We propose a multivariate nonparametric technique for generating reliable shortterm historical yield curve scenarios and confidence intervals. The approach is based on a Functional Gradient Descent (FGD) estimation of the conditional mean vector and covariance matrix of a multivariate interest...

We propose the Heterogeneous Autoregressive (HAR) model for the estimation andprediction of realized correlations. We construct a realized correlation measure where both the volatilities and the covariances are computed from tick-by-tick data. As for the realized volatility, the presence of...

We propose an affine term structure model which accommodates non-linearities in the drift and volatility function of the short-term interest rate. Such non-linearities are a consequence of discrete beta-distributed regime shifts constructed on multiple thresholds. We derive iterative closed-form...

We propose a new multivariate DCC-GARCH model that extends existing approaches by admitting multivariate thresholds in conditional volatilities and conditional correlations. Model estimation is numerically feasible in large dimensions and positive semi-definiteness of conditional covariance...

We propose a simple class of multivariate GARCH models, allowing for time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical)...

We propose a multivariate nonparametric technique for generating reliable scenarios and confidence intervals for the term structure of interest rates from historical data. The approach is based on a functional gradient descent (FGD) estimation of the conditional mean vector and the conditional...

Prices or returns of financial assets are most often collected in local times of the trading markets. The need to synchronize multivariate time series of financial prices or returns is motivated by the fact that information continues to flow for closed markets while others are still open. We...

The fast-growing literature on the news and social media analysis provide empirical evidence that the financial markets are often driven by information rather than facts. However, the direct effects of sentiments on the returns are of main interest. In this paper, we propose to study the...

The daily term structure of interest rates is filtered to reduce the influence of cross-correlations and autocorrelations on its factors. A three-factor model is fitted to the filtered data. We perform statistical tests, finding that factor loadings are unstable through time for daily data. This...

We document that cross-sectional return predictions based on OLS and Lasso type linear methods contain no predictive power for large cap stocks over the last decades. Small and micro cap stocks are highly predictable throughout the entire sample. Based on the 68 firm characteristics (FC)...