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Abstract We examine the relationship between Mixed Data Sampling (MIDAS) regressions and the estimation of state space models applied to mixed frequency data. While in some cases the binding function is known, in general it is not, and therefore indirect inference is called for. The approach is...
Abstract Most GARCH-type models follow Engle’s (1982) original idea of modeling the volatility of asset returns as a function of only past information. We propose a new model, which retains the simple GARCH structure, but describes the volatility process as a mixture of past and current...
Abstract This paper investigates the pricing and weak convergence of an asymmetric non-affine, non-Gaussian GARCH model when the risk neutralization is based on a variance-dependent exponential linear pricing kernel with stochastic risk aversion parameters. The risk-neutral dynamics are obtained...
Abstract We examine the impact of temporal and portfolio aggregation on the quality of Value-at-Risk (VaR) forecasts over a horizon of 10 trading days for a well-diversified portfolio of stocks, bonds and alternative investments. The VaR forecasts are constructed based on daily, weekly, or...
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