The Non‐Misleading Value of Inferred Correlation: An Introduction to the Cointelation Model B Mahdavi-Damghani Wilmott 2013 (67), 50-61, 2013 | 28 | 2013 |

The Misleading Value of Measured Correlation B Mahdavi-Damghani, D Welch, C O'Malley, S Knights Wilmott 2012 (62), 64-73, 2012 | 28 | 2012 |

De‐arbitraging With a Weak Smile: Application to Skew Risk B Mahdavi-Damghani, A Kos Wilmott 2013 (64), 40-49, 2013 | 24 | 2013 |

Introducing the Implied Volatility Surface Parametrization (IVP): Application to the FX Market B Mahdavi-Damghani Wilmott 2015 (77), 68-81, 2015 | 9 | 2015 |

Introducing the HFTE Model: A Multi-Species Predator Prey Ecosystem for High Frequency Quantitative Financial Strategies B Mahdavi-Damghani Wilmott 2017 (89), 2017 | 7 | 2017 |

A proposed risk modeling shift from the approach of stochastic differential equation towards machine learning clustering: Illustration with the concepts of anticipative … B Mahdavi-Damghani, S Roberts Available at SSRN 3039179, 2017 | 6 | 2017 |

The Unfortunate cosT Of Pattern rEcognition (UTOPE-ia): the Genetic Disorder of the Financial Industry B Mahdavi-Damghani Wilmott 2012 (60), 28-37, 2012 | 6* | 2012 |

Deciphering price formation in the high frequency domain: Systems & evolutionary dynamics as keys for construction of the high frequency trading ecosystem B Mahdavi-Damghani, S Roberts University of Oxford-Oxford-Man Institute of Quantitative Finance, 2017 | 5 | 2017 |

Portfolio optimization in the context of cointelated pairs: Stochastic differential equation vs. machine learning approach B Mahdavi-Damghani, K Mustafayeva, S Roberts, C Buescu Machine Learning Approach (March 4, 2018), 2018 | 4 | 2018 |

Machine Learning Techniques for Deciphering Implied Volatility Surface Data in a Hostile Environment: Scenario Based Particle Filter, Risk Factor Decomposition & Arbitrage … B Mahdavi-Damghani, S Roberts https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3133862, 2018 | 3 | 2018 |

Convergence of Heston to SVI Proposed Extensions: Rational & Conjecture for the Convergence of Extended Heston to the Implied Volatility Surface Parametrization B Mahdavi-Damghani, K Mustafayeva, S Roberts Available at SSRN 3039185, 2017 | 3 | 2017 |

Data-Driven Models & Mathematical Finance: Opposition or Apposition? B Mahdavi-Damghani Available at SSRN 3347739, 2019 | | 2019 |

A Bottom-up Approach to the Financial Markets B Mahdavi-Damghani, S Roberts Available at SSRN 3331423, 2019 | | 2019 |

Portfolio Optimization for Cointelated Pairs: SDEs vs. Machine Learning B Mahdavi-Damghani, K Mustafayeva, S Roberts, C Buescu arXiv preprint arXiv:1812.10183, 2018 | | 2018 |

Machine Learning vs. Mathematical Finance: Opposition or Apposition? Thoughts Around Reconstructing Quantitative Finance a Decade after the Subprime Derivatives & Electronic … B Mahdavi-Damghani University of Oxford, 2018 | | 2018 |

Agent-Based Quantitative Financial Strategies & Price Formation: Systems & Evolutionary Dynamics as Deciphering Keys of the High Frequency Trading Ecosystem B Mahdavi-Damghani, S Roberts | | 2018 |

Machine Learning Methods for Financial Forecasting: Application to the S&P 500. B Mahdavi-Damghani University of Oxford, 2006 | | 2006 |

Financial Mathematics or Machine Learning in the context of Portfolio Optimization for Cointelated Pairs? B Mahdavi-Damghani, K Mustafayeva, S Roberts, C Buescu | | |

Data-Driven Models & Mathematical Finance: Opposition or Apposition?(14th Draft) B MAHDAVI-DAMGHANI | | |