Earticle

We investigate the investment strategies of individual day traders in the Taiwan Index Futures market, along with their impact on market liquidity and volatility. Our results indicate a tendency among most individual day traders to behave as irrational contrarian traders. We also present consistent evidence to show that most individual day traders provide market liquidity by reducing the bid-ask spread, temporary price volatility and the temporal price impacts. Our results, which are consistent with the experimental results of Bloomfield et al. (2009), provide no support for the general criticism that day trading destabilizes the market while also exacerbating market volatility.

This paper investigates the eect of the ETF illiquidity on the ETF tracking error, return, and volatility. Both ETF illiquidity and ETF tracking errors are positively related and are persistent over time. The empirical tests of the liquidity adjusted capital asset pricing model show that illiquid ETFs tend to be more sensitive to underlying index returns or ETF market liquidity, and a positive liquidity premium exists in the US ETF markets. Further, I show that an ETF variance is typically larger than its NAV variance when the ETF is not actively traded. This result conrms that illiquid ETFs are much riskier when market liquidity declines sharply.

본 연구에서는 확률적 변동성하에서 Black-Scholes 옵션 모형과 volatility skew 방식의 가격성과와 헤지성과를 검토하였다. 이를 위해 Heston(1993)의 확률적 변동성 모형이 가정하는 것과 동일한 일련의 주가와 변동성 자료를 시뮬레이션으로 생성하였다. Heston 의 확률적 변동성 모형이 선택된 이유는 Heston 모형이 Black-Schole 모형의 한계를 크게 개선하고 있다는 기존의 실증적 연구에 기반한다. 또한 Heston 모형은 확률적 변동 성 하에서 옵션 가격에 대한 폐쇄형 해를 제공하기 때문에 몬테카르로 시뮬레이션을 수행 하는데 매우 적합하다. Rubinstein(1994)의 콜 옵션 데이터를 활용한 예비적 분석은 Heston 모형과 volatility skew 방식이 Black-Scholes 모형의 표본 내 가격 오차를 대폭 줄이는 것으로 나타났다. 또한 Heston(1993)의 확률적 변동성 모형에서 가정하는 것과 동일한 주가와 옵션 가격을 생성하여 분석한 시뮬레이션에서도 volatility skew 방식이 확률적 변동성으로 야기되는 Black-Scholes 모형의 표본 외 가격 오차를 상당 폭 줄였다. 그러나 헤지성과 측면에서는 Black-Scholes 모형과 volatility skew 방식의 차이가 거의 존재하지 않았다.

In this study, the pricing and hedging performances of the Black-Scholes model and the volatility skew method is examined in the presence of stochastic volatility. To show this stock prices consistent with the Heston’s (1993) stochastic volatility model are generated. Our choice of the Heston (1993) model of stochastic volatility stems from the fact that it provides a closed-form formula necessary in Monte Carlo simulation experiments. The preliminary empirical study utilizing Rubinstein’s data (1994) reveals that the stochastic volatility model and volatility skew method substantially reduces in-sample pricing errors of the Black-Scholes model. Our simulation results also confirms that the volatility skew method can effectively reduce the pricing errors of the Black-Scholes model caused by stochastic volatility. However, in terms of hedging performance, we do not find any significant difference between the Black-Scholes model and the volatility skew method.

We investigate the information content of trading activity in S&P 500 component stocks, S&P 500 index options and VIX options on the future realized volatility of S&P 500 index returns and find that the only consistently useful information on the determination of future realized volatility is provided by trading activity in VIX calls. We also find a discernible increase in the level of predictability when investors are more worried, when the level of information asymmetry in the VIX call market is higher, and when the transaction costs of VIX calls are lower, relative to S&P 500 index options.

In this study, we compare the pricing and hedging performance of options-pricing models using two parameter-estimation methods to employ cross-sectional options data with multiple maturities. In the Portfolio of Volatility Smiles method, each set of parameters that describe the individual volatility smile for each maturity are estimated separately. In the Volatility Surface method, a single parameter set that describes the entire volatility surface is estimated, regardless of the time to maturity. When pricing and hedging options with various times to maturity, the Portfolio of Volatility Smiles method generally outperforms the Volatility Surface method, irrespective of the option-pricing model used, maturity, and moneyness. Considering the volatility smile individually at each maturity is more effective in pricing and hedging options than is considering the volatility surface simultaneously.

