Mutli Asset & Derivatives / Quantitative Analysis / Statistics

Kenneth Lee

*** ****** ******, *** **** Pun, Hong Kong

+852-****-**** ***.***.****@*****.***

MULTI ASSETS & DERIVATIVES / QUANTITATIVE RESEARCH / STATISTICS & DATA SCIENCE Ambitious, detail-oriented Junior willing to leverage Statistics & Economics background with 2 years of Research, Programming, Data Analytics in Multi-Asset & Derivatives Market and Quantitative Risk experience into a Junior Quantitative Researcher. Suitable in fast-paced floors. Exposure to Fin Tech, Equity Warrants Market Making, Multi-Assets (Equity, Index, FX, Commodities, Rates), Derivatives and Structured Products pricing, order, post-trade flow execution in Asia. Solid Financial Engineering and Risk contexts along with Programming, Automation and Multi-Thread Programming experience using VBA, C++. Proficiency in Python, R, Matlab, SQL to operate Database Query Scripting, Statistical Computation, Time Series, Machine Learning, Optimization, High-Frequency Tick Data Analysis, Trading Strategy Back-Testing. CORE STRENGTHS & EXPERIENCES

* Strategy Back-Testing * Statistical Arbitrage * Financial Engineering * Multi-Asset & Derivatives * Market Making

* Solid Programming * Quantitative Analysis (Time Series / Machine Learning) * Economics * Team Oriented WORK EXPERIENCE

Nov 2015 – Aug 2016 Leonteq Securities – Cross Asset Structured Solutions Analyst Central, Hong Kong Covering Institutional Clients in Korea, Asset Management Clients in Singapore

• Executed 100 OTC Swaps & Options to generate approximately YTD 1.5 Mio USD Sales P&L

• Priced and quoted approximately 500 weekly OTC requests-for-quotes (RFQs) of exotic payoffs on multi-assets (including Rates, FX, Equity Index, Commodities, Credit and Hybrid)

• Liaised with Structuring & Trading to enhance pricing market competency, tracking pricing parameters (vol/barrier/skew shift) and analyze traded-away deals in terms of PV and Vega

• Promoted Index Sponsorship Services to Asset Management clients, and consulted appropriate assets (EQ, FX, Futures, Options) and execution orders (Stop-Limit, VWAP, TWAP)

• Elevated exotic variations of Multi-Asset Stepdown-Autocallables and Algo-Linked Products

• Tracked and covered daily global market & corporate events to identify trading ideas and signals

• Analyzed Stock, Index, Futures, ETF intra-day market data to seek pattern signals & volatility

• Cooperated with MO & Operations to set-up & capture post-trade P&L and manage life cycles

• Contributed to developing OTC Pricing Platforms specialized for the Korea Sales Team Apr 2015 – Sep 2015 Hyundai Securities – Quantitative Market Risk Analyst Seoul, Korea Covering Pricing & Validation, Quantitative Risk Measures (R, Matlab, VBA, C++, SQL)

• Simulated 500 daily asset path scenario generations to assess VaR, 1st / 2nd order Greeks. Negotiated appropriate risk limits to optimize capital requirements for each trading desk

• Generated Local Volatility surfaces, Skew, Correlations to validate Front Office Hedge Strategy

& Pricings, reflect correct Mark-to-Market P&L, and prevent loss of 15 Mio Trading P&L

• Commenced projects developing new strategies on multi-asset futures using Neural Networks

& Risk-Premia, cooperating with Equity Solution Trading Desk to generate YTD 1 Mio P&L INTERNSHIPS

Mar 2015 – Apr 2015 KR Futures – Global Macro Futures Night Trading Desk Intern Seoul, Korea Covering Global Macro Futures Prop Trading Execution Orders & Client Margin Accounts

• Executed orders for Prop-Trading Book Account and managed margin accounts for clients

• Researched Prop Trading ideas for in-house strategies and back-tested performance to validate Dec 2014 – Feb 2015 Nomura – IT Developer (Equity Warrants Trading Desk Intern) Seoul, Korea Covering Market-Making Equity Warrants Desk Issue/Report/Database Platform (VBA, XML)

