A new copula for modeling portfolios with skewed,leptokurtic and high-order dependent risk factors

The paper proposes a new copula for modeling higher-order dependencies between pairs of portfolio assets, employing orthogonal polynomials to model symmetric co-kurtoses. Skewness and leptokurtosis of portfolio margins are modeled either with the Gram–Charlier expansion of the Normal distribution or Gram–Charlier-like expansions of leptokurtic laws. Details on the estimation method of this copula are provided, and a simulation study is carried out to assess its potential range of applicability with respect to widely employed alternatives in the copula literature. Empirical evidence of the suitability of this approach to model financial data and compute risk measures is provided.     

Testing for mutually exciting jumps and financial flights in high frequency data

We propose a new nonparametric test to identify mutually exciting jumps in high frequency data. We derive the asymptotic properties of the test statistics and show that the tests have good size and reasonable power in finite sample cases. Using our mutual excitation tests, we empirically characterize the dynamics of financial flights in forms of flight-to-safety and flight-to-quality. The results indicate that mutually exciting jumps and risk-off trades mostly occur in periods of high market stress. Flight-to-safety episodes (from stocks to gold) arrive more frequently than do flight-to-quality spells (from stocks to bonds). We further find evidence that reverse cross-excitations or seeking-return-strategies exhibit significant asymmetry over the business cycle, reflecting the fact that investors appear to be selling gold – rather than bonds – to invest in stocks during good market conditions.