World Leading Hi-Tech Research Defining World Leading Computational Quantitative Risk Management Practices™

Dr. Yogesh Malhotra

Chief Research Scientist

Computational Quantitative Finance-IT-Risk Analytics,

Computational Quantitative Analytics, Quantitative Modeling, Financial Risk Management, Cybersecurity Risk Management,

PhD,MSQF,MSNCS,MSCS,MSAcc,MBAEco, SAS,CEH,CISSP,CISA,CPA Education

Who's Who in America^{®},

Who's Who in the World^{®},

Who's Who in Finance & Industry^{®},^{ }Who's Who in Science & Engineering^{®}^{}

Direct E-mail - LinkedInGMail: dr.yogesh.malhotra

Phone: 646-770-7993

Portfolio of Global CxO Research & Practice Leadership

Big Banks, Trillion $ Funds, Trillion $ Practices, Wall Street CxOs, Silicon Valley CxOs,

$100 Billion IT Firms, National Science Foundation, UN, US & World Governments.

2015 Princeton Quant Trading Conference Presentation on Future of Finance: Cyber Finance.

2015: 24 SSRN Top-10 Paper Awards: Quantitative Finance, Econometrics, &, Risk Modeling

Computational Quantitative Analytics Risk Management Research Leading Industry Leaders.

AACSB Reports Impact of Research among Finance Nobel Laureates such as Black-Scholes.

Global Research Impact recognized among IT and Finance-Economics Nobel laureates in business press, industry surveys & scientific impact studies.

Digital & Cyber Risk Analytics Tech Ventures leading Computational Quantitative Analytics, Machine Learning, Data Science, Quantitative Finance, & Cyber Risk Management Practices.Global High-Impact Thought Leadership spanning Silicon Valley to Seoul and all the continents in between with global impact across most nations of the world.

Worldwide Digital Transformation Editorial Coverage & Interviews in Wall Street Journal, New York Times, Fortune, Fast Company, Forbes, Business Week, CIO, CIO Insight, Computerworld, Information Week, etc.

Projects Goldman Sachs JP Morgan Wall Street Hedge Funds Princeton Quant Presentation Model Risk Management Publications Tech Ventures Global Impact

Research Impact Education Future of Finance Bayesian vs. VaR Markov Chain Monte Carlo Models Cyber Finance Future of Risk Cyber Risk Bitcoin Protocol

Cyber Risk Insurance Models Risk Models Beyond VaR Wireless Mobile Trust Models Pen Testing Frameworks Bitcoin Cryptanalytics NFS Cryptanalytics AlgorithmsSummary - Profile - Recent Projects - Research Impact - Projects Portfolio - Expertise & Interests - Education - Publications - Tech Ventures - Google Scholar - SSRN

SUMMARYDr. Yogesh Malhotra is the Founding Chairman and Chief Scientist at the New York based LLC focused on Computational Quantitative Analytics, Financial Risk Management, and, Cybersecurity Risk Management internationally recognized for leading global risk management practices. He has over two decades of influential leadership experience in global banking and financial systems, quantitative modeling, risk management, and, information technology including leadership roles with top Wall Street investment banks with $1 Trillion AUM such as JP Morgan.

He has served as invited adviser to US and World Governments, UN, NSF, and $100 Billion dollar global corporations across USA, N. America, Asia, and, Europe and taught and lectured as invited Executive Education faculty at Carnegie Mellon and Kellogg. He has founded award-winning risk analytics tech ventures whose millions of users have included patrons and clients such as Google, Goldman Sachs, Harvard, Intel, McKinsey, Microsoft, MIT, NASA, Ogilvy, Princeton, Silicon Valley VCs & CEOs, US Air Force, US Army, and, US Navy. Prior to that, he was a currency arbitrage and global financial systems software engineer for Big Banks such as Bank of America and Banque Indo-Suez and Big IT firms across USA, Hong Kong and India.

