Global Risk Management Network, LLC, 757 Warren Rd, Cornell Business & Technology Park, Ithaca, NY 14852-4892
World Leading Hi-Tech Research Defining World Leading Digital, Computational, Quant & Cyber Risk Analytics Practices

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Dr. Yogesh MalhotraLinkedInBeyond 'Prediction' to 'Anticipation of Risk'Research Impact among Nobel LaureatesPrinceton University PresentationsDigital Ventures:
[Digital Transformation Pioneer] [Computational Quant Analytics] [Cyber Security Risk Engineering] [AI, Algorithms & Machine Learning] [FinTech: 'Rethinking Finance']
Post-Doc Quant Presentations at Princeton,Quant Top-10 PhD Double Doctorate,MSQF,MSCS,MSNCS,MSAcc,MBAEco,BE,CEng,CISSP,CISA,CEH,CCP/CDP,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®
Dr. Yogesh Malhotra
Post-Doc Computational Quant Analytics-AI & Modeling-Algorithms-Machine Learning: Princeton Quant Presentations,
PhD,MSQF,MSCS,MSNCS,MSAcc,MBAEco,
BE,CEng,CISSP,CISA,CEH,CCP/CDP
Who's Who in America®,
Who's Who in the World®,
Who's Who in Finance & Industry®,
Who's Who in Science & Engineering®
. 


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*RESEARCH
*SSRN
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GoogleScholar
*Princeton
*Syracuse
      


 

Research Impact among Nobel Laureates: Computer Scientist, Management Scientist, Information Scientist.
Wall Street Investment Banks-Hedge Funds Quant: Invited Princeton Post-Doctoral Quant Presentations.
Global Computational Quant Leaderships: Digital, Computational, Quant, Cyber Risk Management-Analytics.

World's Largest Banking & Finance and IT & Telecom Firms; Silicon Valley VCs & CxOs, Wall Street CxOs,
National Science Foundation; United Nations; US-World Governments, Economies & Defense Agencies.

*E-mail: Dr.Yogesh.Malhotra[at]gmail.com *LinkedIn: linkedin.com/in/yogeshmalhotra
*2016 & 2015 Princeton Quant Trading Conference: Sponsors: Goldman Sachs, Citadel, SIG, KCG Holdings.
*2016 Princeton Quant Trading Conference Invited Research Presentation: Sponsor: Princeton University.
*2015 Princeton Quant Trading Conference Invited Research Presentation: Sponsor: Princeton University.
*2015-2016: 39 Top-10 SSRN Research Rankings: Digital, Computational, Quantitative & Cyber Risk Analytics.
*2016 New York State Cyber Security Conference Research Presentation: Sponsor: New York State Governor.
*2008: AACSB: Real Impact of Research among Nobel Laureates such as Black-Scholes & William Sharpe.

INTERVIEWS IN WORLDWIDE BUSINESS & TECHNOLOGY PRESS: INSIGHTS & FORESIGHTS GUIDING GLOBAL PRACTICES
CIO Magazine CIO Insight Inc. Magazine Fortune Magazine Wall Street Journal Business Standard
Over 20-Years of Global High Impact Hi-Tech Digital Practices Leadership spans Silicon Valley to Seoul and all continents in between.

AACSBAACSB logo

  
Wall Street Journal
  
Risk Management Tech Ventures leading Computational Quantitative Analytics, Machine Learning, Data Science, Quantitative Finance, & Cybersecurity Practices.
Worldwide Business and IT Editorial Coverage & Interviews in Wall Street Journal, New York Times, Fortune, Fast Company, Forbes, Business Week, CIO, CIO Insight, Computerworld, Information Week, etc.


