World Leading Hi-Tech Research Defining World Leading Risk Management Practices
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Dr. Yogesh Malhotra
Chief Research Scientist

Computational Quantitative Analytics
Machine Learning, Data Science,
Quantitative Finance, Cybersecurity


PhD, MSQF, MSCS, MSNCS, MSAcc, MBAEco,
BE Mech., ABA/AIB, C.Eng., CISSP, CISA, CEH, CCP/CDP, CPA (Education), MATLAB, SAP-ERP/CRM, SAS

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 - LinkedIn

GMail: 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.


*AACSB Reports Impact of Model Risk Management among Finance Nobel Laureates such as Black-Scholes
*Princeton Quant Trading Conference Future of Finance Presentation on Model Risk Management
*Computational Quantitative Analytics Research on Model Risk Management Leading Industry Leaders

Post-Doctoral Quantitative Finance Research in Model Risk Management
2015 Princeton Quant Trading Conference: Post-HFT Model Risk Management: Invited Research Presentation
2015 Jan-May: 24 SSRN Top-10 Rankings:
Uncertainty & Risk Modeling, Econometric Modeling, Stochastic Models
Post-Doc Thesis
: Quantitative Finance Model Risk Management of Tail Risks & Systemic Risks
- Computational Finance, Portfolio Management, Cyber Risk Insurance Modeling, Cyber Finance

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

Quantitative PhD Thesis: Statistical Models of Quantitative Risk Management & Controls 
Quantitative PhD Courses in
Advanced Statistics & Structural Equation Modeling, Carnegie Mellon University 
MS Quantitative Finance: Applied Math:
Advanced Econometrics, Risk Modeling, Fordham University 
Master of Financial Engineering Executive Education, University of California, Berkeley
Kellogg/PRMIA Executive Education, Risk Management, 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, C.Eng., CISSP, CISA, CEH, CCP/CDP, CPA (Education), MATLAB, SAP-ERP/CRM, SAS.

*Projects *Goldman Sachs *JP Morgan *Wall Street Hedge Funds *Princeton Quant Trading Talk *Model Risk Management *SR11-7 & OCC2011-12
*Research *Future of Finance *Bayesian vs. VaR *Markov Chain Monte Carlo Models *Cyber Finance *Future of Risk *Cyber Risk *Bitcoin Protocol


Executive Profile
- Recent Projects - Research Impact - Projects Portfolio - Skills, Expertise & Interests - Education & Certifications - Publications - Tech Ventures

EXECUTIVE PROFILE
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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 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.

• 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 Quantitative Modeling PhD Computer Scientist 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
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JP Morgan Private Bank, Goldman Sachs Alumnus' Asset Manager & Venture Capital
Econometric Modeling, Quantitative Finance, Quantitative Risk Modeling

2015 Jan-May, SSRN Top-10 Papers: 24 Top-10 Rankings in Econometrics & Risk Modeling.
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 Econometrics

Economic 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 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.

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

JP Morgan Portfolio Liquidity Assessment Framework Development Leader

Portfolio Assets Modeled: 17 Asset Classes:
Hedge Funds (HF), Alternative Investments, Equities, Commodities, Fixed Income, Bonds, Currencies:

Developed Large Equity
Developed Small Equity
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 Fund
Equity Hedge Hedge Fund
Merger Arbitrage Hedge Fund
Macro Hedge Fund
Relative Value Hedge Fund

Asset 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 Managers

Axioms 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 York
Mentor:
Wall Street SVP Hedge Fund Manager with Top Wall Street Investment Banks:
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.

Project Management and Technical Team Leadership

SAS
High Frequency Econometric Modeling
of Market 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.

2015 Jan-May, SSRN Top-10 Papers: 24 Top-10 Rankings in Econometrics & Risk Modeling:
Advisors: Distinguished Computer Scientists, Mathematicians, &, Physicists, AFRL/NYS-CRI.

