Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Hansen, P. Reinhard"'
Autor:
Hansen, Peter Reinhard, Tong, Chen
We introduce a novel method for obtaining a wide variety of moments of a random variable with a well-defined moment-generating function (MGF). We derive new expressions for fractional moments and fractional absolute moments, both central and non-cent
Externí odkaz:
http://arxiv.org/abs/2410.23587
We introduce a novel multivariate GARCH model with flexible convolution-t distributions that is applicable in high-dimensional systems. The model is called Cluster GARCH because it can accommodate cluster structures in the conditional correlation mat
Externí odkaz:
http://arxiv.org/abs/2406.06860
Autor:
Hansen, Peter Reinhard, Tong, Chen
We introduce a new class of multivariate heavy-tailed distributions that are convolutions of heterogeneous multivariate t-distributions. Unlike commonly used heavy-tailed distributions, the multivariate convolution-t distributions embody cluster stru
Externí odkaz:
http://arxiv.org/abs/2404.00864
Autor:
Hansen, Peter Reinhard, Luo, Yiyao
Time-varying volatility is an inherent feature of most economic time-series, which causes standard correlation estimators to be inconsistent. The quadrant correlation estimator is consistent but very inefficient. We propose a novel subsampled quadran
Externí odkaz:
http://arxiv.org/abs/2310.19992
Autor:
Tong, Chen, Hansen, Peter Reinhard
The Clustered Factor (CF) model induces a block structure on the correlation matrix and is commonly used to parameterize correlation matrices. Our results reveal that the CF model imposes superfluous restrictions on the correlation matrix. This can b
Externí odkaz:
http://arxiv.org/abs/2308.05895
We propose a new method for generating random correlation matrices that makes it simple to control both location and dispersion. The method is based on a vector parameterization, gamma = g(C), which maps any distribution on R^d, d = n(n-1)/2 to a dis
Externí odkaz:
http://arxiv.org/abs/2210.08147
Autor:
Hansen, Peter Reinhard, Tong, Chen
We introduce a pricing kernel with time-varying volatility risk aversion that can explain the observed time variation in the shape of the pricing kernel. Dynamic volatility risk aversion, combined with the Heston-Nandi GARCH model, leads to a conveni
Externí odkaz:
http://arxiv.org/abs/2204.06943
We introduce a new volatility model for option pricing that combines Markov switching with the Realized GARCH framework. This leads to a novel pricing kernel with a state-dependent variance risk premium and a pricing formula for European options, whi
Externí odkaz:
http://arxiv.org/abs/2112.05308
We show that the Realized GARCH model yields close-form expression for both the Volatility Index (VIX) and the volatility risk premium (VRP). The Realized GARCH model is driven by two shocks, a return shock and a volatility shock, and these are natur
Externí odkaz:
http://arxiv.org/abs/2112.05302
Autor:
Hansen, Peter Reinhard
We propose a simple dynamic model for estimating the relative contagiousness of two virus variants. Maximum likelihood estimation and inference is conveniently invariant to variation in the total number of cases over the sample period and can be expr
Externí odkaz:
http://arxiv.org/abs/2110.00533