구 Vol.32 No.3

저자는 2010년 1월부터 2016년 3월까지 원유가격의 고공행진과 이어진 하락기에 초점을 두고, 원 유가격과 주식가격의 변동성과의 관계를 개별주식과 산업지수 레벨에서 분석하였다. 뉴욕 상품 거 래소에 상장된 대표 유종인 WTI와 총 12개의 KRX 산업분류 속하는 175개의 개별기업의 주가와 12개의 산업지수 자료를 이용했다. 본 논문의 주요 결론은 다음과 같다. 첫째, 개별주식을 이용한 분석결과 원유가격변동이 개별주 식의 변동성에 미치는 영향은 통계적으로 유의미한 계수 중에서는 음의 관계가 많았으며, 원유가격 변동이 주가변동성에 미치는 영향은 산업마다 이질적 (Heterogeneous)임을 밝혀냈다. 둘째, 산업지 수를 이용한 분석에서 원유가격의 하락이 변동성을 증가시키는 경향이 있다는 점과 상승기의 연구 와 마찬가지로 유가 하락기에도 역시 음의 관계를 보이고 있음을 확인할 수 있었다. 셋째, 산업지수 측면에서는 원유가격의 하락이 변동성을 증가시킨다는 것과 원유가격의 과거 값을 이용한 시차효과 는 국내 주식시장에서는 거의 미비하다는 것을 밝혀냈다. 시차효과 분석을 통해 WTI와 관련된 시 장의 정보처리는 평균적으로 효율적임을 밝혀냈지만 이 경우 역시 산업 간 이질성 역시 차이를 나 타내고 있음도 밝혀냈다. 이 같은 결과는 포트폴리오 구성에서, 개별주식 및 산업 포트폴리오의 이질성 및 원유가격과의 상관관계를 고려할 필요가 있다는 함의를 담고 있다. 구체적으로 개별기업의 변동성과 개별기업의 시장가치가중 합으로 표기되는 산업포트폴리오의 변동성 간의 관계를 활용해 산업포트폴리오의 이 질성을 고려하여 투자 안을 구성할 경우 유가하락기 마켓지수가 하락할 때도 포트폴리오 분산효과 를 누릴 수 있음을 밝혔다. I investigate the impact of the oil price on the second moment of stock returns focusing on the time period ranging from January 2010 to March 2016 when the level of oil price reached the historical peak and the sudden plunge soon after. This paper examines the effects of oil price on return volatilities at the firm return and industry portfolio level during the oil price plunge periods. I use two sets of daily price (West Texas Intermediate) and 175 firms listed on the Korean Stock Exchange spanning from 2010 January to 2016 March. 175 individual stocks are sorted into 12 industries following the KRX industry specifications. 12 Industries of interest include car, semiconductor, health, bank, energy and chemical, steel, media, construction, securities, shipbuilding, insurance, and transportation. Main empirical findings are as follows: i) oil prices affect firm returns differently depending on the sector to which firms are allocated. Specifically, firms that belong to the bank, energy, construction, securities, shipbuilding and transportation sectors exhibit a strong negative relationship between changes in oil price and firm return volatilities, whereas firms that belong to the car, semiconductor, health and media/telecommunication sectors display some positive relationships. This finding implies that decreasing oil prices have heterogeneous effect on firm returns and volatilities. In contrast to the result by Narayan & Sharma (2011), I find no systematic effects of the lagged variables on the stock volatilities. Nonetheless, the heterogeneity among sectors in the analysis using lagged variables still remains in a weaker form. Main findings exhibit important implications for the portfolio diversification. To be specific, it is beneficial to utilize heterogeneous dynamics of individual and sector returns responding to the oil price changes when the market index plummets this destroying the diversification effect.

