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Are the KOSPI 200 implied volatilities useful in value-at-risk models?

Kim, Jun Sik; Ryu, Doojin - In: Emerging markets review 22 (2015), pp. 43-64

Persistent link: https://www.econbiz.de/10011304192

Return and volatility spillovers and cojump behavior between the U.S. and Korean stock markets

Kim, Jun Sik; Ryu, Doojin - In: Emerging markets finance & trade : a journal of the … 51 (2015), pp. 3-17

Persistent link: https://www.econbiz.de/10011603316

The information content of option-implied information for volatility forecasting with investor sentiment

Seo, Sung Won; Kim, Jun Sik - In: Journal of banking & finance 50 (2015), pp. 106-120

Persistent link: https://www.econbiz.de/10010509134

The information content of risk-neutral skewness for volatility forecasting

Byun, Suk Joon; Kim, Jun Sik - In: Journal of empirical finance 23 (2013), pp. 142-161

Persistent link: https://www.econbiz.de/10010221765

Implied volatility index of KOSPI200 : information contents and properties

Ryu, Doojin - In: Emerging markets finance & trade : a journal of the … 48 (2012), pp. 24-39

Persistent link: https://www.econbiz.de/10009682531

Implied pricing Kernels : an alternative approach for option valuation

Ryu, Doojin; Kang, Jangkoo; Suh, Sangwon - In: The journal of futures markets 35 (2015) 2, pp. 127-147

Persistent link: https://www.econbiz.de/10011348461

An investigation of return-volatility relationship using high-frequency VKOSPI data

Bagchi, Debasis; Lee, Changjun; Ryu, Doojin - In: Afro-Asian Journal of Finance and Accounting : AAJFA 3 (2012/13) 3, pp. 256-273

Persistent link: https://www.econbiz.de/10010210130

Economic indicators and stock market volatility in an emerging economy

Chun, Dohyun; Cho, Hoon; Ryu, Doojin - In: Economic systems 44 (2020) 2, pp. 1-18

Persistent link: https://www.econbiz.de/10012593418

Forecasting Stock Market Volatility and Application to Volatility Timing Portfolios

Ryu, Doojin - 2022

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...

Persistent link: https://www.econbiz.de/10014238092

Forecasting Stock Market Volatility and Application to Volatility Timing Portfolios

Chun, Dohyun; Cho, Hoon; Ryu, Doojin - 2022

Persistent link: https://www.econbiz.de/10013404229