[Digital Transformation Pioneer] [Computational Quant Analytics] [Cyber Security Risk Engineering] [AI, Algorithms & Machine Learning] [FinTech: 'Rethinking Finance']
Dr. Yogesh Malhotra: LinkedIn: Risk Analytics Beyond 'Prediction' to 'Anticipation of Risk': Princeton University Presentations on FinTech CyberFinance
Who's Who in America®, Who's Who in the World®, Who's Who in Finance & Industry®, Who's Who in Science & Engineering®
2015 & 2016 Princeton Quant Trading Conference Presentations: Computational Quant & Crypto Machine Learning Algorithms,
2008: AACSB International Impact of Research Report: Named among Black-Scholes, Harry Markowitz & Bill Sharpe

*Projects *Goldman Sachs *JP Morgan *Wall Street Hedge Funds *Princeton Presentations *Model Risk Arbitrage *Cyber Finance *Cyber Risk Insurance * Ventures
*Bayesian vs. VaR *Markov Chain Monte Carlo Models *Mobile Trust Models * Pen Testing Frameworks *Bitcoin Cryptanalytics *NFS Cryptanalytics Algorithms
*Research Impact *Future of Finance *Beyond VaR *Model Risk Management *SR11-7 *OCC2011-12 *Future of Risk *Cyber Risk *SSRN *Google Scholar *Publications


EXECUTIVE PROFILE
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Top-10 IT & Statistics Double Doctorate PhD Computer Scientist, Management Scientist, Information Scientist, and, Chartered Engineer with research impact ranked and recognized among Finance & IT Nobel Laureates by AACSB & scientific impact studies. Senior Quant leaderships guiding MDs and PMs at Wall Street investment banks with $1 Trillion AUM such as JP Morgan. Founder, Computational, Quant, &, Risk Analytics Digital Ventures with CxO clients-patrons such as Goldman Sachs, Google, Harvard, IBM, Intel, and, Microsoft recommended by IT visionaries such as Microsoft founder Bill Gates, Big-4 CxOs, and, US Army, Navy, and Air Force CIOs. Invited advisor to $100 Billion hi-tech firms such as Intel, Silicon Valley VCs-CEOs, US & World Governments, UN, NSF. Global Financial Systems projects leader with Big Banks such as Bank of America.

Recent post-doc research invited for presentations at Princeton Quant Trading Conference sponsored by Princeton University, Goldman Sachs, Citadel, SIG, and KCG Holdings. Post-doc research recognized by SSRN for 39 Top-10 SSRN Rankings in Operations Research, Decision Modeling, Stochastic Models, Econometrics, Mathematical Methods & Programming, and, Uncertainty & Risk Modeling. Computational Quant Finance-Risk Analytics projects leader with Wall Street investment banks with $1 Trillion AUM such as JP Morgan: Quant Finance, Liquidity Risk, Market Risk, Credit Risk, Financial Econometrics, Financial Programming, Large-Scale Data Modeling, Interest Rate Derivatives, Fixed Income & Equity Portfolio Modeling with SAS, MATLAB, C++, MS-Excel, VBA, Bloomberg.

Princeton University: Invited Post-Doctoral Quant Research Presentations. 
Carnegie Mellon & Kellogg: Invited Executive Education Faculty.
TT Professor: Computer Scientist, Management Scientist, Information Scientist.

Invited interviews & editorial reviews as industry benchmark for CxO strategies 
in global press including CIO, Wall Street Journal, New York Times, Fortune, Inc., etc.

Post-Doctoral research in Computational Quantitative Analytics: AI & Modeling, Algorithms, Machine Learning
- Having received admission offers from Top-10 PhD Programs in both Accountancy and Economics
- Adding ~ 2x Credits of the 91 Cr 'Double Doctorate' PhD including four new Computational Quant Analytics graduate degrees.
Top-10 MIS PhD: '45-Cr PhD' Credits in both IT-Quantitative Methods & Statistics-Quantitative Methods: 91 Cr PhD.

