Roarke McNaught

Adept technical know-how: - Python (NumPy, SciPy, pandas, statsmodels, scikit-learn, Seaborn, Plotly, Dash, numba, Dask, SQLAlchemy, pymc3, QuantLib, arch, TensorFlow-Probability, cvxpy) - R (tidyverse, data.table, mlr, caret, Prophet, randomforest, rugarch, rmgarch, factorstochvol) - Julia (currently learning) - SQL

  • Financial risk professional with 13+ years of experience in trading, quantitative risk management, and predictive data analytics.
  • Deep understanding of energy and capital markets focusing on electricity, natural gas, equity, and high-yield credit.
  • Advanced skillsets in derivatives pricing, asset valuation, portfolio optimization, hedge analysis, volatility estimation/forecasting, dependence structure modeling (e.g., w/ copulas), and market risk measurement (e.g., VaR, conditional VaR, cash flow-at-risk, gross margin-at-risk, stress testing, sensitivity analysis).
  • Well-versed in multiple linear regression, robust regression, Bayesian inference, and time series analysis (e.g., ARIMA, SARIMAX, GARCH, BSTS).
  • Additional competencies include stochastic programming, Monte Carlo methods, bootstrapping, dimensionality reduction (e.g., PCA, PPCA, kernel PCA, ICA, projection pursuit, factor analysis), regime-switching regression, Hidden Markov Models (HMMs), Gaussian Processes (GPs), random forests, gradient boosting, and deep learning.
  • Houston, TX, USA
  • Member for 6 months
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  • Last seen Mar 11 at 2:17

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