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  • Lummezen Mondal, PhD, MSFM

    (773) 383 1158


    Results-oriented quantitative finance professional with more than ten years of work

    experience in the fifth largest accounting firm in US. One of the two key personnel who

    created the quantitative finance desk primarily for valuations of derivatives and structured

    finance securities within the firm. Completed PhD in Finance with particular expertise in

    Financial Modeling. Graduated MS in Financial Mathematics (MSFM - rank #3 in US) from

    University of Chicago in December 2016.

    Financial Modeling expertise include:

    - Programing Skills: R, Python - Bayesian model: Ridge, Lasso - Swaps, Swaptions, CDS

    C++, Matlab, SQL, SAS, VBA

    - Monte Carlo Simulation

    - Robust regression models:

    Hubert, Tukey, OLS

    - Multivariate Data: SVD,


    - Binomial/ Trinomial Model - HJM, Ho-Lee, Hull-White - Bloomberg, Quandl

    - Risk Models: CCR, CVA, DVA, - Black-Scholes, Blacks model - Volatility: Garch, Heston

    VAR, IRR, EL, LGD, PD - Options Risk: Delta, Gama - Model Validation


    Quantitative Finance Analyst (Summer Project) in Lincoln International LLC, Chicago,

    from 06/30/2016 09/30/2016:

    Worked closely with Credit Risk team to help build credit risk curves to compute market implied yields for CCC rated loan portfolio using Principal Component Analysis (PCA) and HJM framework; thereby generated customer confidence in the firms discount curves used for risky loan portfolio valuation purposes;

    Built valuation models for mortgage based securities (MBS) incorporating

    Prepayment risk and Make-Whole call provisions;

    Quantitative Finance Manager in McGladrey, LLP, Chicago, from 11/2005 11/2015:

    Worked closely with valuation partner to launch the Quantitative Finance Division within McGladreys Financial Advisory Services in 2005, for valuation of OTC equity and fixed income derivatives and mortgaged based structured finance securities thus saving millions of dollars every year spent on hiring external valuation firms for performing similar analyses;

    Generated new revenue stream by developing several models for valuation of complex over-the- counter (OTC) Derivatives which include:

    Warrant/ ESOP valuation model using Monte Carlo Simulation methodology

    incorporating: o Correlation with returns of comparable companies

    o Probability of down-round financing

    o Adjustment to exercise price based on market conditions

  • o Adjustment to conversion ratio from warrant to stock

    Binomial/ Trinomial model for valuation of stock options;

    Using Excel- VBA built a model to generate marks for a portfolio of ~3,000 plain

    vanilla interest rate swaps in six different currencies.

    Building the above models helped our firm to generate credibility with internal audit clients and external valuation clients resulting into creation of an entirely new line of revenue generated from quantitative finance analyses;

    Performed Model Risk Validation (based on SR 11-7 guidelines) of clients models prepared for derivatives valuation purposes so as to streamline audit functions during QE and FYE;

    Expert in using Bloomberg models to price Interest Rate Swaps, Swaptions, Cancellable (European, Bermudan, American) swaps, Variance swaps, Total Return swaps, Cross Currency swaps, Equity Basket Options, Caps and Floors, Options on Commodity Futures, Foreign Exchange Currency Forwards, Options of Foreign Exchange Currency Futures and Credit Default Swaps;

    Performed CVA, DVA adjustments to fixed income derivatives valuations to reflect counterparty credit risks (CCR) in the post-crisis era;

    Corroborated deep dive analysis on mortgage related structured fixed income securities like MBS, CMBS, CDO etc. which helped audit team to issue 10K filings for our audit clients specially during financial crisis in 2007-08 thus generating confidence in our external audit clients thereby helping in revenue generation for our Assurance practice;

    Performed variance analyses on derivatives valuations per FASB guidelines thereby helping audit partners to gain confidence in clients marks to be presented in their 10K filings;

    Performed Value At Risk (VAR) and hedge effectiveness analyses helping our audit clients to remain complaint with SEC and FASB guidelines under current regulatory environment;

    Trained junior employees to perform analyses of complex derivatives and improved realized margin for our Valuation/ Consulting practice;

    Regularly prepared detailed memo on complex derivatives analyses for top management with a focus to present the material in a simplistic manner so that the analyses are easily comprehensible for non-quantitative personnel;

    Performed rigorous statistical analyses on daily trading data from 1995-2013 for stocks traded on OTC-BB for research and publication on idiosyncratic behavior of bulletin board stocks thus contributing to the research on bid-ask spreads for securities from one of the least researched areas of capital markets.


    MS in Financial Mathematics (MSFM), University of Chicago (rank #4 in US)


    PhD in Quantitative Finance, Stuart Graduate Business School, Illinois Institute of

    Technology, Chicago [Scholarship recipient]

    Dissertation Title: Two-Stage Dynamic Hybrid Scoring model that is able to

    (i) distinguish between a financially weak and strong publicly traded firm and

  • (ii) predict the distance, measured in fiscal years, the firm with poor financial

    health is away from its bankruptcy.

    Made original contribution to the cutting-edge sector of Hybrid Scoring

    model for bankruptcy prediction of public companies;

    Dissertation thesis covers 100% of all public companies that bankrupted

    between 1995 and 2005, in addition to DJIA and DJTA constituents during

    this period;

    Generated hybrid scores for publicly traded companies from a combination of

    13 liquidity, profitability and solvency ratios and 4 market related ratios:

    probability of default, distance to default, credit spread and asset volatility computed from Merton model based on KMV framework;

    Applied Principal Component Analysis, Markowitz Multifactor model and

    optimization model based on Markowitzs Portfolio Selection Theory to the

    ten year time series of the selected ratios and generated Probability Scores

    to be assigned to each of the companies in our samples for each of the year;

    Probability Scores correctly categorized 100% of out-sample firms into

    financially weak and strong groups as measured by Receiver Operating

    Characteristics (ROC) and Area Under Curve (AUC) parameters;

    Based on Cumulative Accuracy Profile (CAP) results Probability Scores

    have correctly identified 89% - 100% of out-sample companies by the number

    of years to bankruptcy within the range of 1 year through 10 years to


    Outperformed Altman Z and Z model by 40 and 50 percentage points for

    each of the nine years (two through ten) to bankruptcy for all out-sample

    firms. During the period one year prior to bankruptcy, the results for all the

    models are comparable.

    MS in Applied Mathematica, Jadavpur University, India;

    BS in Mathematics, Jadavpur University, India.


    Co-authored Estimating the marketability discounts: a comparison between bid-ask spreads and Longstaffs Upper Bound, published in Journal of Applied Finance, Volume 23, No. 1, 2013;

    Authored A dynamic hybrid credit scoring model: a two-stage prediction of credit

    quality Illinois Institute of Technology 2008, 244 pages; 3338042 (Dissertation).


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