His award-winning post-doctoral Quantitative Finance research pioneering the global Cyber Finance practice and risk analytics modeling foundation for the global Cyber Insurance industry was invited for presentation at the 2015 Princeton Quant Trading Conference at the Princeton University. In 2008, the AACSB International recognized his research among 'exemplars' of 'considerable impact on actual practice' such as Nobel laureate works of Black-Scholes, Harry Markowitz, and, William Sharpe. His research on systemic risk management and quantitative models published in peer-reviewed journals is ranked by scientific impact studies among others such as economist Joseph Schumpeter and Nobel laureate Herbert Simon.

EXECUTIVE PROFILE•

Invited Quant Research Presentation,Princeton Quant Trading Conference,Princeton University, April 4, 2015.

- Conference Sponsors: Princeton University Bendheim Center & ORFE, Citadel, KCG Holdings.

•Quantitative Finance & Quantitative Risk Modeling Research:24 SSRN Top-10 Paper rankings, Jan-May, 2015.

Advanced Risk Modeling Tools & Statistical Techniques, Advanced Econometrics & Time Series Models, Market Risk, Credit Risk, Liquidity Risk, Capital Markets, Derivatives, Portfolio Construction & Optimization Models, Volatility Models, VaR, ARCH, GARCH, Multifactor Pricing Models, Bayesian Inference, Markov Chain Monte Carlo Models, Cyber Risk.•

Wall Street Investment Banks Project Leaderships of Risk Modeling & Analysis for Banks with $1 Trillion AUM:

JP Morgan Private BankMulti-Asset Portfolio Fund of Funds with $500-600 Billion AUM, Midtown Manhattan.Mentor: JP Morgan Global Head of Quantitative Research & Analytics and US Head of Portfolio ConstructionGoldman Sachs Alumnus' Asset Management Firmwith $400-500 Billion AUM, Midtown Manhattan.• Project Leader, JP Morgan Private Bank Portfolio Construction & Optimization Liquidity Assessment Framework, reporting to and guiding Global Head of Quantitative Research & Analytics, US Head of Portfolio Construction and team.

• Project Leader, Goldman Sachs alumnus’ asset management firm, High Frequency Econometric Modeling of Co-integrated Time Series and Liquidity Microstructure Modeling reporting to and guiding Sr. VP/Portfolio Manager and team.

• Equity Portfolio & Risk Management Strategist, developed Financial Risk Analytics with 200 market data sources, did 3,500 equity trades in double-digit million US$ of 250 companies using technical, fundamental, structural analysis.• Prior Banking & Finance Analytical & Modeling Project Leaderships for Bank of America, Las Vegas; Crédit Agricole CIB, Hong Kong Govt. Treasury Management; Wells Fargo, and, Big-3 IT for Global Financial Systems of worldwide banks.

• Founder, Risk Analytics Ventures with clients & patrons such as Goldman Sachs, Google, Harvard, IBM, Intel, Microsoft, MIT, Ogilvy, Stanford, Xerox. Professional Practice Network of 130,000+ Worldwide Registered Members and Millions of Worldwide Users ranked among Top-10 ‘Social Networks’. Also, founded Top-ranked Web Site (

Computerworld), and, Top-3 Search Engine (Carnegie Mellon Industry.Net National Awards) while working on PhD in mid-1990s.• Carnegie Mellon & Kellogg Executive Education faculty; Quantitative Methods Professor at Syracuse University; Keynote Speaker for UN Global Assets Modeling Expert Panel & World Governments; NSF Computer Scientists Expert Panels.

• 20-year PhD & Post-PhD experience in Statistics, Probability, Econometrics, Quantitative Finance, Operations Research, Computer Science, Cryptography, Encryption models & algorithms such as Regressions, Structural Equations, VaR, ES, EVT, ARCH/GARCH, Machine Learning, Data Mining, Bayesian Inference, Markov Chain Monte Carlo Models.

