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The recursive prediction and filtering formulas of the Kalman filter are difficult to implement in nonlinear state space models since they require the updating of a function. The aim of this paper is to consider the situation of a large number n of individual measurements, called...
This paper proposes a new intraday volatility forecasting model, particularly suitable for modeling a large number of assets. We decompose volatility of high-frequency returns into components that may be easily interpreted and estimated. The conditional variance is a product of daily, diurnal,...
It is well known that strategies that allow investors to allocate their wealth using return and volatility forecasts, the use of which are termed market and volatility timing, are of significant value. In this paper, we show that distribution timing, defined here as the ability to use forecasts...
We provide evidence on two alternative mechanisms of interaction between returns and volatilities: the leverage ef fect and the volatility feedback effect. We stress the importance of distinguishing between realized volatility and implied volatility and find that implied volatilities are...
An important challenge of portfolio allocation arises when the (true) characteristics of returns' distribution are replaced by sample estimates. Such substitutions introduce estimation risk, which adds to traditional financial risk. I develop a new framework to provide a feasible optimal...
We propose several tests for rational bubbles and investigate their power properties. The focus lies on the case where bubble detection is reduced to testing for a unknown change from a random walk to an explosive process. In simulations, a Chow-type break test exhibits the highest power and...
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