Financial Market Volatility and Jumps

by Huang, Xin

Abstract (Summary)
This dissertation consists of three related chapters that study financial market volatility,

jumps and the economic factors behind them. Each of the chapters analyzes a

different aspect of this problem.

The first chapter examines tests for jumps based on recent asymptotic results.

Monte Carlo evidence suggests that the daily ratio z-statistic has appropriate size,

good power, and good jump detection capabilities revealed by the confusion matrix

comprised of jump classification probabilities. Theoretical and Monte Carlo analysis

indicate that microstructure noise biases the tests against detecting jumps, and that

a simple lagging strategy corrects the bias. Empirical work documents evidence for

jumps that account for seven percent of stock market price variance.

Building on realized variance and bi-power variation measures constructed from

high-frequency financial prices, the second chapter proposes a simple reduced form

framework for modelling and forecasting daily return volatility. The chapter first

decomposes the total daily return variance into three components, and proposes

different models for the different variance components: an approximate long-memory

HAR-GARCH model for the daytime continuous variance, an ACH model for the

jump occurrence hazard rate, a log-linear structure for the conditional jump size,

and an augmented GARCH model for the overnight variance. Then the chapter

combines the different models to generate an overall forecasting framework, which

improves the volatility forecasts for the daily, weekly and monthly horizons.

The third chapter studies the economic factors that generate financial market

volatility and jumps. It extends the recent literature by separating market responses

into continuous variance and discontinuous jumps, and differentiating the market’s

disagreement and uncertainty. The chapter finds that there are more large jumps on

news days than on no-news days, with the fixed-income market being more responsive

than the equity market, and non-farm payroll employment being the most influential

news. Surprises in forecasts impact volatility and jumps in the fixed-income market

more than the equity market, while disagreement and uncertainty influence both

markets with different effects on volatility and jumps.

JEL classification: C1, C2, C5, C51, C52, F3, F4, G1, G14

Bibliographical Information:

Advisor:Bollerslev, Tim; Tauchen, George; Gallant, A. Ronald; Eraker, Bjorn

School:Duke University

School Location:USA - North Carolina

Source Type:Master's Thesis

Keywords:stochastic volatility jump realized variance bipower variation macroeconomic news announcements economic derivatives


Date of Publication:05/07/2007

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