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Speaker "Revant Nayar" Details Back

 

Topic

Can financial crashes be anticipated using physics?

Abstract

“The market has experienced large rallies and drawdowns over the last two years driven by uncertainties caused by the pandemic and inflationary fears. These ‘bubbles’ and ‘crashes’ are notoriously difficult to anticipate using AI and data-driven techniques due to non-stationarity and small sample sizes inherent in the problem. We turn to Sornette’s famous interacting spin model of investor interactions in which bubble-induced crashes result from phase transitions during which the dynamics of the market acquires a discrete scale invariance. We investigate if truly, these models or their extensions could have predicted some of the large drawdowns we have seen in the S&P 500 or the supposed ‘bursting of bubbles’ in ‘pandemic stocks’ such as Docusign, Teladoc and Zoom. 

Profile

Revant Nayar is currently Principal and CTO at FMI Tech, among the first quantum AI based quantitative hedge fund and Research Affiliate at Stony Brook University. He started his career as a theoretical physics researcher at IAS and Princeton University with a specialty in quantum field theory and string theory, where he started FMI Tech as a think-tank applying cutting edge innovations in quantum and classical physics to data science and quantitative finance. Subsequently, he served as Research Fellow at NYU Tandon where he developed the first ever group theoretic method to compute options pricing density functions with Peter Carr. 
 
In 2021, he became among the first fund managers applying quantum alternatives to AI to asset management starting with the Indian market and recently expanding to the US market. He has over the years been featured as speaker and panellist at the leading finance and AI conferences including Bloomberg, Strata, Global AI Conference, YPO, NYU and EMEX. He also runs among the largest econophysics research collaborations in the world (FTERC), bringing students, researchers and professors from top universities around the world to generate research at the intersection of physics, mathematics and quantitative finance. Today he is widely regarded as a trailblazer in quantum and econophysics-inspired approaches to asset and risk management and among the promising emerging quant fund managers.