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Deep Learning Interpretability for Rough Volatility

Derivatives Editor -

A group of Cambridge, Imperial College, Alan Turing Institute, and Mediobanca researchers, Damiano Brigo, Bo Yuan, Jack Jacquier, and Nicola Pede, have recently published a preprint entitled Deep Learning Interpretability for Rough Volatility. Here is a non-technical overview of this preprint. Understanding Deep Learning Interpretability...

Machine Learning, Artificial Intelligence, and Inflation Trading: An Interview with Dariush Mirfendereski

Today, Paul Bilokon (Thalesians Ltd) interviewed Dariush Mirfendereski, an alumni of the Machine Learning Institute, established by World Business Strategies, Thalesians, and Thalesians Marine. For many years, Dariush used to be Global Head of Inflation Trading at HSBC. Paul...

Modern Equity Investing Strategies

Anatoly (Alec) Schmidt, Adjunct Professor of Financial Engineering at NYU Tandon School and Stevens Institute of Technology has published a new book - Modern Equity Investing Strategies (World Scientific). This book will satisfy the...

Did Arthur Whitney just open-source k?

The source code of the programming language k (the one behind kdb+/q and Shakti) has been closely guarded by its developer, Arthur Whitney. Earlier in his career he did release the Inculabulum, which he wrote on...

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How to learn cryptography

The understanding of cryptocurrencies and Blockchain implies at least a cursory familiarity with cryptography. In this short note we will consider some of the tools that you could use to learn cryptography rapidly. Prof....

Global Valuation: An Interview with Claudio Albanese

Derivatives Editor -

Today, Paul Bilokon (Thalesians Ltd) interviewed Claudio Albanese, a leading expert on quantitative and computational finance and Founder of Global Valuation. Claudio is also Faculty at Machine Learning Institute (MLI). PB:In 2006, you transitioned from academia to launch Global Valuation. What was the initial business plan? CA: The central idea was that GPU computing would revolutionize Computational Finance and Mathematical Finance. I believed the industry needed to be fundamentally rebuilt with matrix multiplication as the central performance bottleneck. At that time, the significance of this wasn't as clear-cut as it is now. Today, we have seen Machine Learning reshape Classical Statistics, anchored heavily on matrix multiplication, a principle that is true for...

Deep Learning Interpretability for Rough Volatility

A group of Cambridge, Imperial College, Alan Turing Institute, and Mediobanca researchers, Damiano Brigo, Bo Yuan, Jack Jacquier, and Nicola Pede, have recently published...

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