) with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the … sufficiently many volatility components. In comparison with a Binomial MSM specification [7], results are almost identical. This … distribution is very limited. -- Markov-switching multifractal ; scaling ; return volatility …

) with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the … sufficiently many volatility components. In comparison with a Binomial MSM specification [7], results are almost identical. This …

Realized variance can be broken down into continuous volatility and jumps. We show that these two components have very … different predictive powers on future long-term excess stock market returns. While continuous volatility is a key driver of … volatility and future returns. Two by-products of our analysis are that imposing model-based constraints on long term regressions …

found in asset returns distributions, and long-memory found in volatility. Multifractal scaling cannot be assumed, it should …

with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the … uses sufficiently many volatility components. In comparison with a Binomial MSM specification [11], results are almost …