FORECASTING MULTIFRACTAL VOLATILITY PDF

This paper develops analytical methods to forecast the distribution of future returns for a new continuous-time process, the Poisson multifractal. The process . of Technology. Chapter 7: Thoroughly revised version from Journal of Econometrics,. , L. E. Calvet and A. J. Fisher. ‘Forecasting Multifractal Volatility,’ pp. Calvet and Fisher present a powerful, new technique for volatility forecasting that draws on insights from the use of multifractals in the natural sciences and.

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We introduce a discretized version of the model that has a finite state space and allows for an analytical solution to the conditioning problem.

It can be interpreted as a stochastic volatility model with multiple frequencies and a Markov fogecasting state. Have you forgotten your login? The challenge in this environment is long memory and the corresponding infinite dimension of the state space.

Forecasting Long memory Multiple frequencies Stochastic volatility Weak convergence. If you are a registered author of this item, you may also want to check the “citations” tab in your RePEc Author Service profile, multifractql there may be some citations waiting for confirmation.

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We introduce a discretized version of the model that has a finite state space and an analytical solution to the conditioning problem. Other versions of this item: We assume for simplicity that the forecaster knows the true generating process with certainty but only observes past returns.

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If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form. This paper develops analytical methods to forecast the distribution of future returns for a new continuous-time process, the Poisson multifractal.

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Laurent-Emmanuel Calvet 1 AuthorId: Paper This paper develops analytical methods to forecast the distribution of future returns for a new continuous-time process, the Poisson multi-fractal. Download full text from publisher File URL: Calvet Adlai Julian Fisher. Please note that corrections may volstility a couple of weeks to filter through the various RePEc services.

RePEc uses bibliographic data supplied by the respective publishers. Calvet, Laurent Fisher, Adlai. It also allows you to accept potential citations to this item that we are uncertain about. More about this item Statistics Access vplatility download statistics. Laurent-Emmanuel Calvet 1 Adlai J.

You can help correct errors and omissions. Monday, December 17, – 4: It can be interpreted as a stochastic volatility model with multiple frequencies and a Markov latent state.

As the grid size goes to infinity, the discretized model weakly converges to the continuous-time process, implying the consistsency of the density forecasts. For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Corrections All material on this site has been provided by the respective publishers and authors.

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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The process captures the thick tails, volatility persistence and moment scaling exhibited by many financial time series.

Forecasting multifractal volatility

This abstract was borrowed from another version of this item. We assume for simplicity that the forecaster knows the true generating process with certainty but only observes past returns.

Stern School of Business. The process captures the thick tails, volatility persistence, and moment scaling exhibited by many financial time series.

Forecasting multifractal volatility

Full text for ScienceDirect subscribers only As the access to this document is restricted, you may want to look for a different version below or search for a different version of it. When requesting a correction, please mention this item’s handle: General contact details of provider: Friday, April 30, – 2: If you have authored this item and are not yet registered with RePEc, we encourage you to do it here.

As the access to this document is restricted, you may multiffactal to look for a different version below or search for a different version of it. The challenge in this environment is long memory and the corresponding infinite dimension of the state space.

See general information about how to forecastinng material in RePEc. If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. This allows to link your profile to this item.