Realized Volatility, the Good and the Bad

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Realized volatility (RV) refers to the actual movement of an asset’s price over a specific period, typically measured using high-frequency data. Unlike implied volatility, which is derived from options prices and reflects market expectations, realized volatility is computed from historical price data and provides an empirical measure of how much an asset’s price has fluctuated in the past.

Reference [1] further divides realized volatility into good and bad RV. It defines good and bad RV as the squared sum of positive and negative intraday returns within a day, respectively. The authors then study the impact of the volatility risk premium on realized volatility, as well as on good and bad RV, under different market conditions. They pointed out,

Overall. whether it’s a call option or a put option, the prediction model containing the implied information of options can predict the daily realized volatility significantly better than the weekly and monthly forecast horizons. If we further classify options according to moneyness, we can conclude that the implied information content of deep out-of-the-money options has the highest prediction accuracy for weekly good realized volatility. Thus, it is very meaningful for this paper to divide the realized volatility into good and bad volatilities and study the differential performance of volatility risk premium between them, which can provide a new perspective for investors to the changes of future stock market volatility. Especially,  investors need to grasp the good and bad volatilities relationship of the underlying securities, be alert to the impact of the implied information changes in options market on the stock market, and grasp the stock market sentiment from a global perspective and sector perspective so as to improve investment.

In brief, the paper shows that the volatility risk premium has a significant influence on both good and bad volatilities. In particular, the impact of the volatility risk premium on good volatility is significantly stronger than that on bad volatility. In addition, the results show that the implied information content of deep out-of-the-money options has the highest prediction accuracy for weekly good realized volatility.

We note that the study was conducted in the Chinese market. However, the framework can be easily applied to the US and any other developed market.

Let us know what you think in the comments below or in the discussion forum.

References

[1]  Z Li, J Shen, W Xiao, Volatility risk premium, good volatility and bad volatility: Evidence from SSE 50 ETF options,  The North American Journal of Economics and Finance, Volume 74, September 2024, 102206

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