Estimation of covariance matrix via the sparse Cholesky factor with lasso

In this paper, we discuss a parsimonious approach to estimation of high-dimensional covariance matrices via the modified Cholesky decomposition with lasso. Two different methods are proposed. They are the equi-angular and equi-sparse methods. We use simulation to compare the performance of the proposed methods with others available in the literature, including the sample covariance matrix, the banding method, and the L₁-penalized normal loglikelihood method. We then apply the proposed methods to a portfolio selection problem using 80 series of daily stock returns. To facilitate the use of lasso in high-dimensional time series analysis, we develop the dynamic weighted lasso (DWL) algorithm that extends the LARS-lasso algorithm. In particular, the proposed algorithm can efficiently update the lasso solution as new data become available. It can also add or remove explanatory variables. The entire solution path of the L₁-penalized normal loglikelihood method is also constructed.     

Public Response to the Tokai Nuclear Accident

This article discusses the influence of the September 30, 1999 nuclear accident in Tokai village (Japan) on the public's attitudes toward nuclear power in Japan. The data used in this report were taken from the results of two surveys conducted mainly to measure the attitudes of the Japanese public with regard to the use of nuclear power in Japan. The first survey was done before the accident in District 23 in Tokyo and also in Osaka and Nagoya. The second survey, which took place after the accident in District 23 in Tokyo and in Osaka and Nagoya, also included residents in a number of other cities of various sizes throughout Japan. The results of the two surveys showed that (1) acceptability of and trust in nuclear power operation had decreased, (2) perceived accident likelihood and public interest had significantly increased, and (3) there had been neither significant nor even a small change in the public's self-rated knowledge about nuclear power or their distrust of the government. The results also showed that the ratio of nuclear power generation opponents to total respondents had considerably increased (7% to 23%) whereas nuclear power generation supporters had moderately decreased (1% to 12%).     

A permutation-based Bayesian approach for inverse covariance estimation

Abstract

Covariance estimation and selection for multivariate datasets in a high-dimensional regime is a fundamental problem in modern statistics. Gaussian graphical models are a popular class of models used for this purpose. Current Bayesian methods for inverse covariance matrix estimation under Gaussian graphical models require the underlying graph and hence the ordering of variables to be known. However, in practice, such information on the true underlying model is often unavailable. We therefore propose a novel permutation-based Bayesian approach to tackle the unknown variable ordering issue. In particular, we utilize multiple maximum a posteriori estimates under the DAG-Wishart prior for each permutation, and subsequently construct the final estimate of the inverse covariance matrix. The proposed estimator has smaller variability and yields order-invariant property. We establish posterior convergence rates under mild assumptions and illustrate that our method outperforms existing approaches in estimating the inverse covariance matrices via simulation studies.     

相对论性理想流体熵密度的计算

求解自引力非辐射体系的熵结构，这个问题很有意义．本文一般地导出相对论性流体热力学第二定律的协变表达式．利用理想流体的熵流守恒和局域能量守恒等基本守恒律推导出熵密度的计算公式．     

Spatio-temporal change-point modeling

There is by now a substantial literature on spatio-temporal modeling. However, to date, there exists essentially no literature which addresses the issue of process change from a certain time. In fact, if we look at change points for purely time series data, the customary form is to propose a model involving a mean or level shift. We see little attempting to capture a change in association structure. Part of the concern is how to specify flexible ways to bridge the association across the time point and still ensure that a proper joint distribution has been defined for all of the data. Introducing a spatial component evidently adds further complication. We want to allow for a change-point reflecting change in both temporal and spatial association. In this paper we propose a constructive, flexible model formulation through additive specifications. We also demonstrate how computational concerns benefit from the availability of temporal order. Finally, we illustrate with several simulated datasets to examine the capability of the model to detect different types of structural changes.     

On the Necessity of Structure in an Arbitrary World

Abstract

The term response generalization has been poorly defined and has, over many years, been a source of controversy for applied researchers who must grapple with results that show changes in behaviors outside of the response class targeted by their intervention. The present discussion seeks to differentiate response generalization from such terms as response covariation and induction. Instead, response generalization is redefined in the context of response classes and concurrent schedules of reinforcement.     

Portfolio optimization: New capabilities and future methods

Summary  This paper addresses the problem of portfolio selection in finance. In many cases, currently available software to compute the efficient frontier runs into difficulty in problems with more than about 600 securities. To proceed beyond this size, it is often necessary to modify the problem in which case there is typically a loss of information. In this paper, we discuss a computer capability that can exactly compute mean-variance efficient frontiers of problems with up to 2,000 securities in very reasonable time (even if a problem’s covariance matrix is 100% dense). The paper also discusses an augmentation to the theory of portfolio selection that allows multiple objectives (such as dividends, liquidity, social responsibility, amount invested in R&D, and so forth) to be incorporated into the portfolio selection process. In such problems, the efficient set is no longer a “frontier,” but is now best described as a “surface” with the interesting property that it is composed of platelets (like on the back of a turtle). Moreover, the computer capability that can compute the exact efficient frontier of a mean-variance problem with up to 2,000 securities also has, after additional coding, the ability to compute exactly all platelets of the efficient surface of a tri-criterion portfolio problem with up to 400 securities.

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Zusammenfassung  In dieser Arbeit stellen wir einen leistungsf?higen Rechenalgorithmus vor, um den effizienten Rand (die nichtdominierten Alternativen) von Portfolio-Auswahlproblemen in der Finanzierung zu bestimmen. Wir bezeichnen den Berechnungsalgorithmus, der in Java programmiert ist, mit MPQ (multi-parametric quadratic programming). MPQ weist gegenüber bisherigen Berechnungsverfahren eine Reihe von Vorteilen auf: Es kann für umfangreiche Anwendungsf?lle genutzt werden, ist durch passable Rechenzeiten charakterisiert und kann die Menge effizienter Alternativen in einem Bruchteil bisher üblicher Rechenzeiten bestimmen.

     

"已实现"波动率理论研究与评价

"已实现"波动率是一种全新的金融波动率测量方法。"已实现"波动率在理论上没有测量误差的无偏估计量,在实证建模方面比其他模型更易于估计参数,同时最优频率的选取对于"已实现"波动率的测量精确度是很重要的。