• Developed back-testing, issuing, reporting, database platforms to enhance desk efficiency

• Researched global economic indicators to screen market risk factors and regime shifts Aug 2013 – Dec 2013 Gen Re – Actuarial Data Research Assistant Seoul, Korea Covering Risk Rates Data Research and Rates Development (VBA, SQL, SAS)

• Acquired and formatted risk rates data to insure new exotic risks in Life & Health insurances

• Implemented classification methods to identify contingent risk factors in policyholder big data EDUCATION

2005-2014 Yonsei University

• Master of Arts in Statistics (GPA: 3.89 / 4.5) – Thesis: Mortality Projection under Phase-Type Distributions Courses: Semi-parametric Regression, Linear Models, Statistical Computing, Statistical Learning Theory Dynamic Optimization Theory, Statistical Risk Management, Nonparametrics, Credibility Theory (Loss Models)

• Bachelor of Arts in Applied Statistics (Major GPA : 3.65 / 4.5)

• Bachelor of Arts in Economics (Major GPA : 3.7 / 4.5) Undertook courses predominantly in Economics, Statistics, Mathematics, Financial Engineering & Computing 2012-2014 Research Assistant in Actuarial & Financial Engineering Lab / Teaching Assistant in Introduction to Statistics PROJECTS

May 2015 – Aug 2015 Estimation and Comparison between Volatility Models – KOFIA Seminar Project (VBA, R, Matlab)

• Derived Implied Volatilities to examine volatility skew structure from Market Option Prices

• Implemented Stochastic Volatility and Local Volatility models to conduct comparison analysis Dec 2013 – May 2014 Cointegration Analysis on Cross Asset Movements – Research Lab Project (Python, R, Matlab, Linux Terminals)

• Manipulated data across 5 linear cross-asset futures combinations to seek Cointegration relationship SKILLS • Validated Cointegration relationship using Augmented Dickey-Fuller Test and Johansen Test Computer Skills: Office Suite / Excel VBA, C++ / Access, SQL / R, Python, Matlab / Bloomberg, Reuters / OS: (Windows / Linux) English – Native (U.S. Citizen / SSN Holder, Work Visa valid until 2017 July in Hong Kong, Born and Educated until 12 years in U.S.) Korean – Native (Lived, educated and worked in Korea from 12 years old until last year 2015: 2 Years of Work Experience in Korea) Type 1 & Type 4 RA – Passed HKSI Paper 1; enrolled in Hong Kong SFC for Type 1 & Type 4 Regulated Activities (CE: BGW789) Exam P (Probability) – Preliminary Probability Exam of Society of Actuary / Scheduled to take next CFA Lv.1 / SOA FM & SOA MFE Exam Certified Financial Risk Manager – Quantitative Risk Manager Certificate from Korea Financial Investment Association (Cert No: 15-010461) Kenneth Lee

Theoretical Status

Relevant Course Works

Graduate Statistics

[Statistical Learning Theory - (mainly used R, some Python)] This course aimed various statistical learning methods with emphasis on both conceptual and computational aspects. I was able to gain exposure on the below topics:

- Regularized Regression and Variable Selection, Nonparametric Function Estimation, Linear Classification Methods, Boosting & Bagging, Random Forests, Support Vector Machines

[Semi-parametric Regression – (mainly used R, some Fortran)] The primary purpose of this course was to introduce semiparametric regression, which has been recently developed by formulating the nonparametric regression as a simple extension of parametric regression. This course was oriented in problem solving using R. I was able to gain exposure on the below topics:

- Parametric Additive Models, Non-Linear Models, Non-parametric (Automatic) Spline Methods, Penalized Regression Splines, Linear Mixed Models, Semi-parametric Additive Models

[Statistical Computing - (mainly used R, some C In this course, I was able to cover some useful computing methods that used in modern applied statistics. I was able to gain exposure on the below topics:

