Research | Jian Hu @ SMU Department of Economics

Publication

Dissertation Chapter 1: “Dependence Structures in Chinese and U.S. Financial Markets: A Time-varying Conditional Copula Approach” (Applied Financial Economics, forthcoming)
In this paper, we use a time-varying conditional copula approach to model Chinese and U.S. stock markets’ dependence structures with other financial markets. The AR-GARCH-t model is used to examine the marginal distributions, while Normal and Generalized Joe-Clayton copula models are employed to analyze the joint distributions. In this pairwise analysis, both constant and time-varying conditional dependence parameters are estimated by a two-step maximum likelihood method. A comparative analysis of dependence structures in Chinese versus U.S. stock markets is also provided. There are three main findings: First, the time-varying-dependence model does not always perform better than constant-dependence model. This result has not previously been reported in the literature. Second, we find that the upper tail dependence is much higher than the lower tail dependence in some short periods, which has not been documented in previous literature. Last, Chinese financial market is relatively separate from other international financial markets in contrast to the U.S. market. The tail dependence with other financial markets is much lower in China than in the United States. Dependence, on average, rises significantly over sub-periods.

Working Papers

Dissertation Chapter 2: “Return Dependence and the Limits of Product Diversification in Financial Firms”, with Thomas Fomby and Jeffery Gunther
We use copula-GARCH models to investigate dependence between the returns to banking and three other financial businesses: insurance underwriting, securities brokerage, and mortgage finance. Typically, negative shocks are less likely to occur to both banking and one of these other financial businesses than to both banking and the market overall. However, in a financial crisis, when risk-reducing diversification is most important, negative tail dependence between banking and other financial businesses increases dramatically. These findings casts doubt on any risk-reducing benefits associated with conglomerates combining banking and other financial businesses.

Dissertation Chapter 3: “Does Weather Matter?"
In response to a recent debate about the weather effect on stock market returns, we use various regressions and copula techniques to reexamine the relationship between temperature and stock market returns and find that the negative correlation is statistically significant in most countries. We disentangle pure temperature effect and seasonality by including month dummies and find negative temperature effects on returns do not change very much. Furthermore, to overcome some drawbacks of the naive regression analysis, copula models are employed to analyze the general dependence between temperature and stock market returns and show that the negative relation remains strong even after controlling for autocorrelations, GARCH effects and non-normality. We conclude that the negative correlation between temperature and stock market returns is prevalent.

“Does a Slowdown in the Sensitive Sector of the Economy Signal Economic Recession?”, with Thomas Fomby
Motivated by a 2006 New York Times article, we perform formal econometric analysis on a proposed leading indicator of the U.S. economy. We distinguish between the strategy for estimating forecasting equations with final-revised data and that with real-time-vintage data. Using conventional autoregressive (AR) and autoregressive distributed lag (ARDL) models we find that the slowdown in the so-called sensitive sector of our economy is an important indicator for economic recession. We also find that even though real-time-vintage data provides better fit in our linear regressions, it does not perform better than final-revised data in terms of forecasting exercises. Forecasts on GDP growth and efficiency of competing models are compared.

Work in Progress

“A Dynamic Common Factor Model on Inflation”

“Systemic Risk in Financial Services: Evidence from the Home Mortgage Crisis”, with Thomas Fomby and Jeffery Gunther

“Asymmetric Dependence Between Hedge Fund and Market Returns”, with Thomas Fomby and Jeffery Gunther