PRMIA Executive Education in Quantitative Risk Management, Kellogg School of Management.
MFE Executive Education in Computational Quant Analytics, University of California Berkeley.
MS Cybersecurity: Cyber Risk Insurance, Algorithms, Machine Learning, AI & Modeling, Pen Testing Champion.
MS Computer Science: Computational Finance, Algorithms, Machine Learning, AI & Modeling, Cryptography.
MS Quantitative Finance: Derivatives, Stochastics, Securities Pricing, Risk Modeling, Risk Management.
MS Accountancy: Finance, Auditing, Derivatives, Valuations, Global Financial Crisis: Risk Management.
MBA Hypermedia Computing, Quant Economics, Advanced Statistics, Econometrics, Optimization Champion.
Certifications: C.Eng., CISSP, CISA, CEH, CCP/CDP, CPA-Education, SAS, MATLAB, SAP-ERP, SAP-CRM, AIB/ABA.

Advancing on Top Wall Street Investment Banks’ Computational Quant Risk Management & Risk Analytics practices leaderships & Research Impact recognized among Finance-Economics and IT Nobel Laureates by AACSB & scientific impact studies continuing global leadership of Computational Quant Risk Management & Risk Analytics practices.

  • Risk Management Analytics beyond 'Prediction'​ to 'Anticipation of Risk'™

    • Risk Management Analytics research program that anticipated needs of Wall Street CEOs, CFOs, CROs to “anticipate risk” over a decade before they all said "we must anticipate risk"​ with invited machine learning research and media interviews in premiere press since 1990s.
    • Advancing Fed/OCC SR11-7 and OCC 2011-12 Model Risk Management (MRM) Execution.
    • Named among others such as Black-Scholes, Markowitz, Sharpe as "exemplar"​ of "considerable impact on actual practice"​
    - AACSB International Impact of Research Report, 2008.
    • CNET Networks Corporate Computing Award for Most Influential Research, 2002.
    • Interviews and Reviews of Related Research in: Wall Street Journal, Fortune, Inc., CIO, etc.

2015-2016: 39 SSRN Top-10 Research Rankings for Post-Doctoral Research
Ranked in Top 10% of SSRN Authors just based on Post-Doctoral Research
Computational Quant Analytics: AI & Modeling, Algorithms, Machine Learning

• 39 SSRN Top-10 Research Rankings:
39 SSRN Top-10 Research Rankings: Computational-Quant-Cyber-FinTech-Algorithms-Machine Learning-AI & Modeling, 2015-2016.
- Quantitative Finance, Computer Science, Cybersecurity, Machine Learning, Bayesian Inference, Markov Chain Monte Carlo Models, Data Science, Computational Statistical Algorithms.
- Post-Doctoral Research & Working Papers
• Research selected for 39 SSRN Top-10 Rankings in Computational Quantitative Risk Analytics.
- SSRN Top-10 Ranking Categories: 
• Capital Markets, 
• Computational Techniques, 
• Corporate Governance, 
• Cyberlaw, 
• Decision-Making under Risk & Uncertainty, 
• Econometric & Statistical Methods, 
• Econometric Modeling, 
• Econometrics, 
• Hedging & Derivatives, 
• Information Systems & Economics, 
• Mathematical Methods & Programming, 
• Microeconomics, 
• Operations Research, 
• Risk Management, 
• Risk Management Controls, 
• Risk Modeling, 
• Stochastic Models, 
• Systemic Risk, 
• Uncertainty & Risk Modeling, and, 
• VaR Value-at-Risk

  • Princeton University: Offensive Cybersecurity & Model Risk Arbitrage

    • 2016 Princeton Quant Trading Conference invited Post-Doc Presentation.
    - Sponsors: Princeton University, Goldman Sachs, Citadel, SIG, Apr 16, 2016.
    - Beyond Stochastics to Non-Deterministic Finance: Model Risk Arbitrage-Open Systems Finance:
    Focus: Cybersecurity, Quant FinTech, Bayesian Networks, Non-Deterministic Probability-Statistics.
    • Pioneered Computational Quantitative Analytics industrial research in Non-Deterministic Finance, Model Risk Arbitrage, Open Systems Finance, and, Black Hat Finance invited for presentation at the 2016 Princeton Quant Trading Conference.

