We propose to model the joint distribution of bid-ask spreads and log returns of a stock portfolio by using Autoregressive Conditional Double Poisson and GARCH processes for the marginals and vine copulas for the dependence structure. By estimating the joint multivariate distribution of both returns and bid-ask spreads from intraday data, we incorporate the measurement of commonalities in liquidity and comovements of stocks and bid-ask spreads into the forecasting of three types of liquidity-adjusted intraday Value-at-Risk (L-IVaR). In a preliminary analysis, we document strong extreme comovements in liquidity and strong tail dependence between bid-ask spreads and log returns across the firms in our sample thus motivating our use of a vine copula model. Furthermore, the backtesting results for the L-IVaR of a portfolio consisting of five stocks listed on the NASDAQ show that the proposed models perform well in forecasting liquidity-adjusted intraday portfolio profits and losses.

We show that the propensity of a bank to experience extreme co-movements in its credit default swap (CDS) premia together with the market is priced in the bank’s default swap spread during the financial crisis. We measure a bank’s CDS tail beta by estimating the upper tail dependence between its default swap spreads and a CDS market index. Our study shows that protection sellers receive a premium for bearing the risk of extreme upward co-movements in default risk. The economic significance of this effect is large yet limited to the recent financial crisis. Banks in the upper quintile of CDS tail beta have spreads that are on average 140 basis points higher than those of banks in the lower CDS tail beta quintile.