The implied volatility from Black and Scholes (1973) model has been empirically tested for the forecasting performance of future volatility and commonly shown to be biased. Based on the belief that the implied volatility from option prices is the best estimate of future volatility, this study tries to find out a better model, which can derive the implied volatility from option prices, to overcome the forecasting bias from Black and Scholes (1973) model. Heston (1993)’s model which improves on the problems of Black and Scholes (1973) model the most for pricing and hedging options is one candidate, and VIX which is the expected risk neutral value of realized volatility under the discrete version is the other. This study conducts a comparative analysis on the implied volatility from Black and Scholes (1973) model, that from Heston (1993)’s model, and VIX for the forecasting performance of future volatility. From the empirical analysis on KOSPI200 option market, it is found that Heston (1993)’s implied volatility eliminates the bias mostly which Black and Scholes (1973) implied volatility has. VIX, on the other hand, does not show any improvement for the forecasting performance.

In this study we examine whether daily S&P 500 index volatility can be modeled parametrically as a long-memory process by extending an integrated process to a fractionally integrated one. The modified R/S test statistic and others are significant at the 1% level of significance, so we reject the null hypothesis of no long-term dependence. We have found that there is strong evidence for long memory in the series analyzed. We compare the out-of-sample forecasting performance of volatility models from 1962 to 2009. For various forecasting horizons, the long-memory FIGARCH model tends to make more accurate forecasts. Our empirical finding that the index volatility has long memory is consistent with prior evidence showing that an asset market volatility model such as plain GARCH puts too much weight on recent observations in the estimation process relative to those of the past. The forecasting model with the lowest MSFE and VaR forecast error among the models we consider is the FIGARCH model. In terms of forecasting accuracy, it dominates the widely accepted GARCH and rolling window GARCH models. We find that the White’s reality check p-values for the FIGARCH (1, 1) expanding window model reject the hypothesis that there exists a better model than the two benchmark models. The Hansen’s p-values report the same results.

This study analyzed the interactions and volatility spillover mechanisms between Bitcoin prices and major economic indicators, including the Dow Jones Index, S&P 500 Index, and gold prices, using a VAR model, Granger causality tests, and Impulse Response Functions (IRFs). The results reveal that the Dow Jones and S&P 500 indices significantly influence Bitcoin prices, with the Dow Jones positively impacting Bitcoin in the short term, while the S&P 500 exerts a negative influence. In contrast, gold prices exhibit a relatively weak interaction with Bitcoin, suggesting limited direct volatility spillover between these two assets. Academically, this research contributes by providing empirical evidence of Bitcoin’s dynamic relationships with traditional financial markets, moving beyond its characterization as an independent digital asset. The use of IRFs to differentiate short- and long-term interactions enhances the understanding of volatility spillover mechanisms in financial markets. Additionally, the findings highlight Bitcoin’s growing integration with traditional markets while maintaining independence, particularly in its distinct divergence from gold as an asset class. Practically, the study identifies the Dow Jones and S&P 500 indices as key predictors of Bitcoin price volatility, offering investors actionable insights for portfolio diversification and trading strategies. Furthermore, the weak relationship between Bitcoin and gold suggests that Bitcoin can serve as an independent alternative investment, providing opportunities for risk management and market diversification. These insights emphasize Bitcoin’s evolving role in the global financial ecosystem and its growing relevance as a strategic asset.