• 20-year PhD & Post-PhD experience in data analysis tools, data sources, analysis queries and procedures applied using SPSS, SAS, MATLAB, AMOS, PLS, LISREL, C++, MS-Excel, VBA, Bloomberg, etc.; 100+ Quantitative Statistical & Structural Model Validation Reviews: Top Academic Empirical Journals:Best Reviewer Award, Academy of Management.

• 17-year Post-PhD Statistical Modeling & Analysis Research: Research advancing execution of Model Risk Management (see, e.g., US Fed & OCC SR11-7 & OCC2011-12): named among 'exemplars' of 'considerable impact on actual practice' such as Finance Nobel laureates by the AACSB International Impact of Research Report. Ranked & recognized in Top Business & Economics researchers & Top Information Science & Finance-Economics researchers in business press, industry surveys & scientific impact studies.• Led Team of 200 PhDs including Senior Professors from Top Business Schools to publish High Impact Research guiding worldwide practices.

• Media Interviews & Coverage: Wall Street Journal, New York Times, Fortune, Forbes, CIO, Fast Company, Inc., etc.

• Top-10 PhD Computational Quantitative Analytics Computer Scientist-Econometrician-Chartered Engineer: Double Doctorate in Statistics & IT, Top-14 MS Quantitative Finance (Applied Math), MS Computer Science/Computational Finance, MS Network & Computer Security/Quantitative Finance, MBA Quantitative Economics, MS Accountancy, BE Mechanical Engg., UC Berkeley MFE & Kellogg PRMIA Risk Management Executive Education, SAS Certified, MATLAB Certified, Unix and C Certified.

• Selected for inclusion among worldwide leaders and achievers from both the United States and around the world in:

Marquis Who's Who in America

^{®}

Marquis Who's Who in the World^{®}

Marquis Who's Who in Finance & Industry^{®}

Marquis Who's Who in Science & Engineering^{®}.

RECENT PROJECTS

JP Morgan Private Bank, Goldman Sachs Alumnus' Asset Manager & Venture Capital

Econometric Modeling, Quantitative Finance, Quantitative Risk Modeling

, SSRN Top-10 Papers: 24 Top-10 Rankings in Econometrics & Risk ModelingJan-May2015.

2015 Princeton Quant Trading Conference: Invited Research Presentation, April 2015.

Risk Modeling for Managing Uncertainty in an Increasingly Non-Deterministic Cyber World

Future of Finance beyond 'Flash Boys': Cyber Finance?

- Conference Sponsors: Princeton University Bendheim Center & ORFE, Citadel, KCG Holdings, Apr 4, 2015.

Contents: Model Risk Management, Risk Management, Risk Modeling, Quantitative Finance, Cyber Finance, Virtual Finance, Cyber Insurance Models, Cyber Risk Insurance, Uncertainty Modeling, Uncertainty Management, Knightian Uncertainty, Bayesian Inference, Markov Chain Monte Carlo Models, Quantum Computing, Value at Risk, VaR, T-VaR, Conditional Tail Expectation, ARCH, GARCH, Conditional VaR, Cornish-Fisher Approximation, Cyber-Finance-Trust™ Framework, Expected Shortfall, Expected Tail Loss, Extreme Value Theory, FAST, FIX, Flash Boys, Gibbs Sampling, Metropolis-Hastings Algorithm, HFT, High Frequency Trading, Crypto Currencies, Bitcoin, Model Risks, Power Laws, Quantitative Analytics, Cryptography, Network Protocols, Cryptology, Encryption Algorithms, Cryptanalysis Algorithms.

