C58 - Financial EconometricsReturn

Technology stocks like Facebook, Apple, Amazon, Netflix, and Google, collectively referred to as FAANG stocks, are among the most systemically important equities in global markets, attracting international investors due to the extensive use of technology in day-to-day business. However, these stocks are considered risky assets, so building an optimal portfolio requires effective risk management. To address this, this study examines the jump and co-jump behavior of the FAANG stocks over the period 2012–2026. Jumps are identified using a standardized residual approach in which daily returns that deviate from GARCH (1,1), as well as estimated conditional volatility by more than three standard deviations, are classified as jump events, based on Laurent et al.’s (2016) conceptual framework. Co-jump activity is assessed using a co-exceedance threshold rule and logistic regression, which is in line with the larger co-jump literature (Dungey and Hvozdyk, 2011; Bouri et al., 2020). Results highlight the presence of jump and co-jump activity within the FAANG stocks, where Google and Amazon exhibited the highest co-jump connectedness, revealing their vital role in spreading economic shocks across the FAANG network. In contrast, Netflix appeared to be a more peripheral asset with lower co-jump centrality. Jumps occur during macro stress periods, most notably the 2018 US-China trade war, the COVID-19 pandemic in 2020, and the 2022 rate-hike cycle, and are generally negative in direction, indicating asymmetric downside risk. Our findings are directly relevant to global investors, asset managers, and portfolio managers. Policymakers may use these outcomes to construct a stronger framework for improving financial stability and mitigating systemic risk during market stress periods.

This study investigates whether the canonical asymmetric volatility documented in developed markets can be generalized to an emerging market setting, using the Casablanca Stock Exchange (MASI index, 2011–2023) as a case study. Applying symmetric and asymmetric GARCH models with a three period subsample robustness check (pre-COVID, COVID, post-COVID),  we uncover a pattern of attenuated asymmetry. During normal conditions and the COVID-19 crisis, the market exhibits significant volatility persistence coupled with symmetric responses to shocks, challenging the near-universal evidence of leverage effects. However, the post-COVID geopolitical crisis temporarily activates powerful asymmetry, revealing that volatility dynamics are state-dependent and crisis-type specific. The symmetric GARCH model outperforms asymmetric specifications in forecasting accuracy across most periods, demonstrating that additional complexity is unwarranted during normal conditions. These findings show that microstructure characteristics fundamentally shape volatility dynamics, and that the leverage effect cannot be universally assumed across all emerging markets.

The paper investigates the relationship between short selling activities of stocks on the volatility of the US market and its sectors. We apply the multivariate DCC GARCH Model on the NYSE US 100 Index between November 2017 and October 2018. We find evidence that investments in some specific firms on the market reduce the market volatility and higher short selling activities reduce risk in the market. The study also finds that firms in the financial sector dominate the market and short selling activities in this sector has a greater impact on the market volatility. We also find portfolio managers to be better off investing in the market than creating portfolio within sectors.