본 연구에서는 한국과 독일의 주식시장을 대상으로 시장변동성의 상호간 전이현상에 관하여 분석하였다. 시장변동성의 전이효과 측정은 대칭 및 비대칭 이변량 GARCH-BEKK 모형을 사용하였는 데 이는 사전에 국가 상호간의 공변적 상관관계에 아무런 제약을 가하지 않은 모형으로 변동성 전이 방 향성 및 강도를 쉽게 파악할 수 있는 장점이 있기 때문이다. 또한 예기치 않은 전일의 수익률충격을 상 승충격과 하락충격으로 구분한 비대칭모형을 사용한 이유도 예기치 않은 수익률 상승의 충격과 예기치 않은 수익률 하락의 전이효과가 일반적으로 서로 다르게 나타나는 이른바 비대칭 현상 때문이다. 한편, 본 연구에서는 1997년 1월 1일부터 2012년 12월 31일까지의 4,173일간의 일별자료를 기준으로 표본을 구 성하였는데 2008년 Lehman Brothers의 파산신청을 계기로 촉발된 전세계적 글로벌 금융위기 국면을 별 도의 소표본으로 독립시켜 변동성 전이현상을 관측하였다. 본 연구에서 연구대상국을 한국과 독일로 선정한 까닭은 여러 가지가 있으나 기본적인 이유를 들자면 다음과 같다. 우선 한국은 비록 2005년부터 개발대상국에서 탈피하여 선진국권으로 분류되고는 있으나 아직까지 개도국권의 영향력을 벗어나지 못하고 있으며 독일은 EU가 창설된 이후 유럽중앙은행 등 대 표적인 EU기구를 관장하고 있는 선진국이라 할 수 있다. 과거 여러 가지 위기 때마다 관측되어 온 사실 은 위기의 진원지가 선진국에 있었을지라도 오히려 그 피해는 개도국권에서 더 많이 발견되었는데 주로 ‘안전지대로의 회피(Flight-to-Quality)’라는 자금흐름의 성격을 반영한 결과였다. 즉, 선진국발 변동성 충격, 특히 하락 충격으로 발생한 충격은 개도국권 시장의 급속한 자금이탈과 더불어 수익률의 급락 등 많은 부작용을 불러왔다. 이를 반영하여 미국과 개도국 간의 충격전이에 관한 연구들은 많이 행해진데 반해 EU의 대표국인 독일과 개도국간의 충격전이에 관한 연구는 아직까지 거의 행하여지지 않았다. 따 라서 본 연구에서는 이 같은 문제점을 인식하여 개도국의 대표국인 한국과 선진국의 대표국인 EU의 독 일을 대상국으로 선정하였다. 본 연구의 분석 결과 나타난 주요 시사점은 다음과 같다. 우선 전체기간 대상, 대칭모형의 추정결과로는 한국에서 독일로의 충격전이가 유의적인 양(+)의 방향 을 나타낸 반면, 독일에서 한국으로의 충격전이는 유의적인 음(-)의 방향을 나타내 독일주식이 한국에 서는 전반적으로 분산투자 효과가 생긴 것으로 판단되었다. 둘째, 전체 표본기간에서의 비대칭 모형의 결과는 상승충격은 양국간 유의적 양(+)의 모습을 보였던 반면 하락충격은 양국간 양뱡향 모두 유의적인 음(-)의 값을 기록하여 결국 시장의 하락충격에서는 양 국이 공통적으로 서로의 충격을 완화시켜 주는 이른바 분산투자의 위험경감효과를 보여주었다. 셋째, 글로벌 금융위기국면에서의 대칭모형의 추정결과를 보면, 전체 국면과는 정반대의 결과를 도출 했는데 즉, 한국에서 독일로의 충격은 유의적인 음(-)으로 나타난 반면 독일에서 한국으로의 충격은 유 의적인 양(+)의 모습을 나타내어 일견 금융위기 때는 선진국의 충격이 더 강하게 전달된다는 사실을 입 증하여 주었다. 그러나 넷째 결과를 보면 이 같은 셋째의 결과를 희석시켜 주는데 비대칭모형의 추정결과는 상승충격 의 경우는 대칭모형과 유사하게 도출되는데 반해 하락충격의 경우 흥미롭게도 독일에서 한국으로의 하 락충격은 유의적인 음(-)의 결과를 보였고 반대로 한국에서 독일로의 하락충격은 유의적인 양(+)의 모 습을 보임으로써 한국에서의 하락충격은 독일로 전달되는데 반해 독일에서의 하락충격은 한국으로 와서 는 그 효과가 상쇄되는 것으로 나타났다. 종합적으로 위의 결과들을 종합하면 본 연구에서 특기할만한 새로운 사실이 도출되었는데 그것은 선 진국에서 그것도 위기국면에서의 하락충격이 한국으로 상쇄효과를 보임으로써 특이하게 독일 주식이 한 국에서의 포트폴리오 전략상 반드시 포함되어야 할 주식인 것으로 발견되었다는 점이다. 이 같은 사실은 변동성 전이에 관하여 많은 연구들 중에서 최초로 입증된 흥미로운 사실이라 할 수 있다.