  • Princeton University: Defensive Cybersecurity & Model Risk Management

    • 2015 Princeton Quant Trading Conference invited Post-Doc Presentation.
    - Sponsors: Princeton University, Citadel, KCG Holdings, Apr 4, 2015.
    - Quantitative Finance Models for Extreme Risks: Cyber Risk Insurance Modeling & Finance.
    Focus: Cyber Finance: Quantitative Finance, Computer Science, Cybersecurity, Machine Learning.
    • Pioneered Computational Quantitative Analytics industrial research in Cyber Finance & Cyber Risk Insurance Modeling in collaboration with the committee of distinguished research scientists from AFRL/NYS-CRI invited for presentation at the 2015 Princeton Quant Trading Conference.
    • Pioneering Quantitative Finance Analytics: Statistical Computing Methods & Algorithms
    Cyber Finance: Future of Finance Beyond 'Flash Boys': Tail Risks & Systemic Risks: 
    Risk Modeling for Managing Uncertainty in an Increasingly Non-Deterministic Cyber World.
    Advanced Risk Modeling Statistical Techniques: Econometrics & Time Series Models, Bayesian Inference, Markov Chain Monte Carlo, Capital Markets, Derivatives, Portfolio Construction & Optimization Models, Volatility Models, VaR, ARCH, GARCH, Multifactor Pricing Models, Market Risk, Credit Risk, Liquidity Risk, Cyber Risk Insurance Models.
    • Invited ERM/MRM Keynotes to Top Investment Bank HQ and National CROs/CSOs.
    • Invited Cyber-RM Expert Advice & Invited Interviews by MDs-Teams of Top Wall Street Firms.

  • Math-FinTech-Algorithms: Transformation of Finance for Switzerland

    Math-Fintech-Algorithms: Transformation of Finance for Switzerland
    Sponsor: Switzerland Federal Department of Economic Affairs.
    Mathematics-FinTech-Algorithms: Digital Transformation of Global Banking & Finance, 2016.
    Switzerland Federal Department of Economic Affairs, Education & Research EAER.

  • Enterprise Cyber Risk Management for CROs-CSOs National Plenary Keynote

    Invited Plenary Keynote to National Fortune 100 Chief Risk Officers & Chief Security Officers:
    National Chief Security Officers Summit, Philip Morris/Altria World HQ, Richmond, VA, Sep 2015.

  • State Street Bank World HQ Keynote on Modeling Extreme Cyber Finance Risks

    Extreme Cyber Risk Computational Quant Finance Models, Aug. 2015:
    State Street Bank World HQ, Boston, MA.

  • Pre-empting the forthcoming Global Cyber Insurance Crisis by Pioneering Cyber Risk Insurance Models beyond Value-At-Risk (VaR) Analytics

    • To avert the impending Global Cyber Insurance Crisis resulting from large-scale commercial reliance upon quantitative models with inherent model risks, tail risks, and systemic risks in current form, this dissertation makes the following key contributions.
    • First, we develop the first known Cyber-Finance-Trust™ framework for Cyber insurance modeling to analyze how finance risk entangled with Cyber risk further exacerbates the systemic, interdependent, and correlated character of Cyber risks.
    • Second, we develop 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. 
    • Third, our review of quantitative models in Cyber risk and Cyber insurance modeling develops the first known analysis establishing significant and extreme model risks, tail risks, and, systemic risks related to predominant models in use.
    • Fourth, we develop 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.
    • Fifth, we develop 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.
    • Sixth, we develop 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.
    • Finally, given increasing role of uncertainty in cyber (and financial) risk modeling and management, we develop a framework for enabling Knightian uncertainty management relating it to model risk management.