- Numerical Integration, Monte Carlo Simulation, Variance Reduction Techniques, Metropolis Hasting Algorithm, Gibbs Sampling, EM Algorithm, Monte Carlo Markov Chain

[Statistical Risk Management - (mainly used R and Matlab)] In this course various mathematical and statistical tools used in measuring and managing financial risk management were covered. In particular, the following topics were introduced and covered:

- Bond Pricing, Types of Duration, Convexity, Risk measures (VaR and Tail VaR), Credit Risk, Credit Metrics, Copulas, Extreme Value Theory, GEV Distributions, Point Processes

[Credibility Theory (Loss Models) – (mainly used R)] In this course parametric and nonparametric methods of estimation for the distribution of the severity and frequency of insurance losses, along with properties of various parametric severity and frequency models with policy modifications and compound distribution of aggregate claims limited fluctuation and greatest accuracy credibility theory were introduced, with emphasis on the latter. I was able to gain exposure on the below topics:

- Insurance Models, MLE & Delta Methods, Credibility, Limited Fluctuation & Greatest Accuracy Credibility Theory, Bhulmann-Straub Model, Empirical Bayesian methods

[Nonparametrics – (mainly used R, some Matlab)]

This course worked to minimize parametric assumption and covered theoretical, applied, and implementation issues as below:

- Contingency Tables, Order Statistics, Goodness of Fit, Rank Statistics, Categorical Data, Estimating Distribution Functions, Nonparametric density and regression, Bootstrap & EM Algorithm

[Linear Models]

This was a course in linear models for continuous responses focusing on theories. In particular, the following topics were introduced and covered:

- Matrix Theory, Multivariate-Normal Distribution, Multivariate quadratic forms, Estibability, Reparametrization, Linear Regression and Analysis of Variance, Estimation Theory, Projection, Weighted Least Squares, Multivariate Tests of Linear Hypothesis, Confidence Regions, etc. Under

graduate

Applied

Statistics

[Stochastic Processes]

This course covered basics of Markov chain theory, and other stochastic processes. Topics: Random Walk, Hidden Markov Chains, Poisson Processes, Birth & Death Processes, Optimum Stopping Time, Long-Run behaviour of Markov Chains, Brownian Motions

[Bayesian Statistics – (mainly used R and BUGS)]

This course introduced theoretical concepts and problem solving skills in Bayesian Statistics. Topics: Bayesian Probability, Bayes Rules, Bayesian Statistics Theory, Simulation, Metropolis- Hasting Algorithm, Gibbs Sampling, Hierarchical Prior Distributions, Bayesian Inference

[Regression Analysis – (mainly used R, some SAS & Minitab)] This course explored basic theoretical developments underlying regression analyses. Topics: Linear Regression models, Multiple Regression models, Model Diagnostics and Variable Selections, Qualitative Predictor Variables, Principle Component Analysis, Ridge Regression

[Computer Programming (exclusively used R)]

This course explored basic programming concepts, data analysis and visualization using R. Topics: Data Structures, Data I/O Operations, Object-Oriented Programming in R, Statistical Tests

[Financial Engineering (1)(2) (mainly used VBA, some C This course covered Derivatives Pricing Theory in # (1) and handled implementations on # (2) course Topics: Brownian Motion, Ito’s Lemma, Black-Scholes PDE Equation, CRR/JR/EQ Binomial Models, BDT Trees, HW Model, Barrier Options (and path-dependent options), Exotic Options, Greeks Statistical/Mathematical Analytic Software Programming Status R

(in

Windows

& Linux)

5 years

[Hyundai Securities]

Implemented Long/Short Equity Models with Multi-Asset Futures intra-day prices based on Risk-Parity Strategies and Trend Detection techniques referring <Bruder & Roncalli

(2013)>, <Maillard, Roncalli, and Teiletche (2010)>, <Paul D. McNelis - Neural Networks in Finance, Gaining Predictive Edge in the Market (2005)>

- To obtain optimal weights within models, solved matrix optimization problems using non-linear optimization libraries and functions (optim, nlm, etc.,) and validated results satisfying constraints

