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Quantitative analyst

Illinois, United States
January 29, 2017

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Aditya Gudsoorkar

**** * ******** ******, ***. *R • Chicago, IL 60616 • 773-***-**** •


• Analytical Skills: Time Series Analysis, Data Analysis, Predictive Modelling, Analysis of Variance, Regression Analysis

• Platforms and Frameworks: R Studio, SAS Enterprise Edition, .NET, Visual Studio, MS Excel, MS Access

• Tools and Programing Languages: C++, C#, R, MATLAB, SQL, Python, VBA, Reuters, Bloomberg

• Financial Risk Management: Portfolio Risk using Value at Risk, GARCH, NGARCH, Monte-Carlo simulation EDUCATION

IIT STUART SCHOOL OF BUSINESS, Chicago, IL Expected May 2017 MS Finance (Financial Engineering)

Recipient, Stuart School of Business Merit-Based Scholarship Relevant Coursework: Statistical Analysis, .Futures and Options, Models for Derivatives, Market Risk Member of Stuart Investment Club, Member of Centre for Financial Innovation

DHIRUBHAI AMBANI INSTITUTE OF INFORMATION AND COMMUNICATION TECHNOLOGY, Gandhinagar, India April 2011 Bachelor of Technology (Information and Communication Technology) Head of Music Club, Editor for the university magazine ‘Entelechy’ EXPERIENCE

DAIRY OPPORTUNITIES LLC, Chicago November 2016- Present Quantitative Analyst Intern

• Derived statistical inferences out of fundamental data like USDA reports, NASS survey and New Zealand global dairy trade data and building an analytics system based on it

• Built a regression based futures price predictability model based on the historical data of dairy spot auction

• Use data science tools in R with the help of libraries like Time series Analysis, Performance Analytics, Quandl etc. for forecasting prices of various dairy instruments

• Modelled a quantitative trading strategy for dairy futures and options traded on CME

• Writing scripts in R for automating various processes which assists in trading decisions FUTURES INDUSTRY ASSOCIATION, Chicago Sep 2016- Present Derivatives Database Analyst

• Cleaned the historical FIA derivatives data and ran various data manipulation techniques in R

• Performed physical and logical database design for historical derivatives data

• Wrote analytical SQL queries to fetch trends of transactions in Futures & Options for building global FIA Derivatives database

FUTURES FIRST (GH FINANCIALS), Hyderabad, India June 2011- June 2015 Commodity Analyst/Trader

• Traded Corn, Wheat ad Soybean futures and options with fundamental and technical view on CBOT and NYSE LIFFE

• Developed an in depth understanding of fundamentals of agricultural commodities with respect to seasonality, price risk, futures curve and physical aspects

• Analysed USDA reports, Export Sales, WASDE reports, NASS survey etc. and presented them to the team

• Developed trading strategies and implemented them with VBA and C++

• Tracked macro-economic developments, geo-political events and price movements of global indices which could affect commodity markets

• Managed a trade book with a notional value of $5 million which generated monthly transaction revenues of $20,000 PROJECTS AND RESEARCH

STYLE ANALYSIS, PORTFOLIO ANALYTICS, AND PORTFOLIO ATTRIBUTION Jan 2016-June 2016 Guide: Ricky Cooper, Illinois Tech, Chicago

• Performed style analysis for a US multi cap equity mutual fund using the four Russell indices to determine the investing style of the fund and to determine the benchmark by calculating minimum tracking error

• Performed time series & weighted average regressions to analyze the active returns of manager’s portfolio

• Performed portfolio analytics with risk factors such as beta, market cap, book to price, and sectors to determine the efficiency of the risk model, to determine which risk factors drove the market MARKET RISK Aug 2016-Dec 2016

Guide: Prof Li Cai, Illinois Tech, Chicago

• Calculated historical simulation 1-day 95% VaR and 1-Day 95% CVaR, Linear VaR for a portfolio of ETF

• Wrote a script in R to calculate Maximum Drawdown

• Simulated an exotic options position in order to calculate Monte Carlo Simulation VaR in R

• Used daily return data of an instrument to model the volatility by GARCH model and EWMA model, and evaluated the performance of each model by statistical tests


Guide: Prof Sang Baum Kang, Illinois Tech, Chicago

• Analyzed payoff structure for compound options and programmed in MATLAB to calculate prices of four types of compound options i.e. call-on-call, call-on-put, put-on-call, put-on-put. COMMODITY FUTURES RETURN PREDICTABILITY AND HEDGING STRATEGIES Jan 2016-June 2016 Guide: Prof. Sang Baum Kang, Illinois Tech, Chicago

• Finding statistical evidence for predictability of Zinc futures returns from technical analysis and literature based prediction model

• Built a Linear Regression based predictability model for Zinc futures prices on LME using the historical data and built scripts in MATLAB to automate these processes


• Drummer for College rock band

• Scuba School International certified open water diver,

• Volunteer for NGO Nirmaan

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