Estimating stochastic volatility models using daily returns and realized volatility simultaneously

@article{Takahashi2007EstimatingSV,
  title={Estimating stochastic volatility models using daily returns and realized volatility simultaneously},
  author={Makoto Takahashi and Yasuhiro Omori and Toshiaki Watanabe},
  journal={Comput. Stat. Data Anal.},
  year={2007},
  volume={53},
  pages={2404-2426}
}
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49 References

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