In this study, mutual volatility spillover effects between stock markets of Korea and Germany have examined, using symmetric and asymmetric bivariate GARCH (generalized autoregressive conditional heteroscedasticity) BEKK (Baba, Engle, Kraft, and Kroner) regression models. The GARCH-BEKK model is based on a framework without any restrictions on the conditional correlations of the multivariate model. Accordingly this model can differentiate directions and magnitudes of volatility spillovers. Additionally, the asymmetric model can differentiate downward shock (resulting from unexpected increase in return) and upward shock (unexpected decrease in return), therefore it is chosen in this study to find out existence of this asymmetry. It is shown that there is a obvious distinction between downward and upward shock from many recent studies. Total sample period of this paper is 4,173 days from the beginning of 1997 to the end of 2012. However, to discover the volatility spillover effect in times of crisis more precisely, I add another sub-sample period of Global Financial Crisis from July 1, 2008 to June 30, 2009. Major findings are as follows. First, shock spillover from Korea to Germany is shown to be significantly positive, contrary to the significantly negative effect of that from Germany to Korea, from the estimation of symmetric model during the whole sample period of 1997 to 2012. Second, downward shock spillovers stemming from the unexpected decrease in market return in both directions turn out to be negative in the whole sample period, suggesting mutual diversification effect between these two countries. Third, during the Global Financial Crisis times, results for the shock spillovers from the symmetric model are changed to be just the opposite from the results during the whole sample period. In other words, shock spillover from Germany to Korea turns out to be positive whereas that from Korea to Germany is shown to be negative. Finally and most importantly, downward shock from Germany to Korea during the GFC times turns out to be significantly negative while that from Korea to Germany shows still positive, signaling diversification effect in portfolio formation from Korea especially in the crisis times. The last finding is perhaps for the first time and quite surprising and valuable among the studies for international volatility spillovers in the global stock market. The last finding is the existence of significantly negative shock spillover, i.e., shock reduction from the developed market to the emerging market.

It is well known that the pattern of implied volatilities in foreign currency options forms a smile shape which is referred to as a volatility smile. On the other hand, the volatility skew is a general pattern of implied volatilities in equity options. In this paper, we consider the Carr-Geman-Madan valuation of options in incomplete markets on which the preference structure of the market participants are reflected. Through a simple continuous static no arbitrage extension, we examine how the smiles and skews are related.

Motivated by the mixed findings of the existing literature, we investigate the performance of the volatility targeting strategy in four Asian equity markets based on a block-bootstrap simulation. We found no clear evidence of outperformance of the strategy against a 50/50 constant-mix portfolio, except in the Chinese market where volatility and tail risk are highest. The lack in performance has been attributed to an inability to detect the negative relationship between volatility and returns by all of the volatility forecasting models we consider. This may affect the capacity to reduce downside risk and tail risk but consistently causes a substantial drag on performance. Owing to forecasting errors, the strategy appears to perform considerably better and easier to implement in practice when using a model with low sensitivity to volatility changes along with a rebalancing buffer.

This paper investigates asymmetries in volatility connectedness among the G7 stock markets. Using daily realized semi-volatility indices, obtained from intra-day data, we provide ample evidence for the asymmetric volatility connectedness. We find that the impact of bad volatility strictly dominates that of good volatility in generating connectedness across financial markets. In particular, the global financial crisis and the European debt crisis have witnessed most influential episodes of volatility connectedness. We also discuss that the effect of the US stock market on other countries has been largely due to bad volatility.

Based on the theory of a wedge between the physical and risk-neutral conditional volatilities in Christoffersen, Elkamhi, Feunou, and Jacobs (2009), we develop a modification on the GARCH option pricing model with the filtered historical simulation proposed in Barone-Adesi, Engle, and Mancini (2008). The current conditional volatilities under the physical and risk-neutral measures are the same in the previous model, but should have been allowed to be different. Using extensive data on S&P 500 index options, our approach, which employs the current risk-neutral conditional volatility estimated from the cross-section of the option prices (in contrast to the existing GARCH option pricing models), maintains theoretical consistency under conditional non-normality as well as improves the empirical performances. Remarkably, the risk-neutral volatility dynamics are stable over time under this model. In addition, the comparison between the VIX index and the riskneutral integrated volatility validates our approach economically.

