Search results

This paper examines the price discovery process among the Korea stock index markets using the vector error correction model (VECM) and the multivariate generalized auto regressive conditional heteroskedasticity (M-GARCH) model. The minute-by-minute price series of the KOSPI200 index, KOSPI200 futures, and KODEX200 are cointegrated.

The empirical results are summarized as follows: First, VECM estimation results indicate that when the cointegrating relationship is perturbed by the arrival of ntis, the KODEX200(ETF) does not adjusted to restore equilibrium. This is the task of the KOSPI200 futures and spot. These two index securities use the KODEX200 to represent the ntioequilibrium price, with the KOSPI200 futures responding faster than the KOSPI200 spot. When the cointegrating relationship betweeiesOSPI200 spot and futues is perturbed by the arrival of ntis, the KOSPI200 spot does adjusted to restore equilibrium. Next, the results from the multivariate GARCH modes indicate that the volatilities of esOSPI200 spot and futures markets suggest unidirectiona1volatility spillover from KOSPI200 futures to KOSPI200 spot. KODEX200(ETF) volatilities spill over bothesOSPI200 spot and futures markets. and this happen in the reverse direction with a strong effect from the KODEX200 to KOSP200 futures and spot.

The overall findings indicate that the KODEX200(ETF) market dominates KOSPI200 futures and spot in the price discovery process. The regulation of Instutional traders on trading on futures markets explains its superior price discovery function.

It is known that the National Pension Service (NPS) of Korea contributes to the market stability because it tends to pursue the negative feedback trading strategy in the Korean stock market. While many studies deal with institutional investors’ trading in the financial derivatives market, the NPS’s trading in the derivatives market is rarely studied. Using the NPS’s trading data for the period from January 2010 to March, 2020, the authors examine the transactions of the NPS in the KOSPI200 futures market. We find that the NPS’s net investment flow (NIF) in KOSPI200 futures is negatively associated with the past returns of KOSPI200 futures and the KOPI200 index. However, we also find that the NPS’s NIF of KOSPI200 futures is positively associated with its NIF in KOSPI200 stocks. Along with the legal restriction on the NPS’s trading in the derivatives market, the result suggests that the NPS uses KOSPI200 futures to deviate the problems related to non-synchronous trading in the spot market. To the best of our knowledge, this paper is the first study of the NPS’s transactions of KOSPI200 futures. The paper suggests that the NPS does not trade KOSPI200 futures for hedging or arbitrage profit but for complementing its transactions in the spot market of KOSPI200 stocks.

This study tests empirically the impacts that the issue and redemption of index-typed ELS has on KOSPI200 & KOSPI200 Future Index and the performance of ELS redemption by using daily stock market data of year 2010-2015. The first one of research results is that net amount of ELS issue has significantly negative (-) effect on KOSPI200 Index and KOSPI200 Future Index, which ascertains that the amount of ELS issue becomes larger as KOSPI200 Index gets lower. It shows that index-typed ELS has reverse-hedging effect while underlying stock-typed ELS has hedging effect. This phenomenon seems to have arisen in the complex conditions of ELS structural traits and vulnerable situations of security market where KOSPI Index has moved up and down with in-box pattern and KOSPI200 trading volume and KOSPI200 Future trading amount & volume have been decreasing consistently. Second result is that ELS performance in advanced redemption fund (principal non-guarantee type) shows the fact that return of private equity fund has been significantly 0.37% higher than that of public offering fund, while performance in maturity redemption fund (principal guarantee type) shows the fact that return of public offering fund has been significantly 1.26% higher than that of private placement. Considering of the meager difference of return in advanced redemption fund and the higher return of public offering fund in maturity redemption fund, we can infer that efficiency of ELS market would leave no information asymmetry by the difference between the fund-raising types.

The National Pension Service (NPS) of Korea is one of the largest institutional investors in the world and it has been known as the market stabilizer in the Korean stock market. Nevertheless, it is hard to find the research about the impact of the NPS on the futures market. We investigated the effect of the NPS’s trading KOSPI200 futures on the returns, the liquidity and the volatility of the market using the recent ten years’ transaction data. The main findings are as follows. First, the NPS’s net investment flow (NIF) in the KOSPI200 futures market shows the predictability about the returns of both KOSPI200 futures and KOSPI200 spot index. Second, the NPS’s NIF in the KOSPI200 futures market improves the liquidity of the KOSPI market, where the transactions involved in both the spot market and the futures market occur. Third, the NPS’s NIF in the KOSPI200 futures market reduces the volatility of both the KOSPI200 futures market and the KOSPI market. Unlike the prior studies showing that our futures market tends to increase the volatility of the stock market through the volatility transfer, our finding suggests that the NPS’s trading KOSPI200 futures contributes to decreasing the volatility in both markets. To the best of the authors’ knowledge, this paper is the first study that investigates the impact of the NPS’s trading KOSPI200 futures on the KOSPI200 futures market and the stock market. It shows that the NPS plays a role of the market stabilizer in the futures market. In addition, the NPS’s trading KOSPI200 futures also affects the KOSPI stock market, stabilizing it in terms of both the liquidity and the volatility.

This study examines the lead-lag relationship between KOSPI200 and the volatility index based on the implied volatility from the KOSPI200 options. The sample period covers from January 2, 2003 to June 30, 2004. Both daily and minute-by-minute data were used for the lead-lag analysis. The study also determines whether the response of volatil ity index to KOSPI200 is symmetric or not. The most important findings may be summarized as follows.

First, there is no lead-lag relationship between the change in volatility index and the KOSPI200 returns on a daily basis. However, on a minute-by-minute basis, volatility index leads KOSPI200 for the group of largest increases in volatility index, and the opposite is true for the group of largest decreases and least changes in volatility index. The option market appears to react more quickly to volatility increases, while the stock market seems more sensitive to volatility decreases. Second, the volatility increase in response to the stock market decline is more severe than the volatility decrease in response to the stock market rise for daily data. This evidence of asymmetry suggests that volatility index plays a role of investors’fear gauge. Our results show no asymmetric response of volatility index to stock market movements for weekly data.

This paper presents 6 time-series that have negative correlation with KOSPI200 Index and a quantitative trading methodology based on stochastic control chart using these time-series. The proposed quantitative trading framework detects trade (long or short) timing by monitoring whether a time-series touches 4 trigger lines, which play a role as control limits in control chart. In other words, a time-series upwardly touches one of trigger line, then the framework take a short position on KOSPI200 Index Futures, while in case of downward touch, it takes a long position. The 6 time-series are derived from VKOSPI and USD Futures Index that are negatively correlated with KOSPI200 Index, and have a significance that prevents disclosure of trading strategies by processing and transforming the original time-series. Computational experiments using real KOSPI200 futures index for recent 4 years are conducted to show the excellence of the proposed investment strategies against benchmark strategies under quantitative trading framework.

This paper develops “Strategy Benchmark Index (SBI)” using KOSPI200 options data from January 2004 to March 2017, and then investigates their performances. The SBIs were constructed in the same way as those published daily by CBOE. To effectively analyze the performance of these SBIs, we classified them into four types : (1) Return enhancement SBIs (six indices), (2) Volatility trading SBIs (two indices), (3) Directional trading SBIs (two indices) and (4) Other SBIs (two indices). The return enchancement SBIs include bechmark indices tracking the performance of various covered call strategies and put writing strategies, which are generally used to increase investment returns. The volatility trading SBIs include benchmark indices tracking the performance of well-known volatility trading strategies such as butterfly spread and condor. Benchmark indices tracking the performance of various types of zero-cost collar strategies are classified into the directional trading SBIs. Our empirical results are as follows. First, the risk-adjusted performances of nine SBIs of the total twelve SBIs constructed from KOSPI200 index options has been shown to be great. Second, from a portfolio perspective, some SBIs can be helpful to improve the portfolio performance of CRRA (Constant Relative Risk Aversion) investors. These results imply that passive investment strategies with KOSPI200 index options can provide additional benefits that both equities and bonds do not provide. Third, even when we use the traditional mean-variance framework other than expected utility theory to verify the economic benefit of the SBIs, our empirical results are found to be still valid. In conclusion, our results suggest that some passive investment strategies using KOSPI200 index options would be beneficial to long term investors.

This paper investigates the effects of risk neutral distribution (RND) from option prices on the distribution of the underlying asset. More specifically, we focus on the third moment of distribution, called skewness, which contains important information predicting the jumps of stock index. The sample period covers from January 2002 to July 2006 with the closing price returns of KOSPI200 Index and the KOSPI200 options. The skewness of the risk neutral distribution is estimated from non-parametric method of Bakshi et al.(2003) and the parametric method of Corrado and Su (1996). When estimating the skewness of the underlying assets, we employ Chen et al.(2001) model and calculate the historical skewness from the1-month ahead return underlying asset. Using statistical methodology such as VAR (Vector Autoregressive model), Granger causality test, impulse response and variance decomposition model, we examine whether the skewness of the underlying asset responds to the change of the implied RND. Followings are the major findings and implications drawn from the empirical analysis of the Korean options market. First of all, skewness of options estimated from non-parametric method have information contents predicting the third-moment of KOSPI200 index return whereas skewness of options estimated from parametric method does not have any information forecasting the skewness of KOSPI200 index return.

This paper tries to find the information flow between KOSPI200 Index and KOSPI200 Futures more accurately by considering two models. First, three-stage least-squares regression is used to estimate lead and lag relationships based on the representation of a simultaneous-equations model because futures and cash returns may affect each other contemporaneously. Secondly, a bivariate GARCH model is used because the lead-lag relationships between the two markets should consider not only return itself but also return volatility. The results from the first regression suggest that KOSPI200 futures returns and the index are simultaneously related and that the lead from futures to cash returns extends for about 40 minutes and the lead from cash to futures returns extends for about 30 minutes, which means the lead-lag relationship between the two markets are not unidirectional. I find from the analysis of a bivariate GARCH model that the information flow between the two markets is rather symmetrical when the volatility relationships are also considered, although it seems non-symmetrical when the returns relationships alone are considered. I also find a much stronger dependence in both directions in the volatility of returns between the cash and futures markets than that observed in the returns alone. When I consider intraday volatility as well in the lead-lag relationship between the two markets, KOSPI200 futures markets strongly lead index markets but KOSPI index do not lead futures markets. Evidence also suggests strong intermarket dependences in the conditional volatilities and in the return shocks. So the results have implications for understanding the pattern of information flows between the two markets.

This paper aims to provide the necessity to activate long-term exchange-traded derivatives (ETD) in Korea. In the era of aging, low interest rates and low economic growth, the investment demand for long-term financial products, and its hedging demand have steadily increased. Unfortunately, long-term ETD do not trade in Korea, and this study presents political suggestions to invigorate long-term ETD based on overseas cases and empirical analysis. Specifically, this study suggests the necessity to activate exchange traded funds (ETFs) options, long-term Korea treasury bond futures and options and long-term Volatility Index of Korea Composite Stock Price Index future and options. The introduction of those long-term ETD not only contributes to providing long-term investment and hedging vehicles but also reduces market inefficiencies in the Korean industry of ETFs, bonds and structured products.