Wall Street Investment Banks & Venture Capital Projects on Quantitative Finance & Risk Modeling

Technologies & Frameworks Applied

Quantitative Finance, Quantitative Analytics, Econometric Modeling, Data Science, Market Risk, Credit Risk, Liquidity Risk, Financial Modeling, Risk Management, Stress Testing, Portfolio Optimization, Derivatives, SAS, SQL, MATLAB, C++, Microsoft Excel, VBA, R, Python, Bloomberg, Financial Risk, Model Risk, Portfolio Management, Hedge Funds, Financial Econometrics, Algorithms, Machine Learning, Predictive Analytics, Statistical Modeling, Data Modeling, Software Engineering, Statistics, Interest Rate Derivatives, Fixed Income, Equities, Trading Strategies, MS Access, Stochastic Modeling, Market Microstructure, Investment Management, Asset Liability Management, Data Mining, Structural Equation Modeling, Quantitative Models, Operations Research, Computer Science, Financial Accounting, Financial Statement Auditing,Optimization.

Computational Quantitative Finance & Risk Modeling, Advanced Financial EconometricsEconomic Capital, Capital Adequacy, Basel/US Federal Reserve/OCC Frameworks & Regulations, Portfolio Risk, Liquidity Risk, Credit Risk, Market Risk, Econometric Analysis, Market Microstructure, Interest Rate Derivatives, Stochastic Volatility, Fixed Income, Equity, Derivatives (Options, Futures, Forwards, Swaps, Swaptions)

Credit Risk Models

Credit Default Swaps, Default Probabilities, Gaussian Copula, Nth to Default Swaps, Simulations, Large Portfolio Approximation, CreditMetrics, KMV, VaR, Expected Default Frequency (EDF), Counterparty Risk, Credit Valuation Adjustment (CVA), Stress Testing, Basel II/III, Worst Case Default Rate (WCDR), Exposure at Default (EAD), Loss Given Default (LGD), Probability of Default (PD), Risk Weighted Assets (RWA)

Market Risk Models

Volatility Modeling, GARCH/Extensions, MLE, Variance/Correlation Models, Portfolio VaR, QMLE, Non-Normality, Cornish-Fisher, Extreme Value Theory (EVT), Expected Shortfall (ES), Coherent/Spectral Risk Measures, Weighted/Filtered/Historical Simulation, Monte Carlo, Backtesting VaRs/ES, Stress Testing, Basel II/III

Interest Rate Derivatives Models

Simulations, Analytic Expectation, Tree Models, Calibrations; Continuous Time, CIR,Vasicek, Merton, Hull-White, BDT, & HJM Models; Bond Options, Treasuries, Coupon Bonds, Caplets, Floorlets, Swap Contracts, Bond Risk Premia, Yield Curve, Markov Regime Switching Models

Equity PortfolioModelsDerivatives, Mean-Variance Portfolios, CAPM, Passive/Active Portfolio Performance, Multi-Factor Models, Cross-Sectional Returns, Asset Allocation, Risky/Risk-Free Portfolios, Diversification, Risk Pooling, CAPM, Anomalies, Dividend Discount/Growth Models

Fixed Income PortfolioModelsBond Valuations, Derivatives, Yields, Term Structure, Credit Spread, Credit Risky Bonds, Interest Rate Risk, Portfolio Performance, Passive/Active/Liability Funding, Hedging, Swaps, Forwards, Futures, ABS, MBS.

JP Morgan Private Bank $500-$600 Billion Multi-Asset Class Portfolio Construction & Optimization Leadership

Portfolio Construction & OptimizationFramework Development for Liquidity Assessment

JP Morgan (JPM) Hands-On Team Leadership Projects, Midtown Manhattan, New York

JP Morgan Portfolio Construction, Optimization & Stress Testing Leader

17-Asset Portfolio Liquidity Assessment & Stress Testing Research & Analysis

Technical Framework & Project Management Foundation:

Exhaustive Review of Recent 25-Years of Liquidity Measurement Research in Research, Policy, and Practice:

Technical Liquidity Risk Models, Methods, & Measures Research: ~5,000 documents ~ 60,000 pages

Research Presentations: Weekly: 225 slides, Final Executive Summary Overview: 5 slides.

MS-Excel/VBA/MATLAB Models for 17-Asset Portfolio Liquidity Assessment & Stress Testing

~ 250 MS-Excel /VBA Linked Worksheets within Aggregate Porfolio and Specific Asset Class Workbooks.

