George Pastrana has extensive experience applying scientific principles to financial problems. He has expertise in option valuation, risk management of derivative portfolios, developing trading strategies, and setting up enterprise-wide risk management systems. Additionally, he has experience with capital management, supplier risk management, operational risk analysis, and quantitative support of trading operations. He is interested in high-level quantitative roles that involve solving complex problems and explaining results to business managers.

1. June 2016
I have always been interested in science and math and like to apply their concepts in all the work that I
do. I studied physics both in college (MIT) and graduate school (Stanford) and worked in research groups
run by very successful physicists, a couple of which are Nobel Prize winners. I am primarily interested in
conceptual frameworks that provide an underpinning for practical solutions for classes of interrelated
problems. My application of scientific principles to financial problems has evolved more or less along the
following lines.
Option Valuation (Trading Desk and CRO/Model Validation Control related)
I am expert in valuing all types of contingent claims: derivatives/options; forwards & futures; structured
products; etc. I have experience with these contracts applied to currencies, commodities, equities and
fixed income, but primarily equities and currencies.
Risk Management of Portfolios Containing Options and Their Underlying Hedges (Trading Desk and
CRO related)
I am expert in the practical risk management of derivative portfolios including how to hedge exotic
options with either vanilla options or their underlying instruments in optimal, cost effective ways. I have
designed and implemented Monte-Carlo simulation based hedging applications to help traders set
rational bid-ask spreads that include hedging transaction costs.
Prop Trading Research and Development (Hedge Fund related)
Developed technical, trend following, multi-asset futures trading strategy. Responsible for trading
signals and allocation rules. System was executed by the trading desk, with no trader discretion allowed.
Allocation rules based on adaptive time-series Sharpe Ratio based filter. Back-testing showed an overall
Sharpe Ratio of about 2, actual performance was closer to 1.5.
Enterprise-Wide Market Risk Management (CRO related)
I have set up a firm-wide market risk management system at Morgan Stanley with risk data elements
collection, VAR and Stress Test capabilities and applied a risk limit framework to it.
I set up a real-time market risk management system at Lehman Brothers that integrated the listed, OTC,
derivatives and program trading desks and calculated VAR and Stress Tests.
Capital Management (CEO, CFO, CRO, COO related)
I have developed a capital management framework that is based on modeling a firm’s stochastic cash
flows and takes into account cost structures including compensation policy, leverage dependent costs of
debt and shareholder payout considerations. It is based on Value-Based Management principles and
allows for business unit specific Costs of Equity. Used it to advice senior management (CEO, CFO, CRO) at
UBS on matters such as: Dividend Policy including Share Buy-Backs; Risk Based Budgeting for the
Investment Bank: Fair Pricing of internal M&A (Corporate Acquisitions/Disbursements), Currency
Management of Equity Replicating Portfolio.
Supplier Risk Management/Third Party Management (CRO, COO related)
I developed, and it is slowly being implemented at Citi, a comprehensive Supplier Risk Management
framework. It is based on modern Security Risk Analysis principles as deployed by large software firms or
the Department of Homeland Security embedded within the COSO Operational Risk Framework. In other
words it analyzes a supplier’s risk in terms of an Inherent Risk related to its touch points with the firm

2. and a Residual Risk after all Control Treatments and their effectiveness are considered. It considers the
superposition of many threat scenarios that are specified by their Impact and Likelihood of occurrence.
Operational Risk Analysis (CRO, COO related)
I developed new techniques to analyze Operational Risk Data in order to map it to well-defined
Operational Risk Domains and to detect possible previously unknown or emerging operational risks.
Much of this analysis involves text analytic methods in order to extract actionable intelligence from
unstructured free-text data elements arising from internal audit or manager’s own risk assessments, IT
outage incidents, SAS compiled Operational Loss Events, Regulatory Issues, etc.
I would ideally love to be involved in high level (CIO, CEO, CFO, CRO, COO, CTO) quantitative support of
trading or financial operations. I am very good at putting together and managing small teams of very
talented people with diverse skills targeted at solving important complex problems. I can convert
business/investment problems into well posed quantitative problems and solve them with such a team
and explain the results and their implementation in terms non-technical business managers can
understand.
Cheers,
George Pastrana