Publication: Modeling and Forecasting Intraday Volatility of Crude Oil Futures
datacite.rights | restricted | |
dc.contributor.advisor | Cerenzia, Mark | |
dc.contributor.author | He, Shuchen | |
dc.date.accessioned | 2025-08-06T14:45:19Z | |
dc.date.available | 2025-08-06T14:45:19Z | |
dc.date.issued | 2025-04-10 | |
dc.description.abstract | This paper examines the intraday 5-minute volatility dynamics of crude oil futures using Market-by-Order (MBO) data from the front-month contract. Within the context of crude oil futures, we report the following key findings: (1) Realized Volatility (RV) serves as a reliable proxy for latent volatility; (2) 5-minute RV displays pronounced intraday seasonality and long-memory characteristics; (3) Deseasonalized 5-minute RV is still long-memory but simultaneously highly stationary, a surprising observation. (4) Fractional differencing tends to eliminate both high- and low-frequency components of the 5-minute deseasonalized RV, making the commonly used AutoRegressive Fractionally Integrated Moving Average (ARFIMA) model less effective. This has profound implications on how we understand volatility. (5) Eventually, we adopt a simpler AutoRegressive Integrated Moving Average (ARIMA) approach and present the results. | |
dc.identifier.uri | https://theses-dissertations.princeton.edu/handle/88435/dsp01bn999b202 | |
dc.language.iso | en_US | |
dc.title | Modeling and Forecasting Intraday Volatility of Crude Oil Futures | |
dc.type | Princeton University Senior Theses | |
dspace.entity.type | Publication | |
dspace.workflow.startDateTime | 2025-04-10T19:55:26.397Z | |
pu.contributor.authorid | 920282742 | |
pu.date.classyear | 2025 | |
pu.department | Ops Research & Financial Engr |
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