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We investigate the economic value of multivariate volatility forecasting ability using a testing framework that assesses the quality of competing methods from a conditional investment perspective. This approach provides a novel means of assessing the benefits of using a particular set of...
We introduce a new model for the joint dynamics of the S&P 100 index and the VXO implied volatility index. The nonlinear specification of the variance process is designed to simultaneously accommodate extreme persistence and strong mean reversion. This grants superior forecasting power over the...
Based on a new approach for measuring the comovements between stock market returns, we provide a new test for the null hypothesis of symmetric comovements in the sense that stock market downturns will lead to the same degree of comovements as market upturns. Since the new measure of comovements...
Realized variance can be broken down into a continuous volatility and a jump components. We show that these two components have very different degrees of power of prediction on future long-term excess stock market returns. Namely, continuous volatility is a key driver of medium to long-term...
Parsimoniously specified distributed lag models have enjoyed a resurgence under the MIDAS moniker (Mixed Data Sampling) as a feasible way to model time series observed at very different sampling frequencies. I introduce cointegrating mixed data sampling regressions. I derive asymptotic limits...
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