@article{pelletier_wei_2023, title={A Stochastic Price Duration Model for Estimating High-Frequency Volatility}, ISSN={["1479-8417"]}, DOI={10.1093/jjfinec/nbad029}, abstractNote={Abstract}, journal={JOURNAL OF FINANCIAL ECONOMETRICS}, author={Pelletier, Denis and Wei, Wei}, year={2023}, month={Oct} }
 @article{clark_pelletier_2022, title={Impact of defaults on participation in state supplemental retirement savings plans}, volume={21}, ISSN={["1475-3022"]}, DOI={10.1017/S1474747220000347}, abstractNote={Abstract}, number={1}, journal={JOURNAL OF PENSION ECONOMICS & FINANCE}, author={Clark, Robert L. and Pelletier, Denis}, year={2022}, month={Jan}, pages={22–37} }
 @article{dufoura_pelletier_2022, title={Practical Methods for Modeling Weak VARMA Processes: Identification, Estimation and Specification With a Macroeconomic Application}, volume={40}, ISSN={["1537-2707"]}, DOI={10.1080/07350015.2021.1904960}, abstractNote={Abstract We consider the problem of developing practical methods for modelling weak VARMA processes. We first propose new identified VARMA representations, the diagonal MA equation form and the final MA equation form, where the MA operator is either diagonal or scalar. Both these representations have the important feature that they constitute relatively simple modifications of a VAR model (in contrast with the echelon representation). Second, for estimating VARMA models, we develop computationally simple methods which only require linear regressions. The asymptotic properties of the estimator are derived under weak hypotheses on the innovations (uncorrelated and strong mixing), in order to broaden the class of models to which it can be applied. Third, we present a modified information criterion which yields consistent estimates of the orders under the proposed representations. The estimation methods are studied by simulation. To demonstrate the importance of using VARMA models to study multivariate time series, we compare the impulse-response functions and the out-of-sample forecasts generated by VARMA and VAR models. The proposed methodology is applied to a six-variable macroeconomic model of monetary policy, based on the U.S. monthly data over the period 1962–1996. The results demonstrate the advantages of using the VARMA methodology for impulse response estimation and forecasting, in contrast with standard VAR models.}, number={3}, journal={JOURNAL OF BUSINESS & ECONOMIC STATISTICS}, author={Dufoura, Jean-Marie and Pelletier, Denis}, year={2022}, month={Jun}, pages={1140–1152} }
 @article{inoue_jin_pelletier_2021, title={Local-Linear Estimation of Time-Varying-Parameter GARCH Models and Associated Risk Measures}, volume={19}, ISSN={["1479-8417"]}, DOI={10.1093/jjfinec/nbaa026}, abstractNote={Abstract}, number={1}, journal={JOURNAL OF FINANCIAL ECONOMETRICS}, author={Inoue, Atsushi and Jin, Lu and Pelletier, Denis}, year={2021}, pages={202–234} }
 @article{mccausland_miller_pelletier_2021, title={Multivariate stochastic volatility using the HESSIAN method}, volume={17}, ISSN={["2452-3062"]}, DOI={10.1016/j.ecosta.2020.07.002}, abstractNote={A new method is proposed for the analysis of multivariate stochastic volatility models, based on efficient draws of volatility from its conditional posterior distribution. It applies to models with several kinds of cross-sectional dependence. Full autoregression and covariance matrices imply dependent volatility series. Mean factor structure allows conditional correlations to vary in time and covary with conditional variances; factors are conditionally Student’s t, allowing for tail dependence across assets, with factor-specific degrees of freedom. Given factors, returns have heterogeneous Student’s t marginals; a copula completes their joint distribution. Volatility series are drawn as a block, one series at a time. An application using daily returns data for ten currencies shows that all features of the model are important.}, journal={ECONOMETRICS AND STATISTICS}, author={McCausland, William and Miller, Shirley and Pelletier, Denis}, year={2021}, month={Jan}, pages={76–94} }
 @article{peers_gregg_lindell_pelletier_romerio_joyner_2021, title={The Economic Effects of Volcanic Alerts-A Case Study of High-Threat US Volcanoes}, volume={41}, ISSN={["1539-6924"]}, DOI={10.1111/risa.13702}, abstractNote={Abstract}, number={10}, journal={RISK ANALYSIS}, author={Peers, Justin B. and Gregg, Christopher E. and Lindell, Michael K. and Pelletier, Denis and Romerio, Franco and Joyner, Andrew T.}, year={2021}, month={Oct}, pages={1759–1781} }