Wall Street Investment Banks Project Leaderships of Risk Modeling & Analysis for Banks with $1 Trillion AUM:
- JP Morgan Private Bank Multi-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 Construction
- Goldman Sachs Alumnus' Asset Management Firm with $400-500 Billion AUM, Midtown Manhattan.
Quantitative Finance, Risk Modeling, Computational Finance, AI-Modeling, Algorithms, Machine Learning, Computer Science, Network Science.

Project Leader: JP Morgan, Wall Street Hedge Funds, & Venture Capital Finance Projects.
Technologies: SAS, MATLAB, C++, MS-Excel, VBA, Bloomberg, NYSE-TAQ, CRSP.
Models: Derivatives, Credit Risk, Market Risk, Interest Rates, Equity & Fixed Income Portfolios.

Credit Risk Models

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

Market Risk Models

Volatility Models, ARCH/GARCH, MLE, 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, 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

Equity Portfolio Models

Derivatives, 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 Portfolio Models

Bond 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.

Project Leader, JP Morgan Private Bank Portfolio Liquidity Risk Modeling Framework, reporting to and guiding
Global Head of Quantitative Research & Analytics, US Head of Portfolio Construction and team. [Midtown Manhattan, New York City]
JP Morgan (JPM) Hands-On Team Leadership Projects Leader
JP Morgan Fund of Funds Liquidity Assessment Framework Development Leader

Mentor: JPM Global Head of Quantitative Research & Analytics, JPM US Head of Portfolio Construction:
JPM Top-4 Leadership ED in Global Financial Crisis Management, Harvard Case Study.
Advised: Team of Senior EDs/MDs, Portfolio Managers, Quants.

JP Morgan Portfolio Construction & Optimization Liquidity Assessment Framework
Asset Pricing, Risk Management, Liquidity Risk, Market Risk, Credit Risk, ALM Risk, Portfolio Risk, Investment Risk, Non-Normality, Non-Linearity. MATLAB, SAS, C++, MS-Excel, VBA, Bloomberg.

Developed Large Equities
Developed Small Equities
Emerging Equity
Unlisted Equity
Various Commodities
Government Bonds
Investment Grade Bonds
Inflation-Linked Bonds
High Yield Corporate Bonds
Emerging Market Hard Currency Bonds
Emerging Market Local Currency Bonds
Major Currencies
Statistical Arbitrage Hedge Funds
Equity Hedge Hedge Funds
Merger Arbitrage Hedge Funds
Macro Hedge Funds
Relative Value Hedge Funds.
17-Asset Class Portfolio Liquidity Assessment & Stress Testing Research & Analysis
Technical Framework & Project Management Foundation:
Exhaustive Review of Recent 25-Years of Liquidity Measurement Research
Academic, Policy, and Practice Literatures:
Technical Liquidity Risk Models, Methods, & Measures Research:
~5,000 documents ~ 60,000 pages.
Project Leader, JP Morgan Private Bank Portfolio Optimization & VaR Stress Testing, reporting to and guiding
Global Head of Quantitative Research & Analytics, US Head of Portfolio Construction and team. [Midtown Manhattan, New York City]
JP Morgan (JPM) Hands-On Team Leadership Projects Leader
JP Morgan Portfolio Construction, Optimization & VaR Stress Testing Leader

Mentor: JPM Global Head of Quantitative Research & Analytics, US Head of Portfolio Construction.

Technologies: MATLAB, SAS, C++, MS-Excel, VBA, Bloomberg

Alternative Investments, Hedge Funds, Equities, Commodities, Fixed Income, Bonds, Currencies

Asset Pricing, Risk Management, Liquidity Risk, Market Risk, Credit Risk, ALM Risk, Portfolio Risk, Investment Risk, Non-Normality, Non-Linearity.
Led quantitative portfolio liquidity modeling for $500B fund-of-funds & hedge funds (HF).
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 and presentations to Senior Quants, 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.

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. [Midtown Manhattan, New York City]
Project: Hedge Fund Quantitative Finance & Quantitative Risk Modeling
Goldman Sachs Alumnus' $400 Billion+ Asset Management Firm.

