Boris Skorodumov

Boris Skorodumov stands as a distinguished quantitative analyst, boasting an extensive track record in the finance sector complemented by a solid academic foundation.
He is a proud alumnus of Columbia University with an M.S. in Mathematics of Finance and has earned a Ph.D. in Nuclear Physics from the prestigious University of Notre Dame. This combination of scholarly achievement and hands-on experience provides him with a distinctive viewpoint and a broad range of capabilities, making him adept at unraveling intricate challenges and pioneering cutting-edge solutions.

  • Ph.D
    Physics

  • M.S
    Finance

  • B.S
    Mathematics

  • Current focus :
    Structured Products

Profile

My journey into nuclear physics PhD studies encompassed several ventures into quantitative finance, igniting a newfound passion for the field. By the close of 2007, my career path had pivoted from the realms of nuclear physics to the dynamic world of applied quantitative finance. This transition was marked by fruitful collaborations with Wall Street experts, tackling real-world issues in portfolio management. The remarkable journey of Emanuel Derman from a physicist to a leading figure in quantitative analysis, chronicled in his work "My Life as a Quant," greatly inspired me. It was an unexpected honor to meet Professor Derman at Columbia University shortly thereafter. The hands-on experience in quantitative finance and the prospect of making a similar transition as Derman bolstered my move towards the finance sector.

Milestones

2007-2008

2008-2010

2010-2012

2012-2017

2017-2022

2022-Current

My journey to quantitative finance started at Columbia University where I studied Mathematics of Finance.

I worked as a quantitative analyst at an energy trading company, providing support to the natural gas and oil trading desks. My responsibilities included assisting with the structuring, pricing, and risk management of commodity derivatives.

I worked as a quantitative analyst at a structured products firm, where I helped build and validate quantitative models for equities, commodities, and foreign exchange markets.

I worked as a quantitative analyst at the investment bank with a primary focus on structured finance. My responsibilities included designing and validating structured product models to support the equity business.

I worked as a portfolio manager at a asset management firm. I helped to build a quantitative asset management group and a structured products business. During my tenure, I launched two algorithmic ETFs and built cross-asset structured products businesses that targeted institutional and retail investors.

I work as a quantitative analyst for a digital asset firm, where I focus on building factor risk models and risk attribution systems.

Selected papers

Review of QIS in traditional finance

The search for new and sophisticated sources of investment return, the appeal of lower-cost quantitative strategies that offer the continuing promise of outperformance coupled with the ...

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Combining ESG Ratings with News Sentiment Generates...

ESG ratings as a stock screener for downside protection can be significantly improved when combined with sentiment indicators derived from news and social media. Following a statistical approach ...

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Sentiment Data Outperforms During Coronavirus Crisis

News sentiment can enhance alpha strategies, along with augmenting risk management models for downside protection during periods of crisis. Following a statistical approach, where by.

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Generating Alpha from Insider Transactions


Insider transactions data can provide valuable insights that are not directly accessible in the public domain. It provides investors with insights into how C-level executives interpret their own ...

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Estimation of mean reversion in Oil and Gas markets

The presence of mean reversion was investigated from historical data of Henry Hub, WTI Crude and Brent Crude spot prices for the time frame 1990-2008. It was analyzed with in the scope of single ...

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Analytical one-factor pricing model for energy vanilla options

One-factor model for forward prices was used to price vanilla options. The mean reversion rate and forward volatility were extracted from available market prices of calls and puts via calibration process ...

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