현재 글로벌 무역 구조는 규칙 기반 세계화에서 권력 기반 지정학적 경제로의 전환이라는 패러다임 변화를 겪고 있다. 트럼프 2차 행정부 ("트럼프 2.0")가 "미국 우선주의" 정책을 실행에 옮기면서, 그 결과로 나타나는 무역 정책의 변동성은 글로벌 공급망에 중대한 외생적 충격으 로 작용하고 있다. 본 연구는 미국-멕시코-캐나다 협정(USMCA) 체제를 중심으로 이러한 변동 성이 국제 무역 흐름에 미치는 구조적 영향을 실증적으로 분석하였다. 2018~2019년의 관세 부 과 사례가 주로 거래적 성격을 띠었던 것과는 달리, 2025년에 관찰되는 정책들은 산업 주권을 위한 구조적 도구로 작용하여 주요 수출 지향 경제의 위험 계산 방식을 근본적으로 변화시키 고 있는 것으로 나타났다. 본 연구의 주요 목적은 새 행정부의 공격적인 관세 정책이 초래하는 실제 위험과 그것이 국내 수출 산업에 미치는 구체적인 영향을 분석하는 것이다. 본 논문은 국제 무역 및 관세 행정 데 이터를 중심으로 한 포괄적인 메타데이터 분석 접근 방식을 활용하여 이질적인 데이터 세트를 종합하고 기업에 부과되는 "불확실성 비용"을 정량화하였다. 분석은 특히 북미 가치 사슬에 깊이 통합되어 있지만 원산지 규정(ROO)의 강화된 시행과 보편적 기본 관세의 위협으로 인해, 장벽이 높아진 자동차 및 철강과 같은 주요 부문의 취약성을 대상으로 하는데에 그 차별성이 있다 하겠다. 연구 결과는 "트럼프 2.0" 체제가 강력한 비관세 장벽으로 작용하여 "양분된 위험" 환경을 조 성한다는 것을 명확하게 보여주고 있다. USMCA 지역은 지역 공급망을 통합하는 것을 목표로 하지만, 행정부의 무역 권한의 변동성은 비회원국 경제에 심각한 적응 비용을 부과하여 기존 자유 무역 협정의 이점을 사실상 무력화하고 있다. 따라서 본 연구는 기존의 "적시 생산 (Just-in-Time)" 효율성 모델이 더 이상 실현 가능하지 않는 것으로 결론 내릴 수 있겠다. 대신, 이는 "만일의 사태에 대비한" 복원력으로의 전략적 전환을 제안하며, 지정학적 경제 분열의 영향을 완화하기 위해 물류 네트워크의 근본적인 재구성과 선제적 정책 대응이 필요한 정책 제언으로서의 가치를 가지고 있다고 분석하였다.

Purpose : This study empirically investigates the structural implications of this volatility on international trade flows, with a specific focus on the United States-Mexico-Canada Agreement (USMCA) framework. Unlike the tariff episodes of 2018-2019, which were largely transactional, the policies observed in 2025 manifest as structural tools for industrial sovereignty, fundamentally altering the risk calculus for major export-oriented economies. Research design, data, methodology : The primary objective of this research is to analyze the realized risks of the new administration’s aggressive tariff policies and their specific impact on domestic export industries. Utilizing a comprehensive meta-data analysis approach centered on international trade and customs administration data, this paper synthesizes heterogeneous datasets to quantify the "ambiguity costs" imposed on firms. The analysis specifically targets the vulnerability of key sectors—such as automotive and steel—that are deeply integrated into North American value chains but face heightened barriers due to stricter enforcement of Rules of Origin (ROO) and the threat of universal baseline tariffs. Results : The findings reveal that the "Trump 2.0" regime functions as a formidable non-tariff barrier, creating a "bifurcated risk" environment. While the USMCA region aims to consolidate regional supply chains, the volatility of executive trade authority imposes severe adaptation costs on non-member economies, effectively neutralizing the benefits of traditional free trade agreements. Conclusions : Consequently, this study argues that the prevailing "Just-in-Time" efficiency model is no longer viable. Instead, it proposes a strategic pivot toward "Just-in-Case" resilience, necessitating a fundamental reconfiguration of logistics networks and proactive policy responses to mitigate the impacts of geoeconomic fragmentation.

The purpose of this paper is to estimate the fluctuation of an earning rate and risk management using the price index of Korea stocks. After an observation of conception of fluctuation, we can show volatility clustering and fluctuation phenomenon in the Korea stock price index using GARCH model with heteroscedasticity. In addition, the effects of fluctuation on the time-series was evaluated, which showed the heteroscedasticity. MCMC method and Winbugs as Bayesian computation were used for analysis.

This study investigates whether stochastic volatility is priced on KOPSI 200 index options by using the delta-hedged gains on a portfolio of a long position in a call, hedged by a short position in the underlying asset, following Bakshi and Kapadia (2003). Contrary to other financial markets such as the S&P index options market, volatility risk is not systematically and consistently compensated on the KOSPI options. Rather jump fear influences most in determining KOSPI 200 option prices. Our results are consistent with extant literatures which have shown that Korean derivatives market is dominated by directional traders, and so there might be no hedging demands on option trades. In our research, we do not impose any specification on the stochastic processes of the underlying asset, volatility, and jumps, consequently setting our results free from misspecification errors.

We investigate the impact of price limit expansion on stocks’ realized volatility, uniquely integrating both magnet effect and correction effect into our model. Our findings reveal that price limit expansion may increase or decrease stock volatility, with the magnet effect and stocks’ inherent volatility levels as primary driving forces, and the correction effect playing a minor role. Typically, a decrease in volatility occurs when a stock’s inherent volatility is moderate (i.e., neither too high nor too low), while an increase takes place when it is relatively high. We offer an insightful explanation of these contrasting behaviors in relation to the magnet effect and stocks’ inherent volatility.