Mentor: Wall Street SVP Hedge Fund Manager with Top Wall Street Investment Banks:
Harvard Computer Scientist & Mathematician Alumnus Wall Street Hedge Fund SVP/PM.
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.

SAS High Frequency Econometric Modeling of Market Microstructure
400 State Street Advisors Trading Strategies Analysis for Alpha and Risk
Hedge Fund Performance Analysis
Quantitative Finance, Quantitative Risk Modeling

Analyzed 400 State Street Associates Trading, Hedging, and Risk Management Strategies.
Replicated /Analyzed Large Scale Data HF Econometrics Models of Market Microstructure.
Critical Review of State Street Associates Trading, Hedging, and Risk Management Strategies.
High Frequency Econometrics Models of Trade Price Impact & Market Microstructure.
Researched Co-Integrated Time Series for Ultra-High Frequency Tick-and-Quote (TAQ) Data.
Presented and Taught VARMAX Models of Co-Integrated Time Series for HF Econometrics.
Analysis: Why Existing `Alpha´ Research Is Insufficient for Profitable Hedge Fund Asset Management.

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.
• Risk Analytics & Risk Management Specialist-Portfolio Strategist
* Execution & Risk Management of Long/Short Equity Trades
- 3,500 Buy/Sell Transactions in Double-Digit Million US$
- Equity Trades of 250 Companies across Diverse Sectors
- Technical/Fundamental/Structural Analysis
- Using Aggregated Data from 200 Market Data Sources.
* Development of Financial Risk Analytics Technologies
- Development Technologies
Unix, CGI, Perl, MySQL, PHP, C++, etc.
* Financial Modeling, Time Series Modeling, Structural Equation Modeling
SAS, SPSS, MATLAB, MS-Excel, VBA, AMOS, PLS, Compustat, WRDS, CRSP.
• 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.
• Global Banking Financial Systems Projects Leader for Global Banks, USA & Hong Kong.
Global Financial Systems Modeling, Models Quality Assurance, Development & Implementation.

• Bank of America merger (Las Vegas), Bank of America Nevada.
Site Leader, Models Quality Assurance & Models/Systems Integration.
Senior Analysts/Analysts Team Leader, Systems Implementation.

• Crédit Agricole Corporate and Investment Bank (Hong Kong)
Formerly, Banque Indo-Suez, Hong Kong
Algorithms Strategist & Technical Lead
Hong Kong Treasury Management, Multi-Currency/Forex Arbitrage.

• Wells Fargo Bank (Davenport)
Formerly Davenport Bank & Trust Company

• Big-3 IT, Unisys Global Financial Services (Atlanta, Norcross)
- CxO Management Consultant: TATA-Unisys Facilitation with CIO Mr. James A. Unruh.
- Senior Analysts/Analysts Team Leader.
Led Modeling & Development of Global Financial Systems Used by Worldwide Banks.

• Tata Group Financial Services Division (Bombay, Delhi): Banking Projects, USA & Hong Kong.
Corporate Strategy Keynote to Strategic & Senior Leadership at the Global Big-3 IT Firm:
- Advancing Beyond Mainframes to Unix & C Software Services for Global IT Market Dominance.
Modeling & Development of Global Financial Systems Used by Worldwide Banks.
- Promoted to Systems Analyst, Global Financial Services, SWOT Mentor: Corporate SVP.
Programmed Algorithmic Language (ALGOL), 3GL & 4GL Systems, Hierarchical DBMS.

• Founder, Risk Analytics Ventures with clients & patrons such as Goldman Sachs, Google, IBM, Intel, Microsoft, Harvard.
Global Thought Leader & Advisor for Big-4, Fortune 100 CxOs, Silicon Valley VCs & CEOs
• Global CxO Risk Management Advisory & Consulting Practice.
- Invited Thought Leader, Accenture Consulting, Senior MDs & Practice Founders/Owners.
- $100 Billion Firms such as Intel Corporation, British Telecom (UK), Philips (Netherlands),
- Silicon Valley VCs & CEOs: 300 Venture Capitalists, Tech-CEOs, and Angel Investors.