MATLAB Code and Execution Outputs for Stress Testing Portfolio of 17 Asset Classes: 74-pages.Portfolio Assets Modeled: 17 Asset Classes:

JP Morgan Portfolio Liquidity Assessment Framework Development Leader

Hedge Funds (HF), Alternative Investments, Equities, Commodities, Fixed Income, Bonds, Currencies:

Developed Large Equity

Developed Small Equity

Emerging Equity

Unlisted Equity

Various Commodities

Government BondsInvestment Grade Bonds

Inflation-Linked Bonds

High Yield Corporate Bonds

Emerging Market Hard Currency Bonds

Emerging Market Local Currency Bonds

Major Currencies

Statistical Arbitrage Hedge Fund

Equity Hedge Hedge Fund

Merger Arbitrage Hedge Fund

Macro Hedge Fund

Relative Value Hedge FundAsset Pricing, Risk Management, Stress Testing, Liquidity Risk, Market Risk, Credit Risk, ALM Risk, Portfolio Risk,

Investment Risk, Non-Normality, Non-Linearity.

Mentor: JPM Top-4 Leadership ED in Global Financial Crisis Management, Harvard Case.

Led quantitative portfolio liquidity modeling for multiple financial asset classes.

Led literature review of all liquidity risk models, methods, and measures.

Led project management & scheduling and delivering high quality results on time.

Led interpretations of all outcomes & findings to ED team of Quants, CIO, MDs, PMs..

Assets: alternatives, HF, equities, commodities, fixed income, bonds, currencies.

Analyzed market risk, credit risk, ALM risk, portfolio risk, investment risk.

Led modeling and stress-testing for all asset classes and composite portfolio.

Led validation of all liquidity and liquidity risk models and measures.

Led verification of model performance, limiting behaviors, responses to stress.

Led modeling of pricing & risk measurement with specific focus on liquidity.

Led evaluation of third-party models, data, software for diverse asset classes.

Led inventorying of model assumptions and assessment of model risks for all assets.

Modeled historical simulation, parametric & modified VaR, expected shortfall.

Modeled and analyzed multi-asset volatility, variances & correlations, GARCH, MLE.

Modeled VaR, QMLE, non-normality, Cornish-Fisher, EVT stochastic models for assets.

Modeled and analyzed liquidity risk models for all assets and portfolio optimization.

Identified & defined benchmark indices & data sources for all asset classes.

Assessed soundness of liquidity & liquidity risk models for assets & portfolio.

Guidance to JP Morgan Managing Directors/Executive Directors/Portfolio ManagersAxioms of Coherency and Convexity of Risk Measures

Exponential and Power Utility Functions for Spectral Risk Measures

Why Gaussian Risk Measures Fail and Where Regulation is Headed Next

Liquidity Measure for Illiquid Assets Solves Material Error in Liquidity Measures

Measuring Liquidity As Shadow Cost For Hedge Fund Indexes

Structuring and Pricing of Liquidity Options Hedge Funds for Price Discovery

Devising and Testing Liquidity Measures for Spreads of CDS Contracts

Liquifiability Index as What You May See in Basel Next

Modeling Measuring and Testing Liquidity Risk Across All Asset Classes

Goldman Sachs Alumnus' $400 Billion Asset Management Firm

Hedge Fund Large Scale Data High Frequency Econometric Modeling Project Leadership

High Frequency Econometric Modeling of Market Microstructure Liquidity & Price Impact

Hedge Fund Performance Analysis of 400 Trading Strategies for Alpha and Risk

Goldman Sachs Alumnus' Firm Hands-On Team Leadership Projects, Midtown Manhattan, New YorkWall Street SVP Hedge Fund Manager with Top Wall Street Investment Banks:

Mentor:

Harvard Computer Scientist & Mathematician Alumnus Wall Street Hedge Fund SVP/PM.

