Measuring equity volatility is an important metric and understanding, describing, and predicting volatility using trading activity provides insight into navigating the stock market. Taking inspiration from existing research analyzing volatility in the stock market, we explore the dynamic relationship between trading volume, trading frequency, and volatility on an intraday basis across ten stocks in the consumer discretionary sector of the S&P 100 for the fourth quarter of 2013. Using three different volatility measures we implement variations of the heterogeneous autoregressive model and vector autoregressive model to investigate the lead-and-lag relationship between volatility and trading activity. Our quantitative analysis provides strong empirical evidence that current trading frequency and trading volume can be used to predict 30-minute measures of volatility and that the prior day rolling average and lagged trading measures are useful predictors in modeling the volatility measures.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Candy, Ryan E.
• Coughlin, Isadora C.
• Baker, Emily N.

Publisher

• Worcester Polytechnic Institute

Identifier

• 16821
• E-project-040121-110157

Keyword

• Heterogeneous Autoregressive model
• High-frequency Data
• Intraday Volatility
• Trading Volume
• Trading Frequency

Advisor

• Wang, Fangfang
• Zou, Jian

Year

• 2021

UN Sustainable Development Goals

• 8 - Decent Work and Economic Growth

Date created

• 2021-04-01

Resource type

• Major Qualifying Project

Major

• Mathematical Sciences

Rights statement

• In Copyright

Last modified

• 2021-05-03