| Comparing Sharpe ratios: So where are the p-values? JD Opdyke Journal of Asset Management 8, 308-336, 2007 | 203 | 2007 |
| Estimating operational risk capital: the challenges of truncation, the hazards of MLE, and the promise of robust statistics JD Opdyke, A Cavallo The Journal of Operational Risk, Forthcoming, 2012 | 52 | 2012 |
| A unified approach to algorithms generating unrestricted and restricted integer compositions and integer partitions JD Opdyke Journal of Mathematical Modelling and Algorithms 9 (1), 53-97, 2010 | 34 | 2010 |
| Fast permutation tests that maximize power under conventional Monte Carlo sampling for pairwise and multiple comparisons JD Opdyke Journal of Modern Applied Statistical Methods 2, 27-49, 2003 | 34 | 2003 |
| Estimating operational risk capital with greater accuracy, precision, and robustness JD Opdyke arXiv preprint arXiv:1406.0389, 2014 | 25 | 2014 |
| Operational risk capital estimation and planning: exact sensitivity analysis and business decision making using the influence function JD Opdyke, A Cavallo Operational Risk: New Frontiers Explored, Risk Books, ed. E. Davis, London …, 2012 | 8 | 2012 |
| Two-sample permutation tests J Opdyke US Patent App. 09/944,249, 2003 | 7 | 2003 |
| Fast, accurate, straightforward extreme quantiles of compound loss distributions JD Opdyke arXiv preprint arXiv:1610.03718, 2016 | 5 | 2016 |
| A single, powerful, nonparametric statistic for continuous-data telecommunications parity testing JD Opdyke Journal of Modern Applied statistical methods 4, 372-393, 2005 | 3 | 2005 |
| Full probabilistic control for direct and robust, generalized and targeted stressing of the correlation matrix (Even When Eigenvalues are Empirically Challenging) JD Opdyke QuantMinds/RiskMinds September, 22-23, 2020 | 2 | 2020 |
| Bootstraps, permutation tests, and sampling orders of magnitude faster using SAS® JD Opdyke Wiley Interdisciplinary Reviews: Computational Statistics 5 (5), 391-405, 2013 | 2 | 2013 |
| Better capital planning via exact sensitivity analysis using the influence function JD Opdyke presentation at the American Bankers Association: Operational Risk Modeling …, 2012 | 2 | 2012 |
| Robust statistics vs. mle for oprisk severity distribution parameter estimation JD Opdyke American Bankers Association Operational Risk Modeling Forum, 2011 | 2 | 2011 |
| Much faster bootstraps using SAS® JD Opdyke InterStat, October, 2010 | 2 | 2010 |
| Misuse of the ‘modified’t statistic in regulatory telecommunications JD Opdyke Telecommunications Policy 28 (11), 821-866, 2004 | 2 | 2004 |
| Getting Extreme VaR Right: Eliminating Convexity and Approximation Biases Under Heavy-tailed, Moderately-Sized Samples (Presentation Slides) JD Opdyke Moderately-Sized Samples (Presentation Slides)(November 27, 2017), 2017 | 1 | 2017 |
| Permutation tests (and sampling without replacement) orders of magnitude faster using SAS® JD Opdyke InterStat, January, 2011 | 1 | 2011 |
| A Powerful and Robust Nonparametric Statistic for Joint Mean-Variance Quality Control JD Opdyke InterStat, September, 2009 | 1 | 2009 |
| Beating the Correlation Breakdown: Robust Inference and Fully Flexible Scenarios and Stress Testing for Financial Portfolios (Presentation Slides) JD Opdyke Beating the Correlation Breakdown: Robust Inference and Fully Flexible …, 2022 | | 2022 |
| Beating the Correlation Breakdown (for Pearsons', Kendall's, Spearman's, and MORE!): Robust Inference and Flexible Scenarios and Stress Testing for Financial Portfolios JD Opdyke Available at SSRN 4056268, 2021 | | 2021 |