- Implemented single hidden layer neural-network models using neural network functions (nnet, predict.nnet, etc.,) to fit into futures market intra-day data and minimize mean square errors

- Connected R and internal Excel VBA Execution Trading Platform to automate trading process

[Graduate Actuarial Research Lab]

Implemented actuarial mortality models such as Lee-Carter Model, Phase-type Law of Mortality, Cairns-Blake-Dowd Model and Spline Model (densely focused on optimization and prediction methods) referring <Ermanno Pitacco, et. Al (2009) - Modelling Longevity Dynamics for Pensions and Annuity Business>, <Lin & Liu (2007) - Markov Aging Process and Phase-type Law of Mortality>

- Conducted Principle Component Analysis (following Goods (1969) paper) to conduct minimization of mean square errors between Belgian and Swedish death rates (181*-****-** year cohort rates) and model estimates and implemented Lee-Carter Model, CBD Model, Spline Model

- Conducted re-production and implemented Phase-type distributions with specified parameters and analysed trends of model parameters to develop an internal forecasting method

[Seminar Courses]

- Quantitative Trading (Graduate Seminar)

Searched alphas through Stock & Forex market tick data and implemented back-testing: used RODBC, RMySQL, dplyr, quantmod, quantstrat, highfrequency, ggplot2, R-GGobi libraries Matlab

(in

Windows)

4 years

[Hyundai Securities]

Implemented Long/Short Equity Models with Multi-Asset Futures intra-day prices based on Risk-Parity Strategies and Trend Detection techniques referring <Bruder & Roncalli

(2013)>, <Maillard, Roncalli, and Teiletche (2010)>, <Paul D. McNelis - Neural Networks in Finance, Gaining Predictive Edge in the Market (2005)>

- To obtain optimal weights within models, solved matrix optimization problems using non-linear optimization functions (fminsearch, fmincon, etc.,) and validated results satisfying constraints

- Implemented single hidden layer neural-network models using neural network functions from McNelis (2005) text to fit into futures market intra-day data and minimize mean square errors

- Connected Matlab and Excel VBA Execution Trading Platform to automate trading processes

[Graduate Actuarial/Financial Engineering Research Lab] Implemented actuarial and financial engineering research and projects below:

<Managing life contingency risk using the Phase-type Mortality model>

<Mortality Projection under the Phase-type Law of Mortality> - Master Thesis

- Conducted re-production and implemented Phase-type distributions with specified parameters and analysed trends of model parameters to develop an internal forecasting method

- Using Closed Form Solutions of the Phase-type Law of Mortality, supported deriving variations of closed forms (Premiums and Reserves of Annuities & Insurances) as well as implementing to compute correlations between Premiums and Reserves of Annuities and Insurances

<Option Pricing and Risk Management using Phase-type Models>

- Scripted Option Pricing Methods and Formulas for underlyings following Phase-Type distributions and conducted comparison analysis with BS and alternative Option Pricing Formulas

- Generated Greeks, VaR, CTE, and other risk measures based on derived Phase-Type formulas

[Seminar & Academic Courses]

- Quantitative Trading (Graduate Seminar)

Searched alphas through Stock & Forex market data and implemented back-testing referring <Ernest P. Chan (2009) - Quantitative Trading>, <Ernest P. Chan (2013) - Algorithm Trading>, <Perry J. Kaufman (2011) – Alpha Trading>

- Advanced Calculus (Undergraduate)

Scripted differential equations & numerical integrations for non-closed form solutions Python 2.7

(in Linux)

1 year

[Statistical Learning Theory – Graduate Course Project] Plotted and analysed stock & forex market daily price data to apply machine learning and pattern recognition techniques using numpy, scipy, random, matplotlib, time libraries HTML & Network Language

XML 6 months

[Nomura]

Implemented Excel-based platforms automatically drafting XML language scripts to automate Issue-preparing process through webpages

Computer Languages (with IDE)

Visual

Basic in

Excel

4 years

[Leonteq Securities]

