Work detail

Influence of stock market variables on correlations among S&P sectors

Author: Mgr. Matěj Coufal
Year: 2022 - summer
Leaders: PhDr. František Čech Ph.D.
Consultants:
Work type: Finance, Financial Markets and Banking
Masters
Language: English
Pages: 100
Awards and prizes:
Link: https://dspace.cuni.cz/handle/20.500.11956/174002
Abstract: This thesis investigates the influence of the exogenous variables (S&P 500 Index,
10-year US Treasury Note, crude oil, and CBOE Volatility Index (VIX)) on the
dynamics of correlations among S&P sectors. We concentrate on daily and weekly
investment horizons, and employ the bivariate Dynamic Conditional Correlation
(DCC) model. Changes in correlations implied by the DCC model are further
modelled using the exogenous variables. The results indicate that VIX has the
best ability to predict future changes in correlations. An increase in VIX on day
(week) t is expected to cause a rise in correlations on day (week) t + 1. Next,
correlations of the Energy sector tend to increase in weeks when crude oil prices
are falling. Further, correlations of the Information Technology sector are likely
to increase on days of rising yield on the 10-year US Treasury Note. Although we
detect a certain power to predict future changes in correlations, very little of these
changes is actually explained.
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