Statistical & Financial Consulting by Stanford PhD
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  • PhD in Statistics from Stanford University

  • PhD Minor in Finance from the Stanford Business School

  • 12+ years of relevant experience on Wall Street and in private financial sector

  • More than 10 undergraduate, master's level and PhD level courses taught at Stanford over a period of 5 years

  • 2 years of statistical consulting at Stanford: advising researchers and students in the fields of Medicine, Biology, Psychology, Sociology, Education and Engineering

  • 9 years of statistical & financial consulting in New York City and all over the world ( remotely ): advising companies, business professionals, researchers and students in the fields of Finance, Marketing, Medicine, Biology, Psychology, Sociology, Political Science, Education, Engineering and Computer Science

  • More than 60 hedge funds, consulting companies, IT companies and online businesses in New York City, Long Island, Los Angeles, San Francisco, Chicago, London and Melbourne acting as clients over the last 9 years

  • More than 100 finance professionals acting as clients over the last 9 years

  • More than 50 MD's, nurses and other medical professionals acting as clients over the last 9 years

  • More than 40 researchers / professors in Psychology, Sociology, Education and Political Science requesting help with the statistical part of their research over the last 9 years 

  • More than 100 PhD students in Biology, Psychology, Sociology, Education and Finance requesting help with dissertation preparation and defense over the last 9 years 

  • More than 250,000 lines of code written in R, Matlab, SAS, Stata and Python during the consulting career


The areas can be divided into several broad, somewhat overlapping categories:

statistics - data mining / machine learning, signal processing, pattern recognition, classification, neural network, projection pursuit, MART, MARS, CART, random forest, support vector machine (SVM), wavelet analysis, genetic algorithm, ridge regression, lasso, nearest neighbor, discriminant analysis, naive Bayes, cluster analysis, multiple linear regression, logistic regression, logit / probit transformation, linearization of nonlinear regression, spline, kernel smoother, nonparametric statistics, cross-validation, model selection, bootstrap, jacknife, factor analysis / principal component analysis (PCA), canonical correlation analysis, Monte Carlo (variance reduction, antithetic / importance sampling, quasi Monte Carlo), Markov Chain Monte Carlo, EM algorithm, Gibbs sampler, Metropolis-Hastings, Bayesian statistics (conjugate prior, hierarchical Bayes, empirical Bayes), multivariate analysis, path analysis, structural equation modeling (SEM), missing data imputation, z-score, t-test, F-test, chi-square test, Wilcoxon test, Mann-Whitney / Kruskal-Wallis test, power calculation, weighted least squares (WLS), generalized least squares (GLS), heteroskedasticity, leverage, outlier diagnostics, robust estimation / hypotheses testing / confidence intervals, shrinkage, variance transformation, propensity score matching, generalized linear model (GLM), analysis of variance (ANOVA / MANOVA), analysis of covariance (ANCOVA / MANCOVA), quantile regression, GWAS, population genetics, survival analysis (Kaplan - Meier estimator, log-rank test, Cox proportional hazards model, accelerated failure time model, competing risks, recurring events), systems reliability, bioinformatics, longitudinal study, models for panel data (fixed effects, random effects, random slopes, GEE models), spatial statistics, family-wise error rate, Bonferroni correction, meta-analysis, experimental design, design of surveys, reliability theory, discrete probability - extensive statistics & biostatistics help;

econometrics - time series, instrumental variable, simultaneous equations, generalized method of moments (GMM), method of maximum likelihood, quasi likelihood, asymptotic efficiency, large sample properties, ARMA / ARIMA, ARCH / GARCH / EGARCH, ARDL, vector autoregression (VAR), vector error correction model (VECM), spectral theory, autocorrelation, Kalman filter, particle filter and other filtering methods, forecasting, intervention analysis, synthetic controls - extensive econometrics & statistics help;

stochastic processes - martingale, point / counting / Poisson process, Brownian motion, Levy process, random field, interpolation / extrapolation, diffusion, semimartingale, stochastic volatility modeling, stochastic calculus (stochastic integral, stochastic differential equation, Ito lemma, backward Kolmogorov equation, Feynman-Kac), stationary process, renewal theory, Markov chain, balance equation, regime switching process, Hidden Markov Model (HMM), structural change, spherically invariant process - help with probability & stochastic processes;

actuarial science - survival model, empirical hazard rate, life table, collective risk, copula model, premium schedule, varying annuity, decrement model, reinsurance derivative, pension funding, ruin theory - actuarial training & help with projects;

finance - asset pricing, option pricing, risk-neutral measure, replicating strategy, market risk, Black - Scholes, term structure, interest rate products, foreign exchange (FX / FOREX), credit derivative, equity, commodities, basket option, exotic derivatives, swap, swaption, cap, caplet, extinguishing swap, cancellable swap, callable bond, convertible bond, barrier option, Asian / American option, knockout, double knockout, baseball option, futures contract, credit default swap (CDS), bespoke CDO, index tranche, first to default swap, mortgage, empirical prepayment models, copula framework, structural models, reduced form models, Moody's / S&P rating based methods, correlation smile, loss curve, Heath - Jarrow - Morton (HJM), Longstaff - Schwartz, Crank - Nicolson scheme, portfolio theory, financial economics, statistical arbitrage (statarb), reversion, momentum, cointegration, Dickey - Fuller, proprietary trading, Sharpe / CalMar ratio optimization, backtesting, drawdown, technical analysis, portfolio optimization and risk management, Value at Risk (VAR), expected shortfall, black swan modeling, correlated risks, trigger events, contagion, hedging, butterfly trading, financial engineering / mathematical finance - extensive finance help;

statistical software - Matlab, R / S-PLUS / RStudio, SPSS / AMOS, SAS, JMP, Stata, Minitab, EViews, Python, Microsoft Excel - help with data analysis & programming.


Typically, I meet face to face with clients in New York and work via Skype, e-mail and / or phone with clients in other locations. What follows is an extended list of the locations I have covered in the past: Stanford (California), New York Metro area, Princeton (New Jersey), Long Island, New Heaven, Greenwich (Connecticut), Philadelphia, Pittsburgh (Pennsylvania), Washington DC, Baltimore (Maryland), Boston, Cambridge (Massachusetts), Columbus, Cleveland (Ohio), Chicago (Illinois), Bloomington (Indiana), Madison (Wisconsin), Miami, Orlando, Gainesville (Florida), Davis, San Francisco, Palo Alto, Mountainview, San Jose, Santa Cruz, Los Angeles, San Diego (California), Seattle (Washington), Houston, Austin, Dallas, College Station (Texas), Phoenix (Arizona), Denver (Colorado), Toronto, Montreal, Vancouver (Canada), Mexico City (Mexico), London, Cambridge, Edinburgh, (United Kingdom), Paris (France), Lausanne (Switzerland), Berlin, Frankfurt (Germany), Utrecht (the Netherlands), Bergen (Norway), Kuwait City (Kuwait), Dubai (UAE), Doha (Qatar), Singapore, Hong Kong (China), Tokyo (Japan), Brisbane, Sydney, Melbourne, Adelaide, Perth (Australia).

Please read the detailed description of the services offered in the areas of statistical consulting and financial consulting: home page, types of servicecase studies and payment options.