Papers by Cristian Pasarica
Scandinavian Journal of Statistics, Mar 1, 2003
This paper characterizes the asymptotic behaviour of the likelihood ratio test statistic (LRTS) f... more This paper characterizes the asymptotic behaviour of the likelihood ratio test statistic (LRTS) for testing homogeneity (i.e. no mixture) against gamma mixture alternatives. Under the null hypothesis, the LRTS is shown to be asymptotically equivalent to the square of Davies's Gaussian process test statistic and diverges at a log log n rate to infinity in probability. Based on the asymptotic analysis, we propose and demonstrate a computationally efficient method to simulate the null distributions of the LRTS for small to moderate sample sizes.
Social Science Research Network, 2007
Using existing theory on efficient jumping rules and on adaptive MCMC, we construct and demonstra... more Using existing theory on efficient jumping rules and on adaptive MCMC, we construct and demonstrate the effectiveness of a workable scheme for improving the efficiency of Metropolis algorithms. A good choice of the proposal distribution is crucial for the rapid convergence of the Metropolis algorithm. In this paper, given a family of parametric Markovian kernels, we develop an algorithm for optimizing the kernel by maximizing the expected squared jumped distance, an objective function that characterizes the Markov chain under its d-dimensional stationary distribution. The algorithm uses the information accumulated by a single path and adapts the choice of the parametric kernel in the direction of the local maximum of the objective function using multiple importance sampling techniques. We follow a two-stage approach: a series of adaptive optimization steps followed by an MCMC run with fixed kernel. It is not necessary for the adaptation itself to converge. Using several examples, we demonstrate the effectiveness of our method, even for cases in which the Metropolis transition kernel is initialized at very poor values.
The American Statistician, May 1, 2002
Statisticians recommend graphical displays but often use tables to present their own research res... more Statisticians recommend graphical displays but often use tables to present their own research results. Could graphs do better? We study the question by going through the tables in a recent issue of the Journal of the American Statistical Association. We show how it is possible to improve the presentations using graphs that actually take up less space than the original tables. We find a particularly effective tool to be multiple repeated line plots, with comparisons of interest connected by lines and separate comparisons isolated on different plots.
Statisticians recommend graphical displays but often use tables to present their own research res... more Statisticians recommend graphical displays but often use tables to present their own research results. Could graphs do better? We study the question by going through the tables in a recent issue of the Journal of the American Statistical Association. We show how it is possible to improve the presentationsusing graphs that actually take up less space than the original tables. We nd a particularly effective tool to be multiple repeated line plots, with comparisons of interest connected by lines and separate comparisons isolated on different plots.
Let''s practice what we preach: using graphs instead of tables
The “Retirement” Problem
Viens/Handbook of High-Frequency Finance, 2011
Scandinavian Journal of Statistics, 2003
This paper characterizes the asymptotic behaviour of the likelihood ratio test statistic (LRTS) f... more This paper characterizes the asymptotic behaviour of the likelihood ratio test statistic (LRTS) for testing homogeneity (i.e. no mixture) against gamma mixture alternatives. Under the null hypothesis, the LRTS is shown to be asymptotically equivalent to the square of Davies's Gaussian process test statistic and diverges at a log log n rate to infinity in probability. Based on the asymptotic analysis, we propose and demonstrate a computationally efficient method to simulate the null distributions of the LRTS for small to moderate sample sizes.
SSRN Electronic Journal, 2007
Using existing theory on efficient jumping rules and on adaptive MCMC, we construct and demonstra... more Using existing theory on efficient jumping rules and on adaptive MCMC, we construct and demonstrate the effectiveness of a workable scheme for improving the efficiency of Metropolis algorithms. A good choice of the proposal distribution is crucial for the rapid convergence of the Metropolis algorithm. In this paper, given a family of parametric Markovian kernels, we develop an algorithm for optimizing the kernel by maximizing the expected squared jumped distance, an objective function that characterizes the Markov chain under its d-dimensional stationary distribution. The algorithm uses the information accumulated by a single path and adapts the choice of the parametric kernel in the direction of the local maximum of the objective function using multiple importance sampling techniques. We follow a two-stage approach: a series of adaptive optimization steps followed by an MCMC run with fixed kernel. It is not necessary for the adaptation itself to converge. Using several examples, we demonstrate the effectiveness of our method, even for cases in which the Metropolis transition kernel is initialized at very poor values.
Statisticians recommend graphical displays but often use tables to present their own research res... more Statisticians recommend graphical displays but often use tables to present their own research results. Could graphs do better? We study the question by going through the tables in a recent issue of the Journal of the American Statistical Association. We show how it is possible to improve the presentationsusing graphs that actually take up less space than the original tables. We nd a particularly effective tool to be multiple repeated line plots, with comparisons of interest connected by lines and separate comparisons isolated on different plots.
Physica A: Statistical Mechanics and its Applications, 2009
The empirical relationship between the return of an asset and the volatility of the asset has bee... more The empirical relationship between the return of an asset and the volatility of the asset has been well documented in the financial literature. Named the leverage effect or sometimes risk-premium effect, it is observed in real data that, when the return of the asset decreases, the volatility increases and vice-versa. Consequently, it is important to demonstrate that any formulated model for the asset price is capable to generate this effect observed in practice. Furthermore, we need to understand the conditions on the parameters present in the model that guarantee the apparition of the leverage effect. In this paper we analyze two general specifications of stochastic volatility models and their capability of generating the perceived leverage effect. We derive conditions for the apparition of leverage effect in both of these stochastic volatility models. We exemplify using stochastic volatility models used in practice and we explicitly state the conditions for the existence of the leverage effect in these examples.
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Papers by Cristian Pasarica