Forecast combinations have frequently been found in empirical studies to produce better
forecasts on average than methods based on the ex ante best individual forecasting model …

Volatility has been one of the most active and successful areas of research in time series
econometrics and economic forecasting in recent decades. This chapter provides a selective …

The concepts of portfolio optimization and diversification have been instrumental in the
development and understanding of financial markets and financial decision making. In light …

The paper deals with the estimation of a high dimensional covariance with a conditional
sparsity structure and fast diverging eigenvalues. By assuming a sparse error covariance …

Second moments of asset returns are important for risk management and portfolio selection.
The problem of estimating second moments can be approached from two angles: time series …

We assess the out-of-sample performance of Bitcoin within portfolios of various asset
classes and a well-diversified portfolio under four strategies and estimate the economic …

We evaluate the out-of-sample performance of the sample-based mean-variance model,
and its extensions designed to reduce estimation error, relative to the naive 1/N portfolio. Of …

The central message of this paper is that nobody should be using the sample covariance
matrix for the purpose of portfolio optimization. It contains estimation error of the kind most …

portfolio selection requires an estimator of the covariance matrix of returns. To address this
problem, we promote a nonlinear shrinkage estimator that is more flexible than previous …

This paper empirically assesses the ability of three putative stablecoins (two dollar-backed,
Tether and USD Coin; and one gold-backed, Digix Gold) to mitigate the risk of facing severe …