We propose to forecast the Value-at-Risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence. We compare our proposed method to a conventional copula-GARCH model where the parameter of a Clayton...

We propose a methodology that can efficiently measure the Value-at-Risk (VaR) of large portfolios with time-varying volatility and correlations by bringing together the established historical simulation framework and recent contributions to the dynamic factor models literature. We find that the...

We propose a new set of formal backtests for VaR-forecasts that significantly improve upon existing backtesting procedures. Our new test of unconditional coverage can be used for both one-sided and two-sided testing, which leads to a significantly increased power. Second, we stress the...

This paper contributes to technical analysis (TA) literature by showing that the high and low prices of equity shares are largely predictable only on the basis of their past realizations. Moreover, using their forecasts as entry/exit signals can improve common TA trading strategies applied on US...

This study models and forecasts the evolution of intraday implied volatility on an underlying EUR–USD exchange rate for a number of maturities. To our knowledge we are the first to employ high frequency data in this context. This allows the construction of forecasting models that can attempt...

We propose a panel data model of price discovery. We find that the stock market contributes to price discovery in most sectors while the Credit Default Swap (CDS) market contributes to price discovery in only a few sectors. We discover that in sectors where both the stock market and the CDS...

This paper proposes and implements a parsimonious three-factor model of the term structure whose dynamics is driven uniquely by observable state variables. This approach allows comparing alternative views on the way state variables – macroeconomic variables, in particular – influence the...

A large universe of technical trading rules applied to a set of technology industry and small cap sector portfolios over the 1995–2010 period yields superior predictability after adjusting for data snooping bias in the first half of the sample period and delivers statistically significant...

This paper assesses the sensitivity of the risk buffers, or capital requirements, of central counterparties clearing over-the-counter derivatives trades to a range of model inputs. It finds capital requirements to be highly sensitive to whether key model parameters are calibrated on a...

We propose the use of convex combinations of parametric copulas as pair-copulas in high-dimensional vine copula models. By doing so, we circumvent the error-prone need to choose and estimate a parametric copula for each pair-copula in a vine model. We show in simulations that our proposed model...