경제/금융 변수를 이용한 한국 주식시장의 변동성 분석 및 예측

이승희 ( Seung Hee Lee ),한희준 ( Hee Joon Han ) 한국경제학회 2016 經濟學硏究 Vol.64 No.2

본 논문에서는 반모수 단일지표(semiparnmetric single index) 모형을 이용하여 한국 주식시장 수익률의 변동성을 분석하였다. 반모수 단일지표 모형은 변동성의 단기적 변동을 설명하는 GARCH 형태의 모형과 변동성의 장기적 변동을 설명하는 단일지표 모형이 곱해진 형태이다. 이 모형은 관측 가능한 경제/금융 변수 중에서 비정상(nonstationary) 변수들을 단일지표 모형에 포함시킴으로써 금융시계열의 비조건부 분산이 시간에 따라 변하는 비정상성을 설명할 수 있으며, 또한 모형을 반모수적으로 추정하므로 모형설정 오류의 우려를 낮출 수 있다. KOSPI지수수익률의 변동성을 분석한 결과는 경기동행지수, VKOSPI지수, 주택매매가격지수를 이용할 때 한국 주식시장 변동성의 장기적 변동을 가장 잘 설명할 수 있음을 나타냈다. 표본 기간 내 및 기간 외 변동성 예측력을 평가한 결과 기존의 모형들보다 반모수 단일지표 모형이 우월하다는 것을 확인하였다. This paper studies stock market volatility in Korea using a semiparametric single index volatility model, in which a single index long run component induced by exogenous covariates is multiplied to a GARCH short run component. When a covariate is nonstationary, i.e. integrated or nearintegrated, the model can account for time-varying unconditional variance of financial time series. Among various economic and nancial indicators, it is found that the coincident composite index, VKOSPI, and housing price index are helpful in fitting and forecasting stock market volatility in Korea. It is shown that the model using these three variables outperforms standard models both in terms of in-sample fitting and out-of-sample forecasting.

거시경제변수 변동에 따른 산업별 주식시장 반응도 분석

김병준 ( Byoung Joon Kim ) 한국생산성학회 2019 生産性論集 Vol.33 No.4

In this paper, I analyze impacts on Korean individual industry stock market index by changes in macroeconomic variables such as one year monetary stabilization bond (MSB) yield chosen as Korean representative interest rate, Korean won - US dollar foreign exchange rate, and OPEC basket crude oil price. With the sample of 5,543 daily observations from the beginning of 1997 to the end of June, 2019 the summary findings from the regression results of GJR-GARCH-X model are as follows. Interest rate is shown to have significant impacts on only 3 industry stock index returns out of total 16 individual industries, whereas it is confirmed to affect positively nearly none of the stock indices volatilities except for the insurance industry. The reason for the insignificancy of the interest rate impact is due to a fact that most investors can react to the government’s monetary policy as perfectly as possible because the MSB yield does not contain any individual default risk premium. Won-Dollar foreign exchange rate is shown to be the most powerful risk factor in Korea because it has significant impacts on not only 11 industry stock indices returns including 7 manufacturings and 4 services but also nearly all the industry stock indices volatilities with only 3 exceptions of food & beverage, textile & garments, and paper & wood industries. The signs for the significant impacts on the returns of the industries are shown to be negative in the 9 sectors and positive in the two sectors as electrics & electonics and transportation equipments. The negative signs reflect the fact that industry return turns to negative when the FX rate goes up as a result of the deteriorating country fundamentals and the positive signs reflect the fact the industry return turns to positive as the price competitiveness improves as a result of the weakened country currency value. Crude oil price, contrary to the former two factors, shows relatively the same effects to the Korean stock market as expected, affecting significantly major export-oriented industry stock returns and volatilities including petrochemicals, machinery, and electrics & electronics. Considering the fact that won-US dollar FX rate is shown to be the most important risk factor in the Korean stock market affecting significantly almost all the return volatilities that belong to either domestic demand sectors or export oriented sectors, the need for fine tuning policy designs for stabilizing won-Dollar FX rate is clearly verified.