FORECASTING MULTIFRACTAL VOLATILITY PDF

Help us Corrections Found an error or omission? Forecasting multifractal volatility General contact details of provider: It also allows you to accept potential citations to this item that we are uncertain about. Monday, December 17, — 4: As the grid step size goes to zero, the discretized model weakly converges to the continuous-time process, implying the consistency of the density forecasts. We assume for simplicity that the forecaster knows the true generating process with certainty but only observes past returns.

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Laurent E. Calvet Abstract This paper develops analytical methods to forecast the distribution of future returns for a new continuous-time process, the Poisson multifractal. The process captures the thick tails, volatility persistence, and moment scaling exhibited by many financial time series. It can be interpreted as a stochastic volatility model with multiple frequencies and a Markov latent state.

We assume for simplicity that the forecaster knows the true generating process with certainty but only observes past returns. The challenge in this environment is long memory and the corresponding infinite dimension of the state space. We introduce a discretized version of the model that has a finite state space and an analytical solution to the conditioning problem. As the grid step size goes to zero, the discretized model weakly converges to the continuous-time process, implying the consistency of the density forecasts.

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Forecasting multifractal volatility

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FORECASTING MULTIFRACTAL VOLATILITY PDF

Dacorogna, Michael M. Full references including those not matched with items on IDEAS More about this item Access and download statistics Corrections All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. See general information about how to correct material in RePEc. For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dana Niculescu. If you have authored this item and are not yet registered with RePEc, we encourage you to do it here.

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Forecasting Multifractal Volatility

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