05/2015

Econometrics: Mathematical Methods & Programming eJournal
Computational Techniques
Information Systems & Economics eJournal

04/2015

Econometrics: Mathematical Methods & Programming eJournal
Computational Techniques

03/2015

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 eJournal

02/2015

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 Methods

01/2015

Econometric Modeling: Capital Markets - Risk eJournal
Microeconomics: Decision-Making under Risk & Uncertainty eJournal
Uncertainty & Risk Modeling
VaR Value-at-Risk

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RESEARCH IMPACT
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Leading-edge computational quantitative analytics research at the intersection of econometrics, finance, machine learning, cybersecurity, and statistical computing algorithms advancing upon prior high impact experience in financial econometrics, quantitative risk modeling, digital marketing, and, digital consumer behavior research and practice with clients and patrons such as:

- JP Morgan, Goldman Sachs, Bank of America, Google, IBM, Intel, Microsoft, and, Ogilvy.

Latest research on machine learning including Bayesian modeling and Markov Chain Monte Carlo Models statistical computing algorithms focus of invited research presentation at the 2015 Princeton Quantitative Trading Conference sponsored by Princeton University Bendheim Center & ORFE, Citadel, and, KCG Holdings, April 2015.

Latest research also selected for 24 Top-10 SSRN rankings in statistical, econometric, computational, and stochastic modeling techniques by the SSRN research network founded and overseen by professors from institutions such as Harvard Business School, Jan-May 2015.

Named as "exemplar" of "considerable impact on actual practice" among Finance Nobel laureates such as Black-Scholes, Markowitz, &, Sharpe by the AACSB International Impact of Research Report, 2008.

Research ranked and recognized among Top-50 Business & Economics researchers as well as Information Science and Finance/Economics Nobel laureates in business press, industry surveys & scientific impact studies.

Advised US & World governments, parliaments, and, cabinets and delivered national keynotes and nationally broadcast interviews among Knowledge Management pioneers such as Dr. Ikujiro Nonaka such as for South Korea's national Vision Korea Campaign, 2000.

Interviewed among Virtual Organization pioneers such as Hatim A. Tayabji, CEO, Verifone, while a PhD student in mid-1990s.

Applied research including world's Top-ranked Research Web site (Computer World), Top-3 Search Engine (Carnegie-Mellon Industry.Net Awards), and Top-10 Social Network developed while doing PhD recognized as global benchmarks of CEO and CIO practices in worldwide business technology press including:

- Wall Street Journal, New York Times, Los Angeles Times, Fortune, Forbes, Inc., Business Week, San Jose Mercury News, Computerworld, Information Week, CIO Magazine, CIO Insight, Chief Executive, etc.

Applied research ventures also recommended and applied by:
- Top IT Executives such as Microsoft Founder, Chairman and CEO Bill Gates;
- Top Business Executives such as PwC Vice Chairman and CKO Ellen Knapp;
- Global Banking and Finance institutions;
- CxOs of NASA / US Army / US Navy / US Air Force / US Air Force Research Lab; and,
- Senior leaders at world governments and parliaments such as the European Union and the Australian Parliament.

More...

PROJECTS PORTFOLIO
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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
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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®.

EDUCATION & CERTIFICATIONS
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Post-Doctoral Quantitative Finance Research in Model Risk Management
2015 Princeton Quant Trading Conference: Post-HFT Model Risk Management: Invited Research Presentation
2015 Jan-May: 24 SSRN Top-10 Rankings: Uncertainty & Risk Modeling
, Econometric Modeling, Stochastic Models
Post-Doc Thesis
: Quantitative Finance Model Risk Management of Tail Risks & Systemic Risks
- Computational Finance, Portfolio Management, Cyber Risk Insurance Modeling, Cyber Finance

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

Quantitative PhD Thesis: Statistical Models of Quantitative Risk Management & Controls 
Quantitative PhD Courses in Advanced Statistics & Structural Equation Modeling, Carnegie Mellon University 
MS Quantitative Finance: Applied Math: Advanced Econometrics, Risk Modeling, Fordham University 
Master of Financial Engineering Executive Education, University of California, Berkeley
Kellogg/PRMIA Executive Education, Risk Management, 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.