Which trader's order-splitting strategy is effective? The case of an index options market

Kim, Hyeyoen; Ryu, Doojin

doi:10.1080/13504851.2012.665590

Cited by 38 publications

(20 citation statements)

References 15 publications

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“…Among market practitioners, it is widely believed that, in the KOSPI200 options market, domestic individual investors tend to regularly and overly buy options and overreact in response to positive news of the underlying market (Kim and Ryu, 2012). Further, the existence of special options accounts makes buying KOSPI200 options easier to implement than writing them.…”

Section: Empirical Results and Discussionmentioning

confidence: 99%

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Stock Returns and Implied Volatility: A New VAR Approach

Lee

Ryu

2013

Economics

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The authors re-examine the return-volatility relationship and its dynamics under a new vector autoregression (VAR) identification framework. By analyzing two model-free impliedvolatility indices -the well-established VIX (in the United States) and the recently published VKOSPI (in Korea) -and their stock market indices, the authors find an asymmetric volatility phenomenon in both the developed and emerging markets. However, the VKOSPI shows impulse response dynamics that are quite different from those of the VIX. This finding can be attributed to the unique characteristics of the KOSPI200 options market, which determine the dynamics of the VKOSPI. JEL G10 G15

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Section: Empirical Results and Discussionmentioning

confidence: 99%

“…3 See the recent studies of Giot (2005aGiot ( , 2005b, Banerjee, Doran, and Peterson (2007), Becker, Clements, andMcCelland (2009), andDuan andYeh (2010). 4 Some recent studies, such as Ryu (2008, 2010), Ryu (2011), and Kim and Ryu (2012), have begun to address the market microstructure issues of the KOSPI200 options market.…”

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Stock Returns and Implied Volatility: A New VAR Approach

Lee

Ryu

2013

Economics

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“…The active participation of individual investors implies that the dynamics of option prices and _________________________ 2 The microstructure of the KOSPI 200 options market is well documented in Ahn et al (2008Ahn et al ( , 2010, Chae andLee (2011), Eom andHahn (2005), Kim and Ryu (2012), and Ryu (2011Ryu ( , 2015. the derived implied volatility are more likely to be affected by market sentiment and behavioral factors, underscoring the importance of the VKOSPI as a fear gauge measure.…”

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Effects of the US Stock Market Return and Volatility on the VKOSPI

2015

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The KOSPI (Korea Composite Stock Price Index) 200 options are one of the most actively traded derivatives in the world. This paper empirically examines (a) the statistical properties of the Korea's representative implied volatility index (VKOSPI) derived from the KOSPI 200 options and (b) the macroeconomic and financial variables that can predict the implied volatility process of the index, using augmented heterogeneous autoregressive (HAR) models with exogenous covariates. The results suggest that the elaborate HAR framework is proficient at describing the dynamics of the VKOSPI and that some domestic macroeconomic variables explain the VKOSPI. More importantly, we find that the stock market return and implied volatility index of the US market (i.e., the S&P 500 spot return and the VIX from the S&P 500 options) play a key role in predicting the level of the VKOSPI and explaining its dynamics, and their explanatory power dominates that of domestic macro-finance variables. Further, while the domestic stock market return does not predict the VKOSPI, the US stock market return does so rather well. When two global factors, both the US stock market return and the US implied volatility index, are incorporated into the HAR framework, the model exhibits the best performance in terms of both in-sample fitting and out-of-sample forecasting ability. JEL C22 C50 G14 G15

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“…2 For details on the VKOSPI and the KOSPI200 options market, refer to Kim and Ryu (2012) and Ryu (2012Ryu ( , 2015. 3 W it also includes absolute deseasonalized values for the variables or extreme weather condition dummies.…”

Section: Empirical Findingsmentioning

confidence: 99%

Weather and stock market volatility: the case of a leading emerging market

Shim

Kim

et al. 2015

Applied Economics Letters

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This study examines how weather affects the stock market volatilities of a leading emerging market. By analysing both historical and model-free implied volatilities, we find that the historical volatility better captures the weather effect than the implied volatility. We also find that volatilities tend to increase in cloudy, wet and windless weather, and that investors asymmetrically react to extremely high weather conditions in comparison with extremely low weather conditions.

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Which trader's order-splitting strategy is effective? The case of an index options market

Cited by 38 publications

References 15 publications

Stock Returns and Implied Volatility: A New VAR Approach

Stock Returns and Implied Volatility: A New VAR Approach

Effects of the US Stock Market Return and Volatility on the VKOSPI

Weather and stock market volatility: the case of a leading emerging market

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