We provide a model-free test for asymmetric correlations in which stocks move more often with the market when the market goes down than when it goes up, and also provide such tests for asymmetric betas and covariances. When stocks are sorted by size, book-to-market, and momentum, we find strong evidence of asymmetries for both size and momentum portfolios, but no evidence for book-to-market portfolios. Moreover, we evaluate the economic significance of incorporating asymmetries into investment decisions, and find that they can be of substantial economic importance for an investor with a disappointment aversion (DA) preference as described by Ang, Bekaert, and Liu (2005). , Oxford University Press. (This abstract was borrowed from another version of this item.)

Asymmetries in Stock Returns: Statistical Tests and Economic Evaluation

In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Terasvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework In addition, other specification tests, with the aim of aiding the model building procedure, are considered Analytical expressions for the test statistics and the required derivatives are provided Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets

Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model

We investigate how the relation between gold prices and the U.S. Dollar has been affected by the recent turmoil in financial markets. We use spot prices of gold and spot bilateral exchange rates against the Euro and the British Pound to study the pattern of volatility spillovers. We estimate the bivariate structural GARCH models proposed by Spargoli e Zagaglia (2008) to gauge the causal relations between volatility changes in the two assets. We also apply the tests for change of co-dependence of Cappiello, Gerard and Manganelli (2005). We document the ability of gold to generate stable comovements with the Dollar exchange rate that have survived the recent phases of market disruption. Our findings also show that exogenous increases in market uncertainty have tended to produce reactions of gold prices that are more stable than those of the U.S. Dollar.

Quynh Nga Nguyen

Papers

Local Gaussian correlations in financial and commodity markets

Hedging and safe-haven characteristics of Gold against currencies: An investigation based on multivariate dynamic copula theory