Volatility estimation in agricultural futures markets: a microstructure approach

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dc.contributor.authorKong, Xianglin
dc.contributor.examiningcommitteeGoswami, Alankrita (Agribusiness & Agricultural Economics)
dc.contributor.examiningcommitteeArzandeh, Mehdi (Lakehead University)
dc.contributor.supervisorFrank, Julieta
dc.date.accessioned2025-01-15T21:02:13Z
dc.date.available2025-01-15T21:02:13Z
dc.date.issued2025-01-03
dc.date.submitted2025-01-09T22:12:02Zen_US
dc.degree.disciplineAgribusiness and Agricultural Economics
dc.degree.levelMaster of Science (M.Sc.)
dc.description.abstractAgricultural markets are known to be more volatile than the other markets. Understanding volatility movements is important to improve both risk management strategies and market forecasts. In an order-driven electronic trading system, the Limit Order Book (LOB) contains trading information based on market participants expectations. Such information may help explain volatility and utilised to make forecasts. In agricultural market, most previous studies have used daily information to predict volatility. This research uses intraday data to forecast volatility in both lean hog and corn markets. Two models are considered, the well-known GARCH (1,1) and the GARCH-X model which includes LOB information. Intraday forecasts coming from GARCH and GARCH-X are compared with intraday realized volatility (RV). Our findings suggest that GARCH and GARCH-X model forecasts are more in line with each other than with RV, and that GARCH-X forecasts do not outperform GARCH (1,1) forecasts. Reasons associated with these findings, limitations of this study, and future work are outlined.
dc.description.noteFebruary 2025
dc.identifier.urihttp://hdl.handle.net/1993/38825
dc.language.isoeng
dc.subjectRealized volatility
dc.subjectGARCH model
dc.subjectMarket microstructure
dc.subjectLimit order book
dc.subjectVolatility
dc.subjectHigh frequency data
dc.titleVolatility estimation in agricultural futures markets: a microstructure approach
local.subject.manitobano
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