Research
Bayesian Theory and Applications
AIQ: People and Machines Smarter Together
Deep Learning (with V. Sokolov).
Deep Learning Computational Aspects (with V. Sokolov).
Deep Learning Factor Alpha (with G. Feng and J. Xu).
Deep Learning for Predicting Asset Returns (with G. Feng and J. He).
Posterior Concentration of Sparse Deep Learning (with V. Rockova).
Weighted Bayesian Bootstrap for Scalable Bayes(with M. Newton and J. Xu).
Bayesian Hypothesis Testing: Redux(with H. F. Lopes).
Statistical Sparsity (with P. McCullagh).
Gaussian Tail Inflation (with P. McCullagh).
van Dantzig pairs, Wald couples and Hadamard Factorisation
Deep Learning: A Bayesian Perspective (with V. Sokolov). Bayesian Analysis.
Deep Learning for Spatio-Temporal Modeling (with M. Dixon and V. Sokolov).
Deep Learning in Finance (with J.B. Heaton and J. Witte). Applied Stochastic Models.
Deep Learning for Short-Term Traffic Flow Prediction (with V. Sokolov). IEEE Transportation Record, C.
Bayesian Tracking of Traffic Flows (with V. Sokolov). IEEE Transactions on Intelligent Transportation Systems
Bayesian L0-regularisation Least Squares (with L. Sun).
Bayesian Analysis for Mixed-Poisson Count Data (with T. Atekin and R. Soyer).
From Least Squares to Signal Processing and Particle Filtering (with N. Singpurwalla and R. Soyer). Technometrics
Lasso Meets Horseshoe (with A. Bhadra, J. Datta, and B. Willard). Prediction Risk for Global-Local Shrinkage Regression (with A. Bhadra, J. Datta, Y. Li and B. Willard)
Horseshoe-Like Sparsity Priors (with A. Bhadra, J. Datta and B. Willard). Why Indexing Works (with J.B. Heaton and J. Witte). Applied Stochastic Models. Augmented Probability Simulation for Accelerated Life Test Design (with R. Soyer). Applied Stochastic Models, 33(3), 322-332. Sequential Bayesian Learning for SV with Variance-Gamma Jumps in Returns (with H. Lopes and S. Warty). Applied Stochastic Models Deep Portfolio Theory (with J.B. Heaton and J. Witte) Mixtures, Envelopes and Hierarchical Duality (with J. Scott). Journal of Royal Statistical Society, B., 78(4), 701-727. The Horseshoe+ Estimator of Ultra Sparse Signals (with A. Bhadra, J. Datta and B. Willard). Bayesian Analysis. Sequential Bayesian Learning for Merton's Jump SV Model (with E. Jacquier and V. Sokolov) A BayesMAP Trend Filter (with V. Sokolov) The Market for EPL Odds (with G. Feng and J. Xu). Journal of Quantitative Analysis in Sports, 12(4), 167-178. Bayesian Regularisation of Predictive Regressions (with G. Feng) Sequential Bayesian Analysis for Poisson Count Data (with T. Atekin and R. Soyer).
Poisson Hyper-Geometric Beta Models (with T. Atekin and R. Soyer).
Negative Conditional Probabilities (with N. Singpurwalla and R. Soyer).
Global-Local Mixtures (with A. Bhadra, J. Datta and B. Willard)
Particle Learning for Fat-tailed Distributions (with H. Lopes). Econometric Reviews, 33, 1666-1691 A Deconvolution Path for Mixtures (2015) (with O. Padilla and J. Scott) A Statistical Theory of Deep Learning (2015) (with M. Heidari and B. Willard). Proximal Algorithms in Statistics and Machine Learning (2015) (with J. Scott and B. Willard). Statistical Science, 30(4), 559-581. Default Bayesian Analysis with Global-Local Shrinkage Priors (2015) (with A. Bhadra, J. Datta and B. Willard)
Bayesian Analysis of the LWR Model (2015) (with V. Sokolov). Annals of Applied Statistics, 9(4), 1864-1885 Bayes Rule for Meijer G-functions (2015) (with B. Willard)
Waiting Time Econometrics for Portfolio Allocation (2015) (with D. Dobrev). Vertical Likelihood Monte Carlo (2015) (with J. Scott)
A Bellman View of Jesse Livermore (2015) (with J. Witte). Chance, 28(1), 27-31. The Implied Volatility of a Sports Game (2015) (with H. Stern). Journal of Quantitative Analysis in Sports, 11(3), 145-153. Bayesian Estimation of Nonlinear Equilibrium Models with Random Coefficients (2015) (with A. Gron and V. Viard). Applied Stochastic Models, 31(4), 435-456. Sequential Learning, Predictability, and Optimal Portfolio Returns (2014) (with M. Johannes and A. Korteweg). Journal of Finance, 69(2), 611-644. The Bayesian Bridge (2014) (with J. Scott and J. Windle). Journal of Royal Statistical Society, B, 76(4), 713-733. Augmented MCMC Simulation for Two-Stage Stochastic Programs with Recourse (2014) (with T. Ekin and R. Soyer). Decision Analysis, 11(4), 250-264.
Analyzing Risky Choices: Q-Learning for Deal-No Deal (2014) (with L. Korsos). Applied Stochastic Models, 30(3), 258-270. Bayesian Instrumental Variables: Priors and Likelihoods (2014) (with H. Lopes). Econometric Reviews, 33:1-4, 100-121. Sampling Polya-Gamma random variates: alternate and approximate techniques (2014) (with J. Scott and J. Windle). . Bayesian Inference for Logistic models using Polya-Gamma latent variables (2013) (with J. Scott and J. Windle). Journal of American Statistical Association, 108, 1339-1349. Data Augmentation for non-Gaussian Regression Models using Variance-Mean Mixtures (2013) (with J. Scott). Biometrika, 100(2), 459-471. Split Sampling: Expectations, Normalisation and Rare Events (2013) (with J. Birge and C. Chang)
Optimisation via Slice Sampling (2013) (with J. Birge)
Asset Allocation: a Bayesian Perspective (2013) (with E. Jacquier). Hierarchical Models and MCMC, 501-516. Tracking Epidemics with Google Flu Trends and a State Space SEIR Model (2012) (with V. Dukic and H. Lopes). Journal of American Statistical Association, 107, 1410-1426. Explosive Volatility: A Model of Financial Contagion (2012) (with J. Scott). Default Bayesian Analysis for Multi-way tables: a Data Augmentation Approach (2012) (with J. Scott). Smart Money, Dumb Money: Learning Type from Price (2012) (with J.B. Heaton). Local Shrinkage Rules, Levy Processes and Regularized Regression (2012) (with J. Scott). Journal of Royal Statistical Society, B, 74(2), 287-311. Good, Great or Lucky? Screening for firms with sustained superior performance using heavy-tailed priors (2012) (with J. Scott). Annals of Applied Statistics, 6(1), 161-185. Simulation-based Regularised Logistic Regression (2012) (with R. Gramacy). Bayesian Analysis, 7(3), 567-590. On the Half-Cauchy prior for a Global Scale parameter (2012) (with J. Scott). Bayesian Analysis, 7(4), 770-796. Optimal Portfolio Choice with Stochastic Volatility (2012) (with A.Gron and B. Jorgensen). Applied Stochastic Models, 28(1), 1-15..
Predictive Macrofinance with Dynamic Partition Models (2011) (with D. Zantedeschi and P. Damien). Journal of American Statistical Association, 106, 427-439. Dynamic Trees for Learning and Design (2011) (with R. Gramacy and M. Taddy). Journal of American Statistical Association, 106, 109-123. Data Augmentation for Support Vector Machines (2011) (with S. Scott). Invited paper with discussion. Bayesian Analysis, 6, 1-49. Optimal Portfolio Choice with Stochastic Volatility (2011) (with A.Gron and B. Jorgensen). Applied Stochastic Models.
Large-Scale Simultaneous Testing with Hypergeometric Inverted-Beta Briors (2011) (with J. Scott).
Shrink Globally, Act Locally: sparse Bayesian estimation and prediction (2011) (with J. Scott). Invited paper with discussion: Bayesian Statistics 9, 501-539. Particle Learning for Sequential Bayesian Computation (2011) (with H. Lopes et al). Invited paper with discussion: Bayesian Statistics 9, 317-360. Corporate Credit Spreads and Parameter Uncertainty (2011) (with A. Korteweg). A Simulation-based approach to Stochastic Dynamic Programming (2011) (with M. Sorensen). Applied Stochastic Models, 27(2), 151-163. Bayesian Methods in Finance (2011) (with E. Jacquier). Handbook of Bayesian Econometrics (eds H. van Dyk et al), 439-513. Nonlinear Filtering and Robust Learning (2011) (with L. Hansen and T. Sargent). Particle Learning of Gaussian process models for Sequential Design and Optimization (2010) (with R. Gramacy). Journal of Computational and Graphical Statistics, 20(1), 102-118.. Particle Learning for General Mixtures (2010) (with C. Carvalho, H. Lopes and M.Taddy). Bayesian Analysis, 5, 709-740. Nonlinear Filtering and Learning (2010) (with M. Johannes and S-M. Yae). Quantile Filtering and Learning (2010) (with M. Johannes and S-M. Yae). Bayesian Inference for Stochastic Volatility Modeling (2010) (with H. F. Lopes). Risk, 515-551. The Horseshoe Estimator of Sparse Signals (2010) (with C. Carvalho and J. Scott). Biometrika, 97(2), 465-480. Bayesian Computation in Finance (2010) (with R. McCulloch et al). In Frontiers of Bayesian Decision Analysis, 383-396. Simulation-Based Estimation in Portfolio Selection (2010) (with E. Jacquier). In Frontiers of Bayesian Decision Analysis, 396-410. Particle Learning and Smoothing (2010) (with C. Carvalho, M. Johannes and H. Lopes) Statistical Science, 25, 88-106. Maximum Expected Utility via MCMC (2009) (with E. Jacquier and M. Johannes). MCMC Methods for Financial Econometrics (2009) (with M. Johannes). Handbook of Financial Econometrics (eds Ait-Sahalia and L.P. Hansen), 1-72. Optimal Filtering of Jump-Diffusions: Extracting Latent States from Asset Prices (2009) (with M. Johannes and J. Stroud). Review of Financial Studies, 22(7), 2259-2299. Particle Filtering (2009) (with M. Johannes). Handbook of Financial Statistics (eds T. Andersen et al), 1015-1028. Markov Chain Monte Carlo (2009) (with M. Johannes). Handbook of Financial Statistics (eds T. Andersen et al), 1001-1015. Extracting SP500 and Nasdaq Volatility: the Credit Crisis of 2007-2008 (2009) (with H. Lopes). Handbook of Applied Bayesian Analysis (eds O'Hagan et al), 319-342. Handling Sparsity via the Horseshoe (2009) (with C. Carvalho and J. Scott). Journal of Machine Learning Research, WICP5(AIStats), 5, 73-80. Practical Filtering with Sequential Parameter Learning (2008) (with J. Stroud and P. Mueller). Journal of Royal Statistical Society, B, 70, 413-128. MCMC Maximum Likelihood for Latent State Models (2007) (with E. Jacquier and M. Johannes) Journal of Econometrics, 127, 615-640. Exact Particle Filtering and Learning (2007) (with M. Johannes). A Bayesian Analysis of Fat-tailed Stochastic Volatility Models with Correlated Errors (2004) (with E. Jacquier and P. Rossi). Journal of Econometrics, 122(1), 185-212. Practical Filtering for Stochastic Volatility Models (2004) (with J. Stroud and P. Mueller). State Space Modeling. The Impact of Jumps and Volatility in Returns (2003) (with B. Eraker and M. Johannes) Journal of Finance, 58, 3, 1269-1300. Bayesian Inference for Derivative Prices (2003) (with J. Stroud). Bayesian Statistics, 7, 641-650. Nonlinear State Space Models with State Dependent Variances (2003) (with P. Mueller and J. Stroud). Journal of American Statistical Association, 98, 377-386. Sequential Optimal Portfolio Allocation: Market and Volatility Timing (2003) (with M. Johannes and J. Stroud). Affine State Dependent Variance Models (2002) (with P. Mueller and J. Stroud). Bayesian Analysis of Stochastic Volatility Models (2002) (with E. Jacquier and P. Rossi). Reprinted. J. Business and Economic Statistics, 1, 69-87. Memoryless Trading (2000) (with W. Eckhardt). Journal of Risk Finance, 4, 1-9. A Bayesian Analysis of the Multinomial Probit Model with Fully Identified Parameters (2000) (with R. McCulloch and P. Rossi). Journal of Econometrics, 173-193. Bayesian Portfolio Selection: An Analysis of the SP500 index 1970-1996 (2000) (with B. Tew). J. Business and Economic Statistics, 18, 164-174. Investing in Leveraged Index funds (1999) (with J. Yasumoto). Journal of Risk Finance, 1, 41-51. State Dependent Jump Models: How Do U.S. Equity Indices Jump? (1998) (with M. Johannes and R. Kumar). Diagnostics for Model Criticism (1996) (with C. Carota and G. Parmigiani). Journal of American Statistical Association, 91, 753-763. Convergence of Markov Chain Monte Carlo Algorithms (1995). (Invited paper with discussion). Bayesian Statistics 5, 297-321. Bayesian Analysis of Stochastic Volatility Models (1994) (with E. Jacquier and P. Rossi). Invited paper with discussion. J. Business and Economic Statistics, 12, 371-417. Bayes factors for Discrete Observations for Diffusion Processes (1994) (with G.O. Roberts). Biometrika, 81, 11-26. On the Geometric Convergence of the Gibbs Sampler (1994) (with G.O. Roberts). Journal of Royal Statistical Society, B, 377-384. Sampling from Log-Concave Distributions (1994) (with A. Frieze and R. Kannan). Annals of Applied Probability, 4, 812-837. A Utility Based Approach to Information for Stochastic Differential Equations (1993) (with G.O. Roberts). Stochastic Processes and their Applications, 48, 341-356. A Note on the Residual Entropy Function (1993). (with P. Muliere and G. Parmigiani). Probability and Engineering Information Science, 7, 413-420. A Bayesian Perspective on the Design of Accelerated Life Tests (1993). In: Advances in Reliability (ed. A. Basu), North-Holland. Shannon information and Bayesian Design for Prediction in Accelerated Life Testing (1993) (with N. Singpurwalla and I. Verdinelli). In: Reliability and Decision making (eds R. Barlow et al), 247-256. Bayesian Model Criticism (1993) (with C. Carota and G. Parmigiani). Proceedings of the Statistical Association. On the Expected Amount of Information from a Non-linear Model (1992). Journal of Statistical Society, B, 54, 889-895. A Monte Carlo Approach to Non-Normal and Non-Linear State Space Modeling (1992) (with B.P. Carlin and D.S. Stoffer). Journal of American Statistical Association, 87, 493-500. Monte Carlo Bayesian Methods for Discrete Regression Models and Categorical Time Series (1992) (with B. P. Carlin). Bayesian Statistics 4, 577-586. Bayesian Design for Random Walk Barriers (1992) (with G. Parmigiani). Bayesian Statistics 4, 715-723. An Expected Utility Approach to Influence Diagnostics (1991) (with B.P. Carlin). Journal of American Statistical Association, 86, 1013-1021. Inference for Non-Conjugate Bayesian Models using the Gibbs Sampler (1991) (with B.P. Carlin). Canadian Journal of Statistics, 19, 399-405. A Bayesian Decision Theoretic Characterization of Poisson Processes (1991) (with G.O. Roberts). Journal of Royal Statistical Society, B, 53, 675-682. A Representation of the Posterior Mean for a Location Model (1991). Biometrika, 78, 426-430. The Diagnosis of Breast Carcinoma in Young Women (1991) (with A. Yelland et al). British Medical J., 302, 618-620. Prior Distributions for the Bivariate Binomial (1990) (with L.A. Wasserman). Biometrika, 77, 901-905. Bayesian Perspectives on Statistical Modeling (1988). PhD Thesis.