Founding Chairman & Chief Knowledge Architect, CEO/CIO/CTO, Risk Analytics Ventures.
• Venture Clients/Patrons: Goldman Sachs, Google, Harvard, IBM, Intel, Microsoft, NASA, etc.
• Founder & Executive Director, Global CxO ventures on Risk Management & Risk Analytics.
- Recommended by Top Tech Visionaries such as:Microsoft founder Bill Gates, Big-4 (PwC, E&Y) CxOs,
Harvard Business School Professors, US & World Governments.
- Recommended by U.S. AFRL/Army/Navy/Air Force/NASA CxOs.


• 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


PROJECTS PORTFOLIO
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Recent Research Presentations and Research Reports
*Princeton University Presentations on the Future of Finance: 'Rethinking Finance' for Era of Global Networked Digital Finance.
*2016 Princeton Quant Trading Conference Invited Research Presentation: Beyond Stochastic Models to Non-Deterministic Methods.
*2015 Princeton Quant Trading Conference Invited Research Presentation: Beyond Risk Modeling to Knightian Uncertainty Management.
*Beyond 'Bayesian vs. VaR' Dilemma to Empirical Model Risk Management: How to Manage Risk (After Risk Management Has Failed).
*Markov Chain Monte Carlo Models, Gibbs Sampling, & Metropolis Algorithm for High-Dimensionality Complex Stochastic Problems.
*Risk, Uncertainty, and Profit for the Cyber Era: 'Knight Reconsidered': Model Risk Management of Cyber Risk Insurance Models.
*Cybersecurity & Cyber-Finance Risk Management: Strategies, Tactics, Operations, &, Intelligence: ERM to Model Risk Management.
*Number Field Sieve Cryptanalysis Algorithms for Most Efficient Prime Factorization on Composites: Beyond Shannon's Maxim.
* Bitcoin Protocol & Bitcoin Block Chain: Model of 'Cryptographic Proof' Based Global Crypto-Currency & Electronic Payments System.
*2015-2016 39 SSRN Top-10 Research Rankings for Computational Quantitative & Risk Analytics Algorithms Machine Learning Research.
* 2008 AACSB International Impact of Research Report: Named among Black-Scholes, Markowitz, Sharpe, Modigliani & Miller

Top Wall Street Investment Banks Quantitative Finance Projects & FinTech Ventures
Princeton: Future of Finance: 'Rethinking Finance' for Era of Global Networked Digital Finance
2016 Princeton Quant Trading Conference: Invited Research Presentation: Model Risk Arbitrage
2015 Princeton Quant Trading Conference: Invited Research Presentations: Future of Finance
Quantitative Finance Risk Analytics Modeling Wall Street Investment Banks & VC Projects
Model Risk Management: Risk Management Analytics from 'Prediction' to 'Anticipation of Risk'
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

Named among FinTech Finance & IT Nobel laureates for Real World Impact of Research
FinTech Innovations: Model Risk Arbitrage, Open Systems Finance, Cyber Finance, Cyber Insurance
AACSB International Reports Impact of Research among Black-Scholes, Markowitz, Sharpe
Research Impact Recognized among Finance & Information Technology Nobel laureates
39 SSRN Top-10 Rankings: Computational Quant Analytics: Algorithms, Methods & Models
FinTech Innovations: Model Risk Arbitrage, Cyber Finance, Cyber Risk Insurance Modeling
Computational Quantitative Finance Modeling & Risk Management Research Publications
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 FinTech-Cyber-Risk Analytics 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
The Future of Finance Project Leading Quantitative Finance Practices at Elite Conferences
The Griffiss Cyberspace Cybersecurity Venture Spans Wall Street and Hi-Tech Research
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