# Log-modulated rough stochastic volatility models

```@article{Bayer2020LogmodulatedRS,
title={Log-modulated rough stochastic volatility models},
author={Christian Bayer and F. Harang and Paolo Pigato},
journal={arXiv: Mathematical Finance},
year={2020}
}```
• Published 2020
• Mathematics, Economics
• arXiv: Mathematical Finance
We propose a new class of rough stochastic volatility models obtained by modulating the power-law kernel defining the fractional Brownian motion (fBm) by a logarithmic term, such that the kernel retains square integrability even in the limit case of vanishing Hurst index \$H\$. The so-obtained log-modulated fractional Brownian motion (log-fBm) is a continuous Gaussian process even for \$H = 0\$. As a consequence, the resulting super-rough stochastic volatility models can be analysed over the whole… Expand
2 Citations

#### References

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