Financial markets embed expectations of central bank policy into asset prices. This paper compares two approaches that extract a probability density of market beliefs. The first is a simulatedmoments estimator for option volatilities described in Mizrach (2002); the second is a new approach...

Financial markets embed expectations of central bank policy into asset prices. This paper compares two approaches that extract a probability density of market beliefs. The first is a simulated moments estimator for option volatilities described in Mizrach (2002); the second is a new approach...

We introduce the new F-Riesz distribution to model tail-heterogeneity in fat-tailed covariance matrix observations. In contrast to the typical matrix-valued distributions from the econometric literature, the F-Riesz distribution allows for different tail behavior across all variables in the...

The network structure of non-centrally cleared derivative markets, uncovered via the European Market Infrastructure Regulation (EMIR), is investigated with a focus on the Covid-19 market turmoil period. Initial and variation margin networks are reconstructed to analyze channels of potential...

We advocate the use of absolute moment ratio statistics in conjunctionwith standard variance ratio statistics in order to disentangle lineardependence, non-linear dependence, and leptokurtosis in financial timeseries. Both statistics are computed for multiple return horizonssimultaneously, and...

We introduce the new F-Riesz distribution to model tail-heterogeneity in fat-tailed covariance matrix observations. In contrast to the typical matrix-valued distributions from the econometric literature, the F-Riesz distribution allows for di↵erent tail behavior across all variables in the...

The network structure of non-centrally cleared derivative markets, uncovered via the European Market Infrastructure Regulation (EMIR), is investigated with a focus on the Covid-19 market turmoil period. Initial and variation margin networks are reconstructed to analyze channels of potential...

In this paper we study the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce...

Underreporting and undersampling biases in top tail wealth, although widely acknowledged, have not been statistically quantified so far, essentially because they are not readily observable. Here we exploit the functional form of power law-like regimes in top tail wealth to derive analytical...