Goldman Sachs Alumnus' $400 Billion+ Asset Management Firm

Firm: Top Wall Street Investment Bank launched by a Goldman Sachs alumnus with $400 billion to $500 billion AUM at the time of the project.

ofProject Management and Technical Team Leadership

SAS High Frequency Econometric ModelingMarket Microstructure of Liquidity

High Frequency Econometrics Models of Trade Price Impact & Market Microstructure.

Researched Co-Integrated Time Series for Ultra-High Frequency Tick-and-Quote (TAQ) Data.

Replicated /Analyzed Large Scale Data HF Econometrics Models of Market Microstructure.

Taught VARMAX Models of Co-Integrated Time Series for High Frequency Econometrics.

Analysis of 400 SSA Quarterly Scan Trading Strategies for Alpha and Hedging

Hedge Fund Performance Analysis Quantitative Finance & Quantitative Risk Modeling Research

Analyzed 400 State Street Associates Quarterly Scan Alpha Trading Strategies.

Critical Review of State Street Associates Quarterly Scan Trading Strategies.

Analysis: Why Existing `Alpha´ Research Is Insufficient for Profitable Hedge Fund Asset Management.

Quantitative Finance Model Risk Management for Systemic Risks and Tail Risks:

Model Risk Management using VaR, Bayesian Inference, Markov Chain Monte Carlo Models

Advanced Risk Modeling Statistical Techniques, Advanced Econometrics & Time Series Models, Bayesian Inference, Markov Chain Monte Carlo Models, Capital Markets, Derivatives, Portfolio Construction & Optimization Models, Volatility Models, VaR, ARCH, GARCH, Multifactor Pricing Models, Market Risk, Credit Risk, Liquidity Risk, Cyber Risk Insurance.Advancing on Wall Street Investment Banks Risk Management, Risk Analytics & Risk Modeling practices leaderships, with research advancing execution of Model Risk Management (see, e.g., US Fed & OCC SR11-7 & OCC2011-12), recognized as "exemplar" of "considerable impact on actual practice" in the AACSB International Impact of Research Report.

Model Risk Management for Quantitative Finance, Cyber Risk Insurance, & Cyber Finance

Advisors: Distinguished Computer Scientists, Mathematicians, &, Physicists, Air Force Research Lab, New York State Cyber Research Institute, SUNY.:

Advancing on project leaderships with Wall Street investment banks such as JP Morgan, peer-reviewed post-doctoral research invited for presentation at the Princeton University applied innovative and scientific quantitative analytical approaches to advance Quantitative Finance Model Risk Management practices. Resulting conclusions and recommendations documented in the post-doctoral research thesis developed the foundation for defining statistically appropriate quantitative models for risk management of cyber risk insurance modeling risk of financial loss assessments thus averting impending nationwide cyber risk insurance industry disaster based upon the use of prior inappropriate risk of financial loss assessment models mirroring similar quantitative modeling problems underlying the Great Global Financial Crisis of 2008-2009.

To avert the impending national Cyber risk and Cyber-insurance disaster based upon large-scale commercial reliance upon quantitative models with inherent model risks, tail risks, and systemic risks in current form

Developed the first known Cyber-Finance-Trust™ framework for Cyber insurance modeling to analyze how financial risk entangled with Cyber risk further exacerbates the systemic, interdependent, and correlated character of Cyber risks.

Developed the first known model risk management framework for Cyber insurance modeling as model risk management has received sparse attention in Cyber risk assessment and Cyber insurance modeling.

Exhaustive review of quantitative models in Cyber risk and Cyber insurance modeling developed the first known analysis establishing significant and extreme model risks, tail risks, and, systemic risks related to predominant models in use.

Developed an empirical study of VaR and Bayesian statistical inference methodologies with specific guidance for containing model risks by applying multiple simple and advanced models for cross-checking the reliability of VaR.

