The Information Content of Intraday Implied Volatility for Volatility Forecasting

Abstract

This study examines the intraday S&P 500 implied volatility index (VIX) to determine when the index contains the most information for volatility forecasting. The findings indicate that, in general, VIX levels around noon are most informative for predicting realized volatility. We posit that the VIX performs better during this time period because trading motivation around noon is less complex, and therefore trades contain more information on the market expectation of future volatility. Further investigation on the 2008 financial crisis period suggests that market participants become more cautious, and thus the forecasting performance is sustained until the market's close. Copyright © 2015 John Wiley & Sons, Ltd.

An Open Innovation Intraday Implied Volatility for Pricing Australian Dollar Options

“…These tick-by-tick data, termed as ultra-high-frequency data by Engle [42], are usually referred to as highfrequency data in current studies. High-frequency data indicated that many financial assets experienced the particular intraday patterns [20] and these patterns were significantly associated with intraday returns variations, volatility, volume, and bid-ask spreads [43]. A large number of studies suggested that intraday trading activities exhibited a U-shaped pattern with the trading volumes being extremely high at the market's opening and closing periods, such as Wood et al [44], Gerety and Mulherin [45], Brock and Kleidon [46] for the New York Stock Exchange (NYSE); Mclnish and Wood [47] for the Toronto Stock Exchange; and Hamao and Hasbrouck [48] for the Tokyo stock exchange.…”

“…As the options prices reflect the market's expectation about the future movements of the prices of the underlying asset over the remaining life of the option contract, more research concentrates on volatility implied in options prices [20]. The implied volatility (IV) contains all available information, including historical data [10,[20][21][22][23][24][25]. It is widely accepted that the IV from the market options price is a reasonable measure of the market's opinion of the volatility of the underlying asset.…”

Intraday Patterns in the Trading Volume of the SPY ETF

“…The U-shaped pattern of intraday trading volume has been documented across financial instruments, trading venues and time periods. In the U.S. equity markets, Blau (2009) finds U-shaped volumes in NYSE traded stocks, Wang and Wang (2016) find it in the SPDR ETF. Abhyankar (1997) finds U-shaped volumes in the London Stock Exchange, Lee (2001) finds it in the Taiwanese Stock Exchange and Hussain (2011) finds it in the DAX 30.…”

A separate reduced‐form volatility forecasting model for nonferrous metal market: Evidence from copper and aluminum

“…Early studies on volatility modeling and forecasting in the metal market primarily focused on generalized autoregressive conditional heteroskedasticity (GARCH)type models (Behmiri & Manera, 2015;Bentes, 2015;Hammoudeh, Malik, & McAleer, 2011;Hammoudeh & Yuan, 2008;Kristjanpoller & Hernández, 2017;Kristjanpoller & Minutolo, 2015;McKenzie, Mitchell, Brooks, & Faff, 2001). More recent literature suggests that high-frequency data can significantly improve the prediction accuracy of future volatility (Gong, He, Li, & Zhu, 2014;Wang & Wang, 2016;Wen, Gong, & Cai, 2016). Moreover, the decomposition between continuous and discontinuous jump components can contribute to acquiring more accurate forecasts.…”