Forecasting Volatility Persistence: Evidence from International Stock Markets

Dublin Core

Title

Forecasting Volatility Persistence: Evidence from International Stock Markets

Subject

Volatility Persistence; Stock Markets; ARCH model; GARCH model; Market efficiency

Description

Volatility persistence represents a notable feature of financial markets and is a widely studied phenomenon that explores the clustering and leverage effects of stock market returns. Recognizing and incorporating volatility persistence into risk management, asset pricing, and portfolio management strategies provide valuable insights for market participants enabling them to navigate and capitalize on the dynamics of market volatility. The aim of this study was to empirically investigate whether the current high volatility in stock markets are temporal or will persist in the future. An ARCH model and a GARCH model were employed to achieve the aim of this study for the JSE, CAC 40, DAX, Nasdaq and Nikkei 225 from May 29, 2023 to May 29, 2018. The findings revealed that stock market volatility will persist at least for some time from the ARCH and GARCH output results. Active traders and market makers need to adapt theirstrategies in response to the expected volatility persistence. Higher levels of persistence may call for adjustments such as widening stop-loss orders to accommodate larger price swings or using more extended timeframes to capture sustained trends. Portfolio managers may also opt for strategies that thrive in volatile market conditions such as breakout trading or mean reversion strategies

Creator

Samuel Tabot Enow

Source

https://dinastipub.org/DIJEFA/article/view/1891/1327

Publisher

IIE Varsity College

Date

11 July 2023

Contributor

Samuel Tabot Enow

Format

PDF

Language

English

Type

Text

Files

Collection

Citation

Samuel Tabot Enow, “Forecasting Volatility Persistence: Evidence from International Stock Markets,” Repository Horizon University Indonesia, accessed March 13, 2025, https://repository.horizon.ac.id/items/show/5830.