Developed an analysis of the Markov Chain Monte Carlo Models, Gibbs Sampling and Metropolis-Hastings statistical computing algorithms for enabling Bayesian statistical inference methodologies to minimize model risk in Cyber risk and Cyber insurance risk modeling for the specific context of cybersecurity.

Developed the first known portfolio theory based framework for Cyber insurance modeling with guidance to minimize model risks, tail risks, and systemic risks inherent in models in commercial Cyber insurance modeling.

Given increasing role of uncertainty in cyber (and financial) risk modeling and management, developed a framework for enabling Knightian uncertainty management relating it to model risk management.•

, SSRN Top-10 Papers: 24 Top-10 Rankings in Econometrics & Risk Modeling:Jan-May2015

Advisors: Distinguished Computer Scientists, Mathematicians, &, Physicists, AFRL/NYS-CRI.05/2015

Econometrics: Mathematical Methods & Programming eJournal

Computational Techniques

Information Systems & Economics eJournal04/2015

Econometrics: Mathematical Methods & Programming eJournal

Computational Techniques03/2015

Econometric Modeling: Capital Markets - Risk eJournal

Econometric Modeling: Risk Management eJournal

Econometric Modeling: Capital Markets - Risk eJournal

Operations Research Network eJournal

OPER Subject Matter eJournal

Systemic Risk

Econometrics: Mathematical Methods & Programming eJournal02/2015

Stochastic Models eJournal

Computational Techniques

OPER: Analytical

Other Econometrics: Mathematical Methods & Programming

Econometric & Statistical Methods - Special Topics eJournal

Microeconomics: Decision-Making under Risk & Uncertainty eJournal

VaR Value-at-Risk

Uncertainty & Risk Modeling

Econometric & Statistical Methods01/2015

Econometric Modeling: Capital Markets - Risk eJournal

Microeconomics: Decision-Making under Risk & Uncertainty eJournal

Uncertainty & Risk Modeling

VaR Value-at-Risk

PROJECTS PORTFOLIO

Top Wall Street Investment Banks Quantitative Finance Projects & Venture Projects

• Quantitative Finance Risk Analytics Modeling Wall Street Investment Banks & VC Projects

• Model Risk Management: Risk Management Analytics from 'Prediction' to 'Anticipation of Risk'

• Princeton Quant Trading Conference: Future of Finance Beyond 'Flash Boys': Cyber Finance:

• Quantitative Finance Risk Analytics, Econometric Analytics, Numerical Programming Models

• Quantitative Finance Model Risk Management for Systemic-Tail Risks in Cyber Risk Insurance

• JP Morgan Portfolio Optimization, VaR & Stress Testing: 17-Asset Class Portfolio

• JP Morgan Portfolio Liquidity Risk Modeling Framework for $500-600Bn Portfolio

• Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis

• Goldman Sachs Alumnus Asset Manager Large-Scale Data High Freq Econometric Models

• Quantitative Finance, Risk Modeling, Econometric Modeling, Numerical Programming

• Technologies of Computational Quantitative Finance & Risk Analytics and Risk Management

• Algorithms & Computational Finance: C++, SAS, Java, Machine Learning, Signal Processing

• Cybersecurity, Financial Protocols & Networks Protocols Analysis, and, Penetration Testing

• Quantitative Finance, Quantitative Risk Analytics & Risk Management Projects Impact

• Digital Social Enterprise Ventures Creating Trillion $ Practices for Hundreds of Millions

Research Impact Recognized among Information Science & Economics Nobel laureates

• AACSB International Reports Impact of Research among Black-Scholes, Markowitz, Sharpe

• Research Impact Recognized among Information Science & Economics Nobel laureates

• Computational Quantitative Finance Modeling & Risk Management Research Publications

• Griffiss Cyberspace Cybersecurity Venture Spans Wall Street and Hi-Tech Research

• Model Risk Management of Cyber Risk Insurance Models & Quantitative Finance Analytics

• Thesis on Ongoing Convergence of Financial Risk Management & Cyber Risk Management

