Signals in the Storm: Predicting Market Shifts with VIX, CVI, MOVE, and BBDXY Indices

dc.contributor.authorEeso, Meron
dc.date.accessioned2025-10-20T14:40:17Z
dc.date.available2025-10-20T14:40:17Z
dc.date.issued2025-04-03
dc.descriptionThis study examines the ability of volatility indices to predict asset returns across equity, bond, cryptocurrency, and currency markets. Using daily data for the VIX, CVI, MOVE, and BBDXY indices, the analysis finds that each index offers meaningful return predictability both within and across markets. Notably, VIX Change Lagged forecasts equity returns, while CVI and MOVE demonstrate significance in multiple markets, and BBDXY Change Lagged provides strong cross-asset signals. The predictive power increases when the indices are combined, with adjusted R² values of 5.16% for SPY and 2.71% for AGG. These results highlight the value of volatility indices as forward-looking market indicators.
dc.description.abstractThis study examines the ability of volatility indices to predict asset returns across equity, bond, cryptocurrency, and currency markets. Using daily data for the VIX, CVI, MOVE, and BBDXY indices, the analysis finds that each index offers meaningful return predictability both within and across markets. Notably, VIX Change Lagged forecasts equity returns, while CVI and MOVE demonstrate significance in multiple markets, and BBDXY Change Lagged provides strong cross-asset signals. The predictive power increases when the indices are combined, with adjusted R² values of 5.16% for SPY and 2.71% for AGG. These results highlight the value of volatility indices as forward-looking market indicators.
dc.description.sponsorshipThe Honors College, Oakland University
dc.identifier.citationEeso, M. (2025). Signals in the Storm: Predicting Market Shifts with VIX, CVI, MOVE, and BBDXY Indices (Undergraduate honors thesis, Oakland University).
dc.identifier.urihttps://hdl.handle.net/10323/18846
dc.language.isoen_US
dc.publisherOakland University
dc.rightsAttribution 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/
dc.subjectVolatility Indices
dc.subjectMarket Prediction
dc.subjectAsset Returns
dc.subjectVIX
dc.subjectCVI
dc.subjectMOVE
dc.subjectBBDXY
dc.subjectEquity Markets
dc.subjectBond Markets
dc.subjectCryptocurrency
dc.subjectRegression Analysis
dc.subjectTime-Series Analysis
dc.subjectFinancial Econometrics
dc.titleSignals in the Storm: Predicting Market Shifts with VIX, CVI, MOVE, and BBDXY Indices
dc.typeThesiseng

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
2025 Thesis, Eeso, Meron.pdf
Size:
495.81 KB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.19 KB
Format:
Item-specific license agreed upon to submission
Description: