Forecasting Multifractal Volatility

  title={Forecasting Multifractal Volatility},
  author={Laurent E. Calvet and Adlai J. Fisher},
  journal={Econometrics: Applied Econometrics \& Modeling eJournal},
Component-wise Representations of Long-memory Models and Volatility Prediction
Extracting and forecasting the volatility of financial markets is an important empirical problem. The article provides a time series characterization of the volatility components arising when the
Exponential Smoothing , Long Memory and Volatility Prediction Tommaso Proietti
Extracting and forecasting the volatility of financial markets is an important empirical problem. The paper provides a time series characterization of the volatility components arising when the
On a multi-timescale statistical feedback model for volatility fluctuations
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Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data
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Option Pricing with Markov Switching Stochastic Volatility Models
  • Yiying Cheng
  • Mathematics, Economics
    Advances in Pacific Basin Business, Economics and Finance
  • 2020
A closed-form option pricing formula and the corresponding hedging strategy for a broad class of MSSV models are developed and it is established that these models perform well in one-day-ahead forecasts of option prices.
Flexible and Robust Modelling of Volatility Comovements: A Comparison of Two Multifractal Models
Long memory (long-term dependence) of volatility counts as one of the ubiquitous stylized facts of financial data. Inspired by the long memory property, multifractal processes have recently been
A Markov-switching multifractal approach to forecasting realized volatility
The volatility specification of the Markov-switching Multifractal (MSM) model is proposed as an alternative mechanism for realized volatility (RV). We estimate the RV-MSM model via Generalized Method


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Density forecasting is increasingly more important and commonplace, for example in financial risk management, yet little attention has been given to the evaluation of density forecasts. The authors
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This book contains several innovative models for the prices of financial assets. First published in 1986, it is a classic text in the area of financial econometrics. It presents ARCH and stochastic
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There has been a tradition among economists which holds that prices in speculative markets, such as grain and securities markets, behave very much like random walks. References include Bachelier
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SummaryWe study equilibria in which agent's belief are rational in the sense of Kurz [1994]. The market is formulated by specifying a stochastic demand function and a continuum of producers, each
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This textbook on financial markets has two purposes: one is to introduce students to the latest theory of financial markets, and the other is to explain the advanced mathematics that is the language