• U.S. Federal Reserve & Office of the Comptroller of the Currency Model Risk Guidance

• Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis

• Markov Chain Monte Carlo Models & Algorithms to Enable Bayesian Inference Modeling

• OCC Notes Cybersecurity Risk & Cyber Attacks as Key Contributor to Banks' Financial Risk

• Future of Bitcoin & Statistical Probabilistic Quantitative Methods: Global Financial Regulation

• Models Validation Expert Panels: IT, Operations Research, Economics, Computer Science

Global, National, & Enterprise CxO Level Thought Leadership Risk Management Ventures

• CxO Think Tank that pioneered 'Digital' Management of Risk, Uncertainty, & Complexity

• CxO Consulting: Global, National & Corporate Risk Management Practices Leadership

• CxO Guidance: Cyber Defense & Finance-IT-Risk Management: Uncertainty & Risk

• CxO Keynotes: Conference Board, Silicon Valley, UN, World Economy: Uncertainty & Risk

• UN Quantitative Economics Expert Paper & Keynote on Global Economists Expert Panel

• National Science Foundation Cybersecurity & Cybercomputing National Expert Panels

• Digital Social Enterprise Innovation Ventures Pioneering the Future of Risk and Quant

• Global Footprint of Worldwide World-Leading CxO Risk Management Ventures & Practices

SKILLS, EXPERTISE & INTERESTS

Algorithms, Data Science, Machine Learning, Statistical Modeling, Quantitative Finance, Risk Management, Econometrics, Investment Banking, Portfolio Management, Financial Modeling, Derivatives, Predictive Analytics, Software Engineering, C++, Matlab, SAS, SQL, Microsoft Excel, VBA, Bloomberg, R, Python, Market Risk, Credit Risk, Liquidity Risk, Model Risk, Hedge Funds, Valuation, Quantitative Analytics, Financial Risk, Portfolio Optimization, Fixed Income, Trading Strategies, Statistics, Financial Econometrics, Time Series Analysis, Stress Testing, Data Modeling, Swaps, Equities, Trading, Data Mining, Stochastic Modeling, Quantitative Models, Asset Liability Management, Interest Rate Derivatives, Structural Equation Modeling, Cyber Risk, Cyber Risk Insurance, Cybersecurity, Information Assurance, Penetration Testing, Metasploit, Nmap, Wireshark, CISSP, CISA, CEH. More...Selected for inclusion in biographical profiles of worldwide leaders and achievers from both the United States and around the world in:

Marquis Who's Who in America

^{®}

Marquis Who's Who in the World^{®}

Marquis Who's Who in Finance & Industry^{®}

Marquis Who's Who in Science & Engineering^{®}.

POST-DOCTORAL & DOCTORAL EDUCATION

Post-Doctoral Quantitative Finance Research Presented at Princeton University

-Extreme RiskQuant Finance Models: Cyber Finance & Cyber Risk Insurance Modeling.

Top-10 PhD Double Doctorate in IT & Statistics, Quantitative Risk Management

- Quantitative PhD Thesis:Statistical Models of Quantitative Risk Management & Controls.

Top-14 MS Quantitative Finance:Applied Math:Advanced Econometrics, Risk Modeling

MFE/PRMIA Executive Education,UC Berkeley, Kellogg School of Management

MS Network & Computer Security:Cyber Finance, Bayesian Inference, Markov Chain Monte Carlo Models

MS Computer Science:Computational Finance, AI & Modeling, Algorithms, Data Mining, Machine Learning

MS Accountancy:Finance: Advanced Financial Accounting & Auditing, Asset Valuations & Risk Management

MBA Quantitative Economics:Advanced Statistics, Econometrics & Optimization

BE, Bachelor of Engineering:Mechanical Engineering:Physics,Chartered Engineer,C.Eng.

ABA/AIB,CISSP,CISA,CEH,CCP/CDP,CPA (Education), EC-Council,MATLAB, SAP-ERP/CRM,SAS.