* Priced Structured Products and OTC Options traded in Asia as below:

- Index/Stock/Commodity/FX Step Down & Up, Low Strike Autocallables

- Index/Stock/Commodity/FX Exotic OTC Options (M-Shape, Double Barrier, Chinese Fan)

- Index/Stock/Commodity/FX Linked KO Notes, Accumulators, and Fixed Coupon Notes

- Index/Stock/Commodity/FX Linked Airbag, Bonus, Outperformance Participation Notes

* Contributed to development of OTC Pricer specialiazed for Korea Sales Team

* Conducted Analytics on Structured Notes Issuance Data in Korea Market to build internal structuring and sales strategies for each institutional clients in Korea

* Troubleshooted Leonteq Platforms built-in Excel to conduct optimization run tests

[Hyundai Securities]

* Validated and improved pricing modules (with dll (dynamic linked libraries) for Structured Notes traded in Korea

- Index/Stock/Commodity/FX Step Down & Up Autocallables

- Index/Stock/Commodity/FX Twin Win Autocallables

- Rates Reverse Convertibles, Dual Range Accruals / Rates & Credit Hybrid Dual Range Accruals

[Financial Engineering Seminar – Korea Financial Investment Association]

* Estimated Implied Volatilities and Local Volatility Surfaces from given Market Prices

* Analyzed the Assumptions between BS Option Pricing model and alternative volatility models such as GARCH models, stochastic volatility model, local volatility model

[Nomura]

Developed automated platforms for Back-Testing, Issue-Preparing, Reporting Equity Linked Warrants Trading Desk

- Verified trading results and back-tested issued warrants through developed platforms

- Generated issue-preparing reports such as Registration, Securities Issue Report, Investor Report, etc., in XML language to automatically report to the Korea Financial Supervisory

[Graduate Financial Engineering Research Lab]

Implemented Options and Interest Rate Derivatives in Financial Engineering Seminar

- Binomial & Trinomial trees, Finite Difference methods (Implicit, Explicit, Crank-Nicolson), Monte-Carlo Simulation with Antithetic Variates, Control Variates, Stochastic & Local Volatilities

[Gen Re]

Classified and grouped cancer and critical illness rate data

- Scripted/Validated classification method logics to apply on policyholder big data sets C++

(in Visual

Studios,

Eclipse, and

vim in

Linux

Terminals)

2 years

[Hyundai Securities]

Validated and improved Front Office and Risk Office pricing modules scripted in C++ for Structured Products traded in Korea

- Index/Stock/Commodity/FX Step Down & Up Autocallables

- Index/Stock/Commodity/FX Twin Win Autocallables

- Rates Dual Range Accrual / Rates & Credit Hybrid Dual Range Accrual

[Graduate Financial Engineering Research Lab]

Implemented Options and Interest Rate Derivatives in Financial Engineering Seminar

- Conducted Option Pricing methods, Finite Difference methods (Implicit, Explicit, Crank- Nicolson), Monte-Carlo Simulation based on Object-Oriented Class Approaches

[Dynamic Optimization Theory – Graduate Course Project] Implemented finite difference methods and dynamic linear programming methods through operational research, network models and business examples Java in

Eclipse

3 months [Self Study] - Implemented Operators, Input/Output, Basic OO-based Option Pricing Text Editor Language

TEX

(Latex)

2 years

[Graduate Actuarial/Financial Engineering Research Lab] Scripted and compiled pdfs with graphs, mathematical operators, tables, etc., with Latex Database Frameworks

MS Access

(with VBA)

2 years

[Nomura]

Scripted Modules to automatically merge and manage issued Equity Linked Warrants data in Database Tables concatenating platforms between MS Access and Excel VBA

[Gen Re]

Developed, updated and compiled rates for risks included in several Critical Illness and Cancer Products through query designs and database tables SQL

(MS-SQL,

Oracle)

2 years

[Hyundai Securities]

Drafted Structured Queries to validate parameters (risk- free interest rate, dividends, volatility surface data, etc.) for Structured Products and Stress Test Scenario inputs

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