Operations Research
http://lists.repec.org/mailman/listinfo/nep-ore
Operations Research
2018-09-17
Hamiltonian Sequential Monte Carlo with Application to Consumer Choice Behavior
http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-618&r=ore
Practical use of nonparametric Bayesian methods requires the availability of efficient algorithms for implementation for posterior inference. The inherently serial nature of Markov Chain Monte Carlo (MCMC) imposes limitations on its efficiency and scalability. In recent years there has been a surge of research activity devoted to developing alternative implementation methods that target parallel computing environments. Sequential Monte Carlo (SMC), also known as a particle filter, has been gaining popularity due to its desirable properties. SMC uses a genetic mutation-selection sampling approach with a set of particles representing the posterior distribution of a stochastic process. We propose to enhance the performance of SMC by utilizing Hamiltonian transition dynamics in the particle transition phase, in place of random walk used in the previous literature. We call the resulting procedure Hamiltonian Sequential Monte Carlo (HSMC). Hamiltonian transition dynamics has been shown to yield superior mixing and convergence properties relative to random walk transition dynamics in the context of MCMC procedures. The rationale behind HSMC is to translate such gains to the SMC environment. We apply both SMC and HSMC to a panel discrete choice model with a nonparametric distribution of unobserved individual heterogeneity. We contrast both methods in terms of convergence properties and show the favorable performance of HSMC.
Martin Burda
Remi Daviet
Particle filtering, Bayesian nonparametrics, mixed panel logit, discrete choice
2018-09-12
Testing for bubbles in cryptocurrencies with time-varying volatility
http://d.repec.org/n?u=RePEc:cor:louvco:2018019&r=ore
The recent evolution of cryptocurrencies has been characterized by bubble-like behavior and extreme volatility. While it is difficult to assess an intrinsic value to a specific cryptocurrency, one can employ recently proposed bubble tests that rely on recursive applications of classical unit root tests. This paper extends this approach to the case where volatility is time varying, assuming a deterministic long-run component that may take into account a decrease of unconditional volatility when the cryptocurrency matures with a higher market dissemination. Volatility also includes a stochastic short-run component to capture volatility clustering. The wild bootstrap is shown to correctly adjust the size properties of the bubble test, which retains good power properties. In an empirical application using eleven of the largest cryptocurrencies and the CRIX index, the general evidence in favor of bubbles is confirmed, but much less pronounced than under constant volatility.
HAFNER Christian,
cryptocurrencies; speculative bubbles; wild bootstrap; volatility
2018-07-25
Communicaiton games with optional verification
http://d.repec.org/n?u=RePEc:cor:louvco:2018013&r=ore
We analyse a Sender-Receiver game in which the Sender can choose between a costless cheap-talk message and a costly verifiable message. The Sender knows the true state of the world, while the Receiver only learns about the state through the message of the Sender. The utility of both players depends on an action the Receiver chooses. We keep the assumptions about the utility functions and about the messages to a minimum and state conditions for fully revealing equilibria. Under the assumption of "smooth" preferences and utility functions we show that a fully revealing equilibrium in which the Sender uses both her message types can only exist as long as the state space and action space are discrete. We illustrate this result for the classical example of quadratic loss utilities. In a continuous setting we show that there can only exist a fully revealing equilibrium in which the Sender uses different message types in different states if we allow for costless verification in some states of the world or if the utility function of at least one player is discontinuous.
SCHOPOHL Simon,
cheap-talk, communication, costly disclosure, full revelation, Sender-Receiver game, verifiable information
2018-04-25
A Class of Time-Varying Parameter Structural VARs for Inference under Exact or Set Identification
http://d.repec.org/n?u=RePEc:fip:fedcwp:1811&r=ore
This paper develops a new class of structural vector autoregressions (SVARs) with time-varying parameters, which I call a drifting SVAR (DSVAR). The DSVAR is the first structural time-varying parameter model to allow for internally consistent probabilistic inference under exact—or set—identification, nesting the widely used SVAR framework as a special case. I prove that the DSVAR implies a reduced-form representation, from which structural inference can proceed similarly to the widely used two-step approach for SVARs: beginning with estimation of a reduced form and then choosing among observationally equivalent candidate structural parameters via the imposition of identifying restrictions. In a special case, the implied reduced form is a tractable known model for which I provide the first algorithm for Bayesian estimation of all free parameters. I demonstrate the framework in the context of Baumeister and Peersman’s (2013b) work on time variation in the elasticity of oil demand.
Bognanni, Mark
structural vector autoregressions; time-varying parameters; Gibbs sampling; stochastic volatility; Bayesian inference;
2018-09-11
Identification of structural multivariate GARCH models
http://d.repec.org/n?u=RePEc:cor:louvco:2018020&r=ore
Multivariate GARCH models are widely used to model volatility and correlation dynamics of nancial time series. These models are typically silent about the transmission of implied orthogonalized shocks to vector returns. We propose a loss statistic to discriminate in a data-driven way between alternative structural assumptions about the transmission scheme. In its structural form, a four dimensional system comprising US and Latin American stock market returns points to a substantial volatility transmission from the US to the Latin American markets. The identified structural model improves the estimation of classical measures of portfolio risk, as well as corresponding variations.
HAFNER Christian,
HERWARTZ Helmut,
MAXAND Simone,
structural innovations; identifying assumptions; MGARCH; portfolio risk; volatility transmission
2018-07-25