 @article{pelletier_tunc_2019, title={Endogenous Life-Cycle Housing Investment and Portfolio Allocation}, volume={51}, ISSN={["1538-4616"]}, DOI={10.1111/jmcb.12521}, abstractNote={Abstract}, number={4}, journal={JOURNAL OF MONEY CREDIT AND BANKING}, author={Pelletier, Denis and Tunc, Cengiz}, year={2019}, month={Jun}, pages={991–1019} }
 @article{krishnamurthy_pelletier_warr_2018, title={Inflation and equity mutual fund flows}, volume={37}, ISSN={["1878-576X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85038835804&partnerID=MN8TOARS}, DOI={10.1016/j.finmar.2017.12.001}, abstractNote={We document a negative relation between inflation and aggregate equity mutual fund flows and hypothesize that this relation is partly due to inflation illusion on the part of investors. Inflation illusion occurs when investors fail to incorporate the effect of inflation into their estimates of nominal growth rates. Consequently, they lower their estimates of the intrinsic values of stocks and move their assets away from equities. Our results are robust to controls for alternative explanations such as inflation proxying for poorer future real cash flow growth and periods of higher inflation being associated with higher equity risk premia.}, journal={JOURNAL OF FINANCIAL MARKETS}, author={Krishnamurthy, Srinivasan and Pelletier, Denis and Warr, Richard S.}, year={2018}, month={Jan}, pages={52–69} }
 @article{clark_pathak_pelletier_2018, title={Supplemental Retirement Savings Plans in the Public Sector: Participation and Contribution Decisions by School Personnel}, volume={39}, ISSN={["1936-4768"]}, DOI={10.1007/s12122-018-9270-2}, number={4}, journal={JOURNAL OF LABOR RESEARCH}, author={Clark, Robert L. and Pathak, Aditi and Pelletier, Denis}, year={2018}, month={Dec}, pages={383–404} }
 @article{pelletier_wei_2016, title={The Geometric-VaR Backtesting Method}, volume={14}, ISSN={["1479-8417"]}, DOI={10.1093/jjfinec/nbv015}, abstractNote={This article develops a new test to evaluate value-at-risk (VaR) forecasts. VaR is a standard risk measure widely utilized by financial institutions and regulators, yet estimating VaR is a challenging problem, and popular VaR forecast relies on unrealistic assumptions. Hence, assessing the performance of VaR is of great importance. We propose the geometric-VaR test which utilizes the duration between the violations of VaR as well as the value of VaR. We conduct a Monte Carlo study based on desk-level data and we find that our test has high power against various alternatives.}, number={4}, journal={JOURNAL OF FINANCIAL ECONOMETRICS}, author={Pelletier, Denis and Wei, Wei}, year={2016}, pages={725–745} }
 @article{berkowitz_christoffersen_pelletier_2011, title={Evaluating value-at-risk models with desk-level data}, volume={57}, DOI={10.1287/mnsc.1080.0964}, abstractNote={ We present new evidence on disaggregated profit and loss (P/L) and value-at-risk (VaR) forecasts obtained from a large international commercial bank. Our data set includes the actual daily P/L generated by four separate business lines within the bank. All four business lines are involved in securities trading and each is observed daily for a period of at least two years. Given this unique data set, we provide an integrated, unifying framework for assessing the accuracy of VaR forecasts. We use a comprehensive Monte Carlo study to assess which of these many tests have the best finite-sample size and power properties. Our desk-level data set provides importance guidance for choosing realistic P/L-generating processes in the Monte Carlo comparison of the various tests. The conditional autoregressive value-at-risk test of Engle and Manganelli (2004) performs best overall, but duration-based tests also perform well in many cases. }, number={12}, journal={Management Science}, author={Berkowitz, J. and Christoffersen, P. and Pelletier, D.}, year={2011}, pages={2213–2227} }
 @article{hall_pelletier_2011, title={NONNESTED TESTING IN MODELS ESTIMATED VIA GENERALIZED METHOD OF MOMENTS}, volume={27}, ISSN={["0266-4666"]}, DOI={10.1017/s0266466610000344}, abstractNote={We analyze the limiting distribution of the Rivers and Vuong (2002, Econometrics Journal 5, 1–39) statistic for choosing between two competing dynamic models based on a comparison of generalized method of moments minimands. It is shown that (i) if both models are misspecified then the statistic has a standard normal distribution under the null hypothesis of equal fit but the ranking could be determined by the choice of the weighting matrix; (ii) if both models are correctly specified or locally misspecified then the limiting distribution of the test statistic is nonstandard under the null.}, number={2}, journal={ECONOMETRIC THEORY}, author={Hall, Alastair R. and Pelletier, Denis}, year={2011}, month={Apr}, pages={443–456} }
