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This study looks at the characteristics and current status of retail structured product market of Korea and tries to explain, in particular, issues related to issue price, cost of hedging, and overpricing. We also analyzed the perspective of the government and the related regulatory policies. We examined various performance measures for portfolios composed of the KOSPI200 Covered Call Index and other assets in order to change the viewpoint of the authorities that the trading of structured products, such as ELS (equity-linked securities) and DLS (debt-linked securities), is in fact not a zero-sum game between the issuers and investors. The empirical results show that the KOSPI200 Covered Call Index has a superior performance compared to the KOSPI200 Index and the others. In addition, from the perspective of certainty equivalent excess returns, the KOSPI200 Covered Call Index also displays the possibility of improving the utility level of risk-averse retail investors. However, it is difficult in reality for individual investors to construct efficient portfolios that employ covered call strategies using options. Hence, individual investors can form optimal portfolios that benefit indirectly from such covered call strategies via investment in financial derivative products issued by securities firms that are able to more easily utilize investment strategies that incorporate options to form optimum portfolios. This means that both the issuer and investor can profit from these financial derivative products and, therefore, it is not a zero-sum game.

The purpose of this study is to investigate hedging effectiveness of KOSPI200 index futures and options using three measures proposed by Fishburn (1977), Ederington (1979), and Howard and D’Antonio (1987). The comparison of hedging effectiveness is conducted based on the market prices of KOSPI200 index futures and options traded in Korea Exchange (KRX) between January of 2001 and January of 2011, during which bootstrapping method is utilized to make a dataset of 100,000 random samples with holding period of 1, 3, 6, and 12 months, respectively. We examine the hedging performance of hedge portfolios made of short futures, protective puts and covered calls respectively based on three hedging effectiveness measures.

One of our finding is that short futures hedging is better than options in minimizing total volatility risk as well as down-side risk, which is consistent to the previous researches. Also futures hedging is more effective in reducing the VaR than the others. Secondly, the optimal hedge ratios of futures in minimizing total risk and down-side risk are turned out to be 0.97~0.98 and 0.94~0.95 respectively. Third, OTM short call hedge is the best hedging instrument when hedgers would like to maximize the Sharpe ratio. Finally, protective put hedging strategy is in general inferior to the short futures and covered call hedge based on three hedging effectiveness measures.

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.

The purpose of this paper is to examine the argument that the put options traded in the exchanges are too high, compared to the asset prices based on the classical CAPM model, and thus the short position of the put option would make a significant profit from trading. In order to explore the earlier report, this paper, using the KOSPI 200 index options market price, estimates the historical rate of return on several option trading strategies such as naked option, protective put, covered call, straddle, and strangle. Secondly this paper compares the historical rates of return on the option trading strategies and Sharpe ratios with those generated by Monte-Carlo simulation and examines whether the historical option returns are inconsistent with Black-Scholes model, Jump-diffusion model, Stochastic Volatility model, or Stochastic Volatility with Jump model. Thirdly, this paper computes the optimal asset allocation ratio among the risk-free asset, risky assets, and option trading strategies in the viewpoint of rational investors who maximize the CRRA utility function.

The results show that the historical returns on short position of ATM and OTM puts are too high to explain based on the classical CAPM, and the optimal allocation ratios among put, risky asset, and the risk-free asset are different from those derived using Monte-Carlo simulation.

The purpose of this paper is to illustrate a profitable and original index options trading strategy.

The methodology is based on auto regressive integrated moving average (ARIMA) forecasting of the S&P 500 index and the strategy is tested on a large database of S&P 500 Composite index options and benchmarked to the generalized auto regressive conditional heteroscedastic (GARCH) model. The forecasts validate a set of criteria as follows: the first criterion checks if the forecasted index is greater or lower than the option strike price and the second criterion if the option premium is underpriced or overpriced. A buy or sell and hold strategy is finally implemented.

The paper demonstrates the valuable contribution of this option trading strategy when trading call and put index options. It especially demonstrates that the ARIMA forecasting method is a valid method for forecasting the S&P 500 Composite index and is superior to the GARCH model in the context of an application to index options trading.

The strategy was applied in the aftermath of the 2008 credit crisis over 60 months when the volatility index (VIX) was experiencing a downtrend. The strategy was successful with puts and calls traded on the USA market. The strategy may have a different outcome in a different economic and regional context.