Overnight volatility, realized volatility, and option pricing

Abstract

The equity market is not trading around the clock, and the overnight information has been proved be important for understanding pricing anomalies, improving volatility forecasting accuracy, and so forth. However, there is little research investigating its impact on option pricing. In this paper, we provide a framework that integrates intraday, overnight returns, and realized volatility simultaneously within an augmented Autoregressive Volatility model. The analytical option-pricing formula for the new model is derived through the closed-form moment generation function. The empirical results based on S&P 500 index options show that distinguishing the overnight component from daily returns has the potential capability to reduce the pricing errors, both in-sample and out-of-sample.

Option pricing with overnight and intraday volatility

“…Muravyev and Ni (2020) find a remarkable day-night pattern: overnight average delta-hedged option returns are negative, whereas intraday average delta-hedged option returns are slightly positive. Wang et al (2022) integrate overnight returns, intraday returns, and intraday realized volatility within an augmented autoregressive volatility model, in which overnight returns and intraday returns are assumed to be independent.…”

Trading around the clock: Revisit volatility spillover between crude oil and equity markets in different trading sessions

“…Therefore, it is normally assumed that overnight information could be reflected rapidly in asset prices when the new trading day starts (Ahoniemi et al, 2015), and the overnight return is calculated based on the difference between the closing price on the previous day and the opening price on the following day. While overnight information is important to study asset price volatility (Tsiakas, 2008; Wang et al, 2022), it is proved that the traditional method of using only one squared overnight return is not sufficient to capture overnight price dynamics (Lee et al, 2022; Lyócsa & Todorova, 2020). Therefore, a new proxy is required to study the overnight information flow in the financial market.…”

“…Second, we provide new empirical evidence of the importance of overnight trading information. We extend the previous research of overnight information study of asset price volatility (Lee et al, 2022;Lyócsa & Todorova, 2020;Tsiakas, 2008;Wang et al, 2022) by considering the trading time difference in different countries. In the current globalization and digital trading era, there is not any real overnight exist, as investors from some counties are trading while investors from other counties are sleeping due to the time lag.…”

“…closing price on the previous day and the opening price on the following day. While overnight information is important to study asset price volatility (Tsiakas, 2008;Wang et al, 2022), it is proved that the traditional method of using only one squared overnight return is not sufficient to capture overnight price dynamics (Lee et al, 2022;Lyócsa & Todorova, 2020). Therefore, a new proxy is required to study the overnight information flow in the financial market.…”

“…Sévi (2014) prove that overnight volatility could improve the forecast accuracy of intraday volatility. Tsiakas (2008), Ahoniemi and Lanne (2013), and T. Wang et al (2022) propose models to forecast equity market intraday returns and volatility with overnight information.…”