A study of the implied volatility function : evidence from Hang Seng Index options market in Hong Kong

This study explores the information content of the implied volatility inferred from stock index options in the over-the-counter (OTC) market, which has rarely been studied in the literature. Using OTC calls, puts, and straddles on the KOSPI 200 index, we find that implied volatility generally outperforms historical volatility in predicting future realized volatility, although it is not an unbiased estimator. The results are more apparent for options with shorter maturity. However, while implied volatility has strong predictability during normal periods, historical volatility is superior to implied volatility during a period of crisis due to the liquidity contraction of the OTC options market. This finding suggests that the OTC options market can play a role in conveying important information to predict future volatility.

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Information Content of Adjusted Implied Volatility in the KOSPI 200 Index Options Market

Journal of Derivatives and Quantitative Studies ◽

10.1108/jdqs-04-2009-b0003 ◽

2009 ◽

Vol 17 (4) ◽

pp. 75-103

Author(s):

Byung Jin Kang ◽

Sohyun Kang ◽

Sun-Joong Yoon

Keyword(s):

Implied Volatility ◽

Risk Premia ◽

Risk Averse ◽

Options Market ◽

Jump Risk ◽

Index Options ◽

Volatility Risk ◽

Model Free ◽

Volatility Model ◽

Forecasting Errors

This study examines the forecasting ability of the adjusted implied volatility (AIV), which is suggested by Kang, Kim and Yoon (2009), using the horserace competition with historical volatility, model-free implied volatility, and BS implied volatility in the KOSPI 200 index options market. The adjusted implied volatility is applicable when investors are not risk averse or when underlying returns do not follow a normal distribution. This implies that AIV is consistent with the presence of risk premia for other risk such as volatility risk and jump risk. Using KOSPI 200 index options, it is shown that the AIV outperforms other volatility estimates in terms of the unbiasedness for future realized volatilities as well as the forecasting errors.

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Patterns of 50 ETF Options Implied Volatility in China: On Implied Volatility Functions

E+M Ekonomie a Management ◽

10.15240/tul/001/2021-1-009 ◽

2021 ◽

Vol 24 (1) ◽

pp. 135-145

Author(s):

Pengshi Li ◽

Yan Lin ◽

Yuting Zhong

Keyword(s):

Implied Volatility ◽

Stock Exchange ◽

Empirical Work ◽

Ordinary Least Squares ◽

Options Pricing ◽

Options Market ◽

European Options ◽

Volatility Smile ◽

Volatility Function ◽

Better Than

The aim of this study is to examine the volatility smile based on the European options on Shanghai stock exchange 50 ETF. The data gives evidence of the existence of a well-known U-shaped implied volatility smile for the SSE 50 ETF options market in China. For those near-month options, the implied volatility smirk is also observed. And the implied volatility remains high for the short maturity and decreases as the maturity increases. The patterns of the implied volatility of SSE 50 ETF options indicate that in-the-money options and out-of-the-money options are more expensive relative to at-the-money options. This makes the use of at-the-money implied volatility for pricing out-of- or in-the-money options questionable. In order to investigate the implied volatility, the regression-based implied volatility functions model is considered employed to study the implied volatility in this study as this method is simple and easy to apply in practice. Several classical implied volatility functions are investigated in this paper to find whether some kind of implied volatility functions could lead to more accurate options pricing values. The potential determinants of implied volatility are the degree of moneyness and days left to expiration. The empirical work has been expressed by means of simple ordinary least squares framework. As the study shows, when valuing options, the results of using volatility functions are mixed. For far-month options, using at-the-money implied volatility performs better than other volatility functions in option valuation. For near-month options, the use of volatility functions can improve the valuation accuracy for deep in-the-money options or deep out-of-the-money options. However, no particular implied volatility function performs very well for options of all moneyness level and time to maturity.

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