 @article{mccausland_miller_pelletier_2011, title={Simulation smoothing for state-space models: A computational efficiency analysis}, volume={55}, ISSN={["1872-7352"]}, DOI={10.1016/j.csda.2010.07.009}, abstractNote={Simulation smoothing involves drawing state variables (or innovations) in discrete time state–space models from their conditional distribution given parameters and observations. Gaussian simulation smoothing is of particular interest, not only for the direct analysis of Gaussian linear models, but also for the indirect analysis of more general models. Several methods for Gaussian simulation smoothing exist, most of which are based on the Kalman filter. Since states in Gaussian linear state–space models are Gaussian Markov random fields, it is also possible to apply the Cholesky Factor Algorithm (CFA) to draw states. This algorithm takes advantage of the band diagonal structure of the Hessian matrix of the log density to make efficient draws. We show how to exploit the special structure of state–space models to draw latent states even more efficiently. We analyse the computational efficiency of Kalman-filter-based methods, the CFA, and our new method using counts of operations and computational experiments. We show that for many important cases, our method is most efficient. Gains are particularly large for cases where the dimension of observed variables is large or where one makes repeated draws of states for the same parameter values. We apply our method to a multivariate Poisson model with time-varying intensities, which we use to analyse financial market transaction count data.}, number={1}, journal={COMPUTATIONAL STATISTICS & DATA ANALYSIS}, author={McCausland, William J. and Miller, Shirley and Pelletier, Denis}, year={2011}, month={Jan}, pages={199–212} }
 @article{pelletier_mitasova_harmon_overton_2009, title={The effects of interdune vegetation changes on eolian dune field evolution: a numerical-modeling case study at Jockey's Ridge, North Carolina, USA}, volume={34}, ISSN={["1096-9837"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-69749085481&partnerID=MN8TOARS}, DOI={10.1002/esp.1809}, abstractNote={Abstract}, number={9}, journal={EARTH SURFACE PROCESSES AND LANDFORMS}, author={Pelletier, Jon D. and Mitasova, Helena and Harmon, Russell S. and Overton, Margery}, year={2009}, month={Jul}, pages={1245–1254} }
 @article{pelletier_2006, title={Regime switching for dynamic correlations}, volume={131}, ISSN={["1872-6895"]}, DOI={10.1016/j.jeconom.2005.01.013}, abstractNote={We propose a new model for the variance between multiple time series, the regime switching dynamic correlation. We decompose the covariances into correlations and standard deviations and the correlation matrix follows a regime switching model; it is constant within a regime but different across regimes. The transitions between the regimes are governed by a Markov chain. This model does not suffer from a curse of dimensionality and it allows analytic computation of multi-step ahead conditional expectations of the variance matrix when combined with the ARMACH model (Taylor (Modelling Financial Time Series. Wiley, New York) and Schwert (J. Finance 44(5) (1989) 1115)) for the standard deviations. We also present an empirical application which illustrates that our model can have a better fit of the data than the dynamic conditional correlation model proposed by Engle (J. Business Econ. Statist. 20(3) (2002) 339).}, number={1-2}, journal={JOURNAL OF ECONOMETRICS}, author={Pelletier, D}, year={2006}, pages={445–473} }
 @article{dufour_pelletier_renault_2006, title={Short run and long run causality in time series: inference}, volume={132}, ISSN={["1872-6895"]}, DOI={10.1016/j.jeconom.2005.02.003}, abstractNote={We propose methods for testing hypothesis of non-causality at various horizons, as defined in Dufour and Renault (Econometrica 66, (1998) 1099–1125). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses considered are nonlinear, the proposed methods only require linear regression techniques as well as standard Gaussian asymptotic distributional theory. Bootstrap procedures are also considered. For the case of integrated processes, we propose extended regression methods that avoid nonstandard asymptotics. The methods are applied to a VAR model of the US economy.}, number={2}, journal={JOURNAL OF ECONOMETRICS}, author={Dufour, Jean-Marie and Pelletier, Denis and Renault, Eric}, year={2006}, month={Jun}, pages={337–362} }