Boris Skorodumov

is an experienced quantitative analyst with a demonstrated history of working in the financial industry.
He holds an M.S. in Mathematics of Finance from Columbia University and a Ph.D. in Nuclear Physics from the University of Notre Dame.

  • Current industry
    Digital Assets

About me

During my PhD studies in nuclear physics, I completed several projects related to quantitative finance, which sparked my interest in the field. By the end of 2007, I decided to shift my focus from fundamental nuclear physics to applied quantitative finance. I began collaborating with practitioners on Wall Street to solve practical problems in portfolio management.

I was amazed by Emanuel Derman's transition from physicist to quantitative analyst, as described in his book "My Life as a Quant". To my surprise, I had the opportunity to meet Prof. Derman at Columbia University within a year. My experience in quantitative finance projects, combined with the possibility of transitioning from nuclear physicist to quantitative analyst, pushed me towards the financial industry.

Timeline

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.

Publications

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 ...

Learn more

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 ...

Learn more

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.

Learn more

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 ...

Learn more

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 ...

Learn more

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 ...

Learn more