All too often, measuring statistical dependencies between financial time series is reduced to a linear correlation coefficient. However, this may not capture all facets of reality. This paper studies empirical dependencies of daily stock returns by their pairwise copulas. We investigate in...

We study the dependence structure of market states by calculating empirical pairwise copulas of daily stock returns. We consider both original returns, which exhibit time-varying trends and volatilities, as well as locally normalized returns, where the nonstationarity has been removed. The...

We propose a new measure named the symbolic performance to better understand the structure of foreign exchange markets. Instead of considering currency pairs, we isolate a quantity that describes each currency's position in the market, independent of a base currency. We apply the k-means...

There are non-vanishing price responses across different stocks in correlated financial markets. We further study this issue by performing different averages, which identify active and passive cross-responses. The two average cross-responses show different characteristic dependences on the time...

Previous studies of the stock price response to trades focused on the dynamics of single stocks, i.e. they addressed the self-response. We empirically investigate the price response of one stock to the trades of other stocks in a correlated market, i.e. the cross-responses. How large is the...

We analyze a recently proposed spatial autoregressive model for stock returns and compare it to a one-factor model and the sample covariance matrix. The influence of refinements to these covariance estimation methods is studied. We employ power mapping as a noise reduction technique for the...