Essays in high-frequency empirical finance and risk management
Abstract (Summary)
This thesis uses intradaily data on financial asset prices to test the weakform
market efficiency hypothesis as well as to analyze high-frequency relationships
between assets that trade in related financial markets. Linkages between financial
markets are aiso investigated at a lower frequency in an empirical study of investor
behavior during periods of increased aggregate risk.
First, the thesis examines the profitability of two types of technical trading
rules-moving average rules and the Relative Strength Index (RSI)
oscillator-when
applied to spot exchange rates at both the intradaily and daily frequencies over a
one-year period. No evidence of technical trading rule profitability is found using
intradaily data. These results support the weak-form market efficiency hypothesis at
the intradaily frequency. Moreover, moving average rules do not yield statistically
significant profits at the daily level. However, the profits earned from applications
of the RSI oscillator to daily foreign exchange rate data are found to be statistically
significant
.
Next, high-frequency relationships between the S&P 500 index, the S&P 500
futures, and S&P Depositary Receipts (SPDRs) are analyzed using the covariance
estimator of De Jong and Nijman (1997) as well as GMM estimation of systems
of simultaneous equations. The futures contract is shown to play a price discovery
role for other instruments involving the S&P 500, while the index has such a role
for investors in SPDRs. The finding that the tutures contract is the main source
of market-wide information corroborates the evidence in the literature, although the
estimated lead of the futures over the index is smaller than previously noted.
Finally, the hypothesis that an increase in risk causes investors to substitute
away from risky assets such as equities and into less risky assets such as bonds in
a 'Bight-to-quality' is empirically tested. A bivariate autoregressive conditional heteroskedasticity
(ARCH) Markov-switching mode1 is developed for monthly U.S.stock
and long-term government bond returns in order to examine the relationship between
equity volatility and bond returns. Two stock volatility/excess bond retum regimes
are identified in the data and monthly excess bond returns are found to be approximately
2% higher in the high equity volatility regirne than in the low volatility state.
These findings have important asset allocation and risk management ramifications.
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Source Type:Master